WorldWideScience

Sample records for dynamically updated adaptive

  1. Adaptive Fault Detection for Complex Dynamic Processes Based on JIT Updated Data Set

    Directory of Open Access Journals (Sweden)

    Jinna Li

    2012-01-01

    Full Text Available A novel fault detection technique is proposed to explicitly account for the nonlinear, dynamic, and multimodal problems existed in the practical and complex dynamic processes. Just-in-time (JIT detection method and k-nearest neighbor (KNN rule-based statistical process control (SPC approach are integrated to construct a flexible and adaptive detection scheme for the control process with nonlinear, dynamic, and multimodal cases. Mahalanobis distance, representing the correlation among samples, is used to simplify and update the raw data set, which is the first merit in this paper. Based on it, the control limit is computed in terms of both KNN rule and SPC method, such that we can identify whether the current data is normal or not by online approach. Noted that the control limit obtained changes with updating database such that an adaptive fault detection technique that can effectively eliminate the impact of data drift and shift on the performance of detection process is obtained, which is the second merit in this paper. The efficiency of the developed method is demonstrated by the numerical examples and an industrial case.

  2. Dynamic Data Updating Algorithm for Image Superresolution Reconstruction

    Institute of Scientific and Technical Information of China (English)

    TAN Bing; XU Qing; ZHANG Yan; XING Shuai

    2006-01-01

    A dynamic data updating algorithm for image superesolution is proposed. On the basis of Delaunay triangulation and its local updating property, this algorithm can update the changed region directly under the circumstances that only a part of the source images has been changed. For its high efficiency and adaptability, this algorithm can serve as a fast algorithm for image superesolution reconstruction.

  3. Secure Geographical routing in MANET using the Adaptive Position Update

    Directory of Open Access Journals (Sweden)

    Aruna Rao S.L

    2014-09-01

    Full Text Available MANETs are infrastructure free network, hence are mostly vulnerable to attacks and maintaining the anonymity of the nodes is also becoming a major concern. Most of the existing geographical routing methodology in Mobile Ad Hoc Networks (MANET does not include any position update mechanism for anonymous mobile nodes. In this paper, we propose a secure geographical routing which uses an adaptive position update technique for MANET. When source wants to transmit the data to destination, it establishes a secured geographical route using group signature. Then a position update technique is used to dynamically adjust the position of nodes based on mobility and network forwarding patterns. The malicious node detection technique is used to detect the malicious node. By simulation results, we show that the proposed technique reduces packet dropping and enhances the packet delivery ratio.

  4. Airborne Network Optimization with Dynamic Network Update

    Science.gov (United States)

    2015-03-26

    AIRBORNE NETWORK OPTIMIZATION WITH DYNAMIC NETWORK UPDATE THESIS Bradly S. Paul, Capt, USAF AFIT-ENG-MS-15-M-030 DEPARTMENT OF THE AIR FORCE AIR...to copyright protection in the United States. AFIT-ENG-MS-15-M-030 AIRBORNE NETWORK OPTIMIZATION WITH DYNAMIC NETWORK UPDATE THESIS Presented to the...NETWORK OPTIMIZATION WITH DYNAMIC NETWORK UPDATE Bradly S. Paul, B.S.C.P. Capt, USAF Committee Membership: Maj Thomas E. Dube Chair Dr. Kenneth M. Hopkinson

  5. The neural dynamics of updating person impressions.

    Science.gov (United States)

    Mende-Siedlecki, Peter; Cai, Yang; Todorov, Alexander

    2013-08-01

    Person perception is a dynamic, evolving process. Because other people are an endless source of social information, people need to update their impressions of others based upon new information. We devised an fMRI study to identify brain regions involved in updating impressions. Participants saw faces paired with valenced behavioral information and were asked to form impressions of these individuals. Each face was seen five times in a row, each time with a different behavioral description. Critically, for half of the faces the behaviors were evaluatively consistent, while for the other half they were inconsistent. In line with prior work, dorsomedial prefrontal cortex (dmPFC) was associated with forming impressions of individuals based on behavioral information. More importantly, a whole-brain analysis revealed a network of other regions associated with updating impressions of individuals who exhibited evaluatively inconsistent behaviors, including rostrolateral PFC, superior temporal sulcus, right inferior parietal lobule and posterior cingulate cortex.

  6. Partial update least-square adaptive filtering

    CERN Document Server

    Xie, Bei

    2014-01-01

    Adaptive filters play an important role in the fields related to digital signal processing and communication, such as system identification, noise cancellation, channel equalization, and beamforming. In practical applications, the computational complexity of an adaptive filter is an important consideration. The Least Mean Square (LMS) algorithm is widely used because of its low computational complexity (O(N)) and simplicity in implementation. The least squares algorithms, such as Recursive Least Squares (RLS), Conjugate Gradient (CG), and Euclidean Direction Search (EDS), can converge faster a

  7. Building nonredundant adaptive wavelets by update lifting

    NARCIS (Netherlands)

    Heijmans, H.J.A.M.; Pesquet-Popescu, B.; Piella, G.

    2002-01-01

    Adaptive wavelet decompositions appear useful in various applications in image and video processing, such as image analysis, compression, feature extraction, denoising and deconvolution, or optic flow estimation. For such tasks it may be important that the multiresolution representations take into a

  8. The Adaptation Finance Gap Update - with insights from the INDCs

    DEFF Research Database (Denmark)

    Olhoff, Anne; Bee, Skylar; Puig, Daniel

    In 2014 the United Nations Environment Programme (UNEP) published its first global Adaptation Gap Report (AGR 2014) (UNEP, 2014), which put forward a preliminary framework for assessing adaptation gaps along with an initial assessment in three selected areas: finance, technology and knowledge...... will be published in the spring of 2016. This update is intended as an input to discussions at the 21st session of the Conference of the Parties (COP 21) to the United Nations Framework Convention on Climate Change (UNFCCC). It brings together key findings on adaptation costs and finance from AGR 2014...... and preliminary findings from the 2016 assessment. Furthermore, it draws on insights concerning adaptation costs and related finance needs, as stated in the adaptation components in the Intended Nationally Determined Contributions (INDCs) – the post-2020 climate actions that countries intend to undertake...

  9. Dynamic adaption of vascular morphology

    DEFF Research Database (Denmark)

    Okkels, Fridolin; Jacobsen, Jens Christian Brings

    2012-01-01

    The structure of vascular networks adapts continuously to meet changes in demand of the surrounding tissue. Most of the known vascular adaptation mechanisms are based on local reactions to local stimuli such as pressure and flow, which in turn reflects influence from the surrounding tissue. Here we...... of the tissue are supplied. A set of model parameters uniquely determine the model dynamics, and we have identified the region of the best-performing model parameters (a global optimum). This region is surrounded in parameter space by less optimal model parameter values, and this separation is characterized...

  10. Adaptive information filtering for dynamic recommender systems

    CERN Document Server

    Jin, Ci-Hang; Zhang, Yi-Cheng; Zhou, Tao

    2009-01-01

    The dynamic environment in the real world calls for the adaptive techniques for information filtering, namely to provide real-time responses to the changes of system data. Where many incremental algorithms are designed for this purpose, they are usually challenged by the worse and worse performance resulted from the cumulative errors over time. In this Letter, we propose two incremental diffusion-based algorithms for the personalized recommendations, which integrate some pieces of local and fast updatings to achieve the approximate results. In addition to the fast responses, the errors of the proposed algorithms do not cumulate over time, that is to say, the global recomputing is unnecessary. This remarkable advantage is demonstrated by several metrics on algorithmic accuracy for two movie recommender systems and a social bookmarking system.

  11. Adaptive learning and complex dynamics

    Energy Technology Data Exchange (ETDEWEB)

    Gomes, Orlando [Escola Superior de Comunicacao Social, Instituto Politecnico de Lisboa, Unidade de Investigacao em Desenvolvimento Empresarial Economics Research Center - UNIDE/ISCTE - ERC, Campus de Benfica do IPL, 1549-014 Lisbon (Portugal)], E-mail: ogomes@escs.ipl.pt

    2009-10-30

    In this paper, we explore the dynamic properties of a group of simple deterministic difference equation systems in which the conventional perfect foresight assumption gives place to a mechanism of adaptive learning. These systems have a common feature: under perfect foresight (or rational expectations) they all possess a unique fixed point steady state. This long-term outcome is obtained also under learning if the quality underlying the learning process is high. Otherwise, when the degree of inefficiency of the learning process is relatively strong, nonlinear dynamics (periodic and a-periodic cycles) arise. The specific properties of each one of the proposed systems is explored both in terms of local and global dynamics. One macroeconomic model is used to illustrate how the formation of expectations through learning may eventually lead to awkward long-term outcomes.

  12. State of the art of dynamic software updating in Java

    DEFF Research Database (Denmark)

    Gregersen, Allan Raundahl; Rasmussen, Michael; Jørgensen, Bo Nørregaard

    2014-01-01

    comprehensive dynamic updating systems developed for Java to date. Together, these systems provide comprehensive support for changing class definitions of live objects, including adding, removing and moving fields, methods, classes and interfaces anywhere in the inheritance hierarchy. We then investigate...... that dynamic updating of class definitions for live objects may under some circumstances result in different run-time behavior than would be observed after a cold restart of the upgraded application. Finally, we conclude by discussing the implication of integrating the dynamic updating model of Gosh...

  13. Map updates in a dynamic Voronoi data structure

    DEFF Research Database (Denmark)

    Mioc, Darka; Antón Castro, Francesc/François; Gold, C. M.;

    2006-01-01

    the complex operations. This resulted in a new formal model for map updates, similar to "cellular encoding", where each update is uniquely characterized by the numbers of newly created and inactivated Voronoi regions. This research shows that the result of the formalization of the operations on the dynamic...

  14. Adaptive, dynamic, and resilient systems

    CERN Document Server

    Suri, Niranjan

    2015-01-01

    As the complexity of today's networked computer systems grows, they become increasingly difficult to understand, predict, and control. Addressing these challenges requires new approaches to building these systems. Adaptive, Dynamic, and Resilient Systems supplies readers with various perspectives of the critical infrastructure that systems of networked computers rely on. It introduces the key issues, describes their interrelationships, and presents new research in support of these areas.The book presents the insights of a different group of international experts in each chapter. Reporting on r

  15. Research on dynamic update transaction for Java classes

    Institute of Scientific and Technical Information of China (English)

    ZHANG Shi; HUANG Linpeng

    2007-01-01

    Dynamic software updating is critical for many systems that must provide continuous service.In addition,the Java language is gaining increasing popularity in developing distributed systems.Most previous works on updating are concerned with safely updating one class every time.It has many limitations on updating classes,such as not allowing deleting methods invoked in other classes.In this paper,the update transaction is purposed to dynamically update the class set,and some of its properties are discussed,such as atomicity,consistency,isolation,and durability (ACID).Then the property of type-safety is proven formally.In order to update without changing the Java Virtual Ma chine (JVM) and the Java programming language,this paper proposes a new implementation method.The method makes use of the Java class loading mechanism and reflection mechanism.We also present how to design an updatable Java program and a Java updating program.At the end of the paper,an experiment is made for analysis.

  16. Dynamic Model Updating Using Virtual Antiresonances

    Directory of Open Access Journals (Sweden)

    Walter D’Ambrogio

    2004-01-01

    Full Text Available This paper considers an extension of the model updating method that minimizes the antiresonance error, besides the natural frequency error. By defining virtual antiresonances, this extension allows the use of previously identified modal data. Virtual antiresonances can be evaluated from a truncated modal expansion, and do not correspond to any physical system. The method is applied to the Finite Element model updating of the GARTEUR benchmark, used within an European project on updating. Results are compared with those previously obtained by estimating actual antiresonances after computing low and high frequency residuals, and with results obtained by using the correlation (MAC between identified and analytical mode shapes.

  17. Adaptive Local Outlier Probability for Dynamic Process Monitoring

    Institute of Scientific and Technical Information of China (English)

    Yuxin Ma; Hongbo Shi; Mengling Wang

    2014-01-01

    Complex industrial processes often have multiple operating modes and present time-varying behavior. The data in one mode may follow specific Gaussian or non-Gaussian distributions. In this paper, a numerical y efficient moving window local outlier probability algorithm is proposed. Its key feature is the capability to handle complex data distributions and incursive operating condition changes including slow dynamic variations and instant mode shifts. First, a two-step adaption approach is introduced and some designed updating rules are applied to keep the monitoring model up-to-date. Then, a semi-supervised monitoring strategy is developed with an updating switch rule to deal with mode changes. Based on local probability models, the algorithm has a superior ability in detecting faulty conditions and fast adapting to slow variations and new operating modes. Final y, the utility of the proposed method is demonstrated with a numerical example and a non-isothermal continuous stirred tank reactor.

  18. Online Sequential Projection Vector Machine with Adaptive Data Mean Update

    Directory of Open Access Journals (Sweden)

    Lin Chen

    2016-01-01

    Full Text Available We propose a simple online learning algorithm especial for high-dimensional data. The algorithm is referred to as online sequential projection vector machine (OSPVM which derives from projection vector machine and can learn from data in one-by-one or chunk-by-chunk mode. In OSPVM, data centering, dimension reduction, and neural network training are integrated seamlessly. In particular, the model parameters including (1 the projection vectors for dimension reduction, (2 the input weights, biases, and output weights, and (3 the number of hidden nodes can be updated simultaneously. Moreover, only one parameter, the number of hidden nodes, needs to be determined manually, and this makes it easy for use in real applications. Performance comparison was made on various high-dimensional classification problems for OSPVM against other fast online algorithms including budgeted stochastic gradient descent (BSGD approach, adaptive multihyperplane machine (AMM, primal estimated subgradient solver (Pegasos, online sequential extreme learning machine (OSELM, and SVD + OSELM (feature selection based on SVD is performed before OSELM. The results obtained demonstrated the superior generalization performance and efficiency of the OSPVM.

  19. Evolutionary dynamics of metabolic adaptation

    NARCIS (Netherlands)

    van Hoek, M.J.A.

    2008-01-01

    In this thesis we study how organisms adapt their metabolism to a changing environment. Metabolic adaptation occurs at different timescales. Organisms adapt their metabolism via metabolic regulation, which happens in the order of minutes to hours and via evolution, which takes many generations. Here

  20. Evolutionary dynamics of metabolic adaptation

    NARCIS (Netherlands)

    van Hoek, M.J.A.

    2008-01-01

    In this thesis we study how organisms adapt their metabolism to a changing environment. Metabolic adaptation occurs at different timescales. Organisms adapt their metabolism via metabolic regulation, which happens in the order of minutes to hours and via evolution, which takes many generations. Here

  1. Dynamic movement-based location update in LEO networks

    Institute of Scientific and Technical Information of China (English)

    王亮; 张乃通; 马永奎

    2003-01-01

    Mobility management is an important aspect of the LEO systems. In terrestrial wireless network, the movement of the user triggers the location updating and determines the paging scheme, while in LEO satellite systems, the location updating and paging is mainly based on the movement of satellite. Terrestrial location management techniques must be altered to fit LEO systems. This paper introduces a modified movement-based location update and paging scheme in LEO networks. In this scheme we propose the meta-cell concept, which includes two spot-beams of one satellite. First we present the location management scheme based on the architecture with meta-cell location area. Then an analytical model is applied to formulate the cost of location updating and location paging for the and movement meta-cell based dynamic location update scheme. The comparison of performance between meta-cell architecture method and conventional signal-spot-cell architecture method is provided to demonstrate the cost-effectiveness and robust of the proposed scheme under various parameters. To reduce the impact of meta-cell architecture on location paging cost, we present forced location update strategy which used in the cases that the meta-cell includes the two spot-beams from different satellites.

  2. Structural Dynamics Model Updating with Positive Definiteness and No Spillover

    Directory of Open Access Journals (Sweden)

    Yongxin Yuan

    2014-01-01

    Full Text Available Model updating is a common method to improve the correlation between structural dynamics models and measured data. In conducting the updating, it is desirable to match only the measured spectral data without tampering with the other unmeasured and unknown eigeninformation in the original model (if so, the model is said to be updated with no spillover and to maintain the positive definiteness of the coefficient matrices. In this paper, an efficient numerical method for updating mass and stiffness matrices simultaneously is presented. The method first updates the modal frequencies. Then, a method is presented to construct a transformation matrix and this matrix is used to correct the analytical eigenvectors so that the updated model is compatible with the measurement of the eigenvectors. The method can preserve both no spillover and the symmetric positive definiteness of the mass and stiffness matrices. The method is computationally efficient as neither iteration nor numerical optimization is required. The numerical example shows that the presented method is quite accurate and efficient.

  3. Dynamic adaption of vascular morphology

    DEFF Research Database (Denmark)

    Okkels, Fridolin; Jacobsen, Jens Christian Brings

    2012-01-01

    The structure of vascular networks adapts continuously to meet changes in demand of the surrounding tissue. Most of the known vascular adaptation mechanisms are based on local reactions to local stimuli such as pressure and flow, which in turn reflects influence from the surrounding tissue. Here ...

  4. Dynamic adaption of vascular morphology

    DEFF Research Database (Denmark)

    Okkels, Fridolin; Jacobsen, Jens Christian Brings

    2012-01-01

    The structure of vascular networks adapts continuously to meet changes in demand of the surrounding tissue. Most of the known vascular adaptation mechanisms are based on local reactions to local stimuli such as pressure and flow, which in turn reflects influence from the surrounding tissue. Here we...

  5. Adaptive Dynamic Programming for Control Algorithms and Stability

    CERN Document Server

    Zhang, Huaguang; Luo, Yanhong; Wang, Ding

    2013-01-01

    There are many methods of stable controller design for nonlinear systems. In seeking to go beyond the minimum requirement of stability, Adaptive Dynamic Programming for Control approaches the challenging topic of optimal control for nonlinear systems using the tools of  adaptive dynamic programming (ADP). The range of systems treated is extensive; affine, switched, singularly perturbed and time-delay nonlinear systems are discussed as are the uses of neural networks and techniques of value and policy iteration. The text features three main aspects of ADP in which the methods proposed for stabilization and for tracking and games benefit from the incorporation of optimal control methods: • infinite-horizon control for which the difficulty of solving partial differential Hamilton–Jacobi–Bellman equations directly is overcome, and  proof provided that the iterative value function updating sequence converges to the infimum of all the value functions obtained by admissible control law sequences; • finite-...

  6. Dynamic optimization and adaptive controller design

    Science.gov (United States)

    Inamdar, S. R.

    2010-10-01

    In this work I present a new type of controller which is an adaptive tracking controller which employs dynamic optimization for optimizing current value of controller action for the temperature control of nonisothermal continuously stirred tank reactor (CSTR). We begin with a two-state model of nonisothermal CSTR which are mass and heat balance equations and then add cooling system dynamics to eliminate input multiplicity. The initial design value is obtained using local stability of steady states where approach temperature for cooling action is specified as a steady state and a design specification. Later we make a correction in the dynamics where material balance is manipulated to use feed concentration as a system parameter as an adaptive control measure in order to avoid actuator saturation for the main control loop. The analysis leading to design of dynamic optimization based parameter adaptive controller is presented. The important component of this mathematical framework is reference trajectory generation to form an adaptive control measure.

  7. Application of firefly algorithm to the dynamic model updating problem

    Science.gov (United States)

    Shabbir, Faisal; Omenzetter, Piotr

    2015-04-01

    Model updating can be considered as a branch of optimization problems in which calibration of the finite element (FE) model is undertaken by comparing the modal properties of the actual structure with these of the FE predictions. The attainment of a global solution in a multi dimensional search space is a challenging problem. The nature-inspired algorithms have gained increasing attention in the previous decade for solving such complex optimization problems. This study applies the novel Firefly Algorithm (FA), a global optimization search technique, to a dynamic model updating problem. This is to the authors' best knowledge the first time FA is applied to model updating. The working of FA is inspired by the flashing characteristics of fireflies. Each firefly represents a randomly generated solution which is assigned brightness according to the value of the objective function. The physical structure under consideration is a full scale cable stayed pedestrian bridge with composite bridge deck. Data from dynamic testing of the bridge was used to correlate and update the initial model by using FA. The algorithm aimed at minimizing the difference between the natural frequencies and mode shapes of the structure. The performance of the algorithm is analyzed in finding the optimal solution in a multi dimensional search space. The paper concludes with an investigation of the efficacy of the algorithm in obtaining a reference finite element model which correctly represents the as-built original structure.

  8. Generalized synchronization with uncertain parameters of nonlinear dynamic system via adaptive control.

    Science.gov (United States)

    Yang, Cheng-Hsiung; Wu, Cheng-Lin

    2014-01-01

    An adaptive control scheme is developed to study the generalized adaptive chaos synchronization with uncertain chaotic parameters behavior between two identical chaotic dynamic systems. This generalized adaptive chaos synchronization controller is designed based on Lyapunov stability theory and an analytic expression of the adaptive controller with its update laws of uncertain chaotic parameters is shown. The generalized adaptive synchronization with uncertain parameters between two identical new Lorenz-Stenflo systems is taken as three examples to show the effectiveness of the proposed method. The numerical simulations are shown to verify the results.

  9. The GBT Dynamic Scheduling System: An Update

    Science.gov (United States)

    Clark, M. H.; Balser, D. S.; Braatz, J.; Condon, J.; Creager, R. E.; McCarty, M. T.; Maddalena, R. J.; Marganian, P.; O'Neil, K.; Sessoms, E.; Shelton, A. L.

    2011-07-01

    The Robert C. Byrd Green Bank Telescope's (GBT) Dynamic Scheduling System (DSS), in production use since September 2009, was designed to maximize observing efficiency while maintaining the GBT's flexibility, improving data quality, and minimizing any undue adversity for the observers. Using observing criteria, observer availability and qualifications, three-dimensional weather forecasts, and telescope state, the DSS software is capable of optimally scheduling observers 24 to 48 hours in advance on a telescope having a wide-range of capabilities in a geographical location with variable weather patterns. Recent improvements for the GBT include an expanded frequency coverage (0.390-90 GHz), proper treatment of fully sampled array receivers, increasingly diverse observing criteria, the ability to account for atmospheric instability from clouds, and new tools for scheduling staff to control and interact with generated schedules and the underlying database.

  10. XML Labeling Schemes for Dynamic Updates: Strengths and Limitations

    Directory of Open Access Journals (Sweden)

    Samini Subramaniam

    2011-01-01

    Full Text Available The importance of XML processing has become a significant field at present days with the intention to support user queries in the most proficient way. In conjunction with this, many labeling schemes were proposed to identify the elements in XML document uniquely as well as preserve structural relationships among the nodes to cater queries with multiple combinations. On the other hand, due to the flexible structure of XML document, the data that is presented and communicated through this technology changes frequently. Therefore, labeling scheme must be able to support dynamic updates so that the existing labels do not require alteration. In this paper, we present some of the existing labeling techniques and their degree of support for structural relationship and dynamic updates.

  11. Towards cost-sensitive adaptation: when is it worth updating your predictive model?

    OpenAIRE

    Zliobaite, Indre; Budka, Marcin; Stahl, Frederic

    2015-01-01

    Our digital universe is rapidly expanding, more and more daily activities are digitally recorded, data arrives in streams, it needs to be analyzed in real time and may evolve over time. In the last decade many adaptive learning algorithms and prediction systems, which can automatically update themselves with the new incoming data, have been developed. The majority of those algorithms focus on improving the predictive performance and assume that model update is always desired as soon as possib...

  12. Updating prediction models by dynamical relaxation - An examination of the technique. [for numerical weather forecasting

    Science.gov (United States)

    Davies, H. C.; Turner, R. E.

    1977-01-01

    A dynamical relaxation technique for updating prediction models is analyzed with the help of the linear and nonlinear barotropic primitive equations. It is assumed that a complete four-dimensional time history of some prescribed subset of the meteorological variables is known. The rate of adaptation of the flow variables toward the true state is determined for a linearized f-model, and for mid-latitude and equatorial beta-plane models. The results of the analysis are corroborated by numerical experiments with the nonlinear shallow-water equations.

  13. An Adaptive Pheromone Updation of the Ant-System using LMS Technique

    Science.gov (United States)

    Paul, Abhishek; Mukhopadhyay, Sumitra

    2010-10-01

    We propose a modified model of pheromone updation for Ant-System, entitled as Adaptive Ant System (AAS), using the properties of basic Adaptive Filters. Here, we have exploited the properties of Least Mean Square (LMS) algorithm for the pheromone updation to find out the best minimum tour for the Travelling Salesman Problem (TSP). TSP library has been used for the selection of benchmark problem and the proposed AAS determines the minimum tour length for the problems containing large number of cities. Our algorithm shows effective results and gives least tour length in most of the cases as compared to other existing approaches.

  14. Dynamical Adaptation in Terrorist Cells/Networks

    DEFF Research Database (Denmark)

    Hussain, Dil Muhammad Akbar; Ahmed, Zaki

    2010-01-01

    Typical terrorist cells/networks have dynamical structure as they evolve or adapt to changes which may occur due to capturing or killing of a member of the cell/network. Analytical measures in graph theory like degree centrality, betweenness and closeness centralities are very common and have long...

  15. Overshooting dynamics in a model adaptive radiation

    NARCIS (Netherlands)

    Meyer, J.R.; Schoustra, S.E.; LaChapelle, J.; Kassen, R.K.

    2011-01-01

    The history of life is punctuated by repeated periods of unusually rapid evolutionary diversification called adaptive radiation. The dynamics of diversity during a radiation reflect an overshooting pattern with an initial phase of exponential-like increase followed by a slower decline. Much

  16. Complex and Adaptive Dynamical Systems A Primer

    CERN Document Server

    Gros, Claudius

    2011-01-01

    We are living in an ever more complex world, an epoch where human actions can accordingly acquire far-reaching potentialities. Complex and adaptive dynamical systems are ubiquitous in the world surrounding us and require us to adapt to new realities and the way of dealing with them. This primer has been developed with the aim of conveying a wide range of "commons-sense" knowledge in the field of quantitative complex system science at an introductory level, providing an entry point to this both fascinating and vitally important subject. The approach is modular and phenomenology driven. Examples of emerging phenomena of generic importance treated in this book are: -- The small world phenomenon in social and scale-free networks. -- Phase transitions and self-organized criticality in adaptive systems. -- Life at the edge of chaos and coevolutionary avalanches resulting from the unfolding of all living. -- The concept of living dynamical systems and emotional diffusive control within cognitive system theory. Techn...

  17. Complex and adaptive dynamical systems a primer

    CERN Document Server

    Gros, Claudius

    2007-01-01

    We are living in an ever more complex world, an epoch where human actions can accordingly acquire far-reaching potentialities. Complex and adaptive dynamical systems are ubiquitous in the world surrounding us and require us to adapt to new realities and the way of dealing with them. This primer has been developed with the aim of conveying a wide range of "commons-sense" knowledge in the field of quantitative complex system science at an introductory level, providing an entry point to this both fascinating and vitally important subject. The approach is modular and phenomenology driven. Examples of emerging phenomena of generic importance treated in this book are: -- The small world phenomenon in social and scale-free networks. -- Phase transitions and self-organized criticality in adaptive systems. -- Life at the edge of chaos and coevolutionary avalanches resulting from the unfolding of all living. -- The concept of living dynamical systems and emotional diffusive control within cognitive system theory. Techn...

  18. Robust master-slave synchronization for general uncertain delayed dynamical model based on adaptive control scheme.

    Science.gov (United States)

    Wang, Tianbo; Zhou, Wuneng; Zhao, Shouwei; Yu, Weiqin

    2014-03-01

    In this paper, the robust exponential synchronization problem for a class of uncertain delayed master-slave dynamical system is investigated by using the adaptive control method. Different from some existing master-slave models, the considered master-slave system includes bounded unmodeled dynamics. In order to compensate the effect of unmodeled dynamics and effectively achieve synchronization, a novel adaptive controller with simple updated laws is proposed. Moreover, the results are given in terms of LMIs, which can be easily solved by LMI Toolbox in Matlab. A numerical example is given to illustrate the effectiveness of the method.

  19. Enhancement of ELDA Tracker Based on CNN Features and Adaptive Model Update.

    Science.gov (United States)

    Gao, Changxin; Shi, Huizhang; Yu, Jin-Gang; Sang, Nong

    2016-04-15

    Appearance representation and the observation model are the most important components in designing a robust visual tracking algorithm for video-based sensors. Additionally, the exemplar-based linear discriminant analysis (ELDA) model has shown good performance in object tracking. Based on that, we improve the ELDA tracking algorithm by deep convolutional neural network (CNN) features and adaptive model update. Deep CNN features have been successfully used in various computer vision tasks. Extracting CNN features on all of the candidate windows is time consuming. To address this problem, a two-step CNN feature extraction method is proposed by separately computing convolutional layers and fully-connected layers. Due to the strong discriminative ability of CNN features and the exemplar-based model, we update both object and background models to improve their adaptivity and to deal with the tradeoff between discriminative ability and adaptivity. An object updating method is proposed to select the "good" models (detectors), which are quite discriminative and uncorrelated to other selected models. Meanwhile, we build the background model as a Gaussian mixture model (GMM) to adapt to complex scenes, which is initialized offline and updated online. The proposed tracker is evaluated on a benchmark dataset of 50 video sequences with various challenges. It achieves the best overall performance among the compared state-of-the-art trackers, which demonstrates the effectiveness and robustness of our tracking algorithm.

  20. Enhancement of ELDA Tracker Based on CNN Features and Adaptive Model Update

    Directory of Open Access Journals (Sweden)

    Changxin Gao

    2016-04-01

    Full Text Available Appearance representation and the observation model are the most important components in designing a robust visual tracking algorithm for video-based sensors. Additionally, the exemplar-based linear discriminant analysis (ELDA model has shown good performance in object tracking. Based on that, we improve the ELDA tracking algorithm by deep convolutional neural network (CNN features and adaptive model update. Deep CNN features have been successfully used in various computer vision tasks. Extracting CNN features on all of the candidate windows is time consuming. To address this problem, a two-step CNN feature extraction method is proposed by separately computing convolutional layers and fully-connected layers. Due to the strong discriminative ability of CNN features and the exemplar-based model, we update both object and background models to improve their adaptivity and to deal with the tradeoff between discriminative ability and adaptivity. An object updating method is proposed to select the “good” models (detectors, which are quite discriminative and uncorrelated to other selected models. Meanwhile, we build the background model as a Gaussian mixture model (GMM to adapt to complex scenes, which is initialized offline and updated online. The proposed tracker is evaluated on a benchmark dataset of 50 video sequences with various challenges. It achieves the best overall performance among the compared state-of-the-art trackers, which demonstrates the effectiveness and robustness of our tracking algorithm.

  1. A Novel Inconsistency Prevention Approach to Dynamic Updating of Web Applications

    Directory of Open Access Journals (Sweden)

    Seyed Habib Seifzadeh

    2013-01-01

    Full Text Available Software update requires that running program is stopped, patched and then restarted from start. This cycle mainly causes disruptions to the programs' execution which may be undesirable. Disruptions could turn out to be more problematic in the web applications, because they usually have to provide round-the-clock services. Nowadays, there are systems called Dynamic Updating Systems which are able to update programs without disruption. However, a dynamic updating system capable of updating web applications is infrequent to date. The present study aims to propose approaches needed to compose a web-based dynamic updating system. Providing these approaches, we have focused on preserving programs' consistency. To this end, different states of a web application are considered, and actions which the dynamic updating system must perform in each state are described. This paper concludes with a discussion about the implementation and the evaluation of the proposed approaches.

  2. Community-based adaptation to climate change: an update

    Energy Technology Data Exchange (ETDEWEB)

    Ayers, Jessica; Huq, Saleemul

    2009-06-15

    Over a billion people - the world's poorest and most bulnerable communities – will bear the brunt of climate change. For them, building local capacity to cope is a vital step towards resilience. Community-based adaptation (CBA) is emerging as a key response to this challenge. Tailored to local cultures and conditions, CBA supports and builds on autonomous adaptations to climate variability, such as the traditional baira or floating gardens of Bangladesh, which help small farmers' crops survive climate-driven floods. Above all, CBA is participatory – a process involving both local stakeholders, and development and disaster risk reduction practitioners. As such, it builds on existing cultural norms while addressing local development issues that contribute to climate vulnerability. CBA is now gaining ground in many regions, and is ripe for the reassessment offered here.

  3. Run-time Phenomena in Dynamic Software Updating: Causes and Effects

    DEFF Research Database (Denmark)

    Gregersen, Allan Raundahl; Jørgensen, Bo Nørregaard

    2011-01-01

    The development of a dynamic software updating system for statically-typed object-oriented programming languages has turned out to be a challenging task. Despite the fact that the present state of the art in dynamic updating systems, like JRebel, Dynamic Code Evolution VM, JVolve and Javeleon, al...

  4. Obesity: a disease or a biological adaptation? An update.

    Science.gov (United States)

    Chaput, J-P; Doucet, E; Tremblay, A

    2012-08-01

    Obesity is characterized by the accumulation of excess body fat and can be conceptualized as the physical manifestation of chronic energy excess. An important challenge of today's world is that our so-called obesogenic environment is conducive to the consumption of energy and unfavourable to the expenditure of energy. The modern, computer-dependent, sleep-deprived, physically inactive humans live chronically stressed in a society of food abundance. From a physiological standpoint, the excess weight gain observed in prone individuals is perceived as a normal consequence to a changed environment rather than a pathological process. In other words, weight gain is a sign of our contemporary way of living or a 'collateral damage' in the physiological struggle against modernity. Additionally, substantial body fat loss can complicate appetite control, decrease energy expenditure to a greater extent than predicted, increase the proneness to hypoglycaemia and its related risk towards depressive symptoms, increase the plasma and tissue levels of persistent organic pollutants that promote hormone disruption and metabolic complications, all of which are adaptations that can increase the risk of weight regain. In contrast, body fat gain generally provides the opposite adaptations, emphasizing that obesity may realistically be perceived as an a priori biological adaptation for most individuals. Accordingly, prevention and treatment strategies for obesity should ideally target the main drivers or root causes of body fat gain in order to be able to improve the health of the population. © 2012 The Authors. obesity reviews © 2012 International Association for the Study of Obesity.

  5. Soft sensor modelling by time difference, recursive partial least squares and adaptive model updating

    Science.gov (United States)

    Fu, Y.; Yang, W.; Xu, O.; Zhou, L.; Wang, J.

    2017-04-01

    To investigate time-variant and nonlinear characteristics in industrial processes, a soft sensor modelling method based on time difference, moving-window recursive partial least square (PLS) and adaptive model updating is proposed. In this method, time difference values of input and output variables are used as training samples to construct the model, which can reduce the effects of the nonlinear characteristic on modelling accuracy and retain the advantages of recursive PLS algorithm. To solve the high updating frequency of the model, a confidence value is introduced, which can be updated adaptively according to the results of the model performance assessment. Once the confidence value is updated, the model can be updated. The proposed method has been used to predict the 4-carboxy-benz-aldehyde (CBA) content in the purified terephthalic acid (PTA) oxidation reaction process. The results show that the proposed soft sensor modelling method can reduce computation effectively, improve prediction accuracy by making use of process information and reflect the process characteristics accurately.

  6. Shape Morphing Adaptive Radiator Technology (SMART) Updates to Techport Entry

    Science.gov (United States)

    Erickson, Lisa; Bertagne, Christopher; Hartl, Darren; Witcomb, John; Cognata, Thomas

    2017-01-01

    The Shape-Morphing Adaptive Radiator Technology (SMART) project builds off the FY16 research effort that developed a flexible composite radiator panel and demonstrated its ability to actuate from SMA's attached to it. The proposed FY17 Shape-Morphing Adaptive Radiator Technology (SMART) project's goal is to 1) develop a practical radiator design with shape memory alloys (SMAs) bonded to the radiator's panel, and 2) build a multi-panel radiator prototype for subsequent system level thermal vacuum tests. The morphing radiator employs SMA materials to passively change its shape to adapt its rate of heat rejection to vehicle requirements. Conceptually, the radiator panel has a naturally closed position (like a cylinder) in a cold environment. Whenever the radiator's temperature gradually rises, SMA's affixed to the face sheet will pull the face sheet open a commensurate amount - increasing the radiators view to space and causing it to reject more heat. In a vehicle, the radiator's variable heat rejection capabilities would reduce the number of additional heat rejection devices in a vehicle's thermal control system. This technology aims to help achieve the required maximum to minimum heat rejection ratio required for manned space vehicles to adopt a lighter, simpler, single loop thermal control architecture (ATCS). Single loop architectures are viewed as an attractive means to reduce mass and complexity over traditional dual-loop solutions. However, fluids generally considered safe enough to flow within crewed cabins (e.g. propylene glycol-water mixtures) have much higher freezing points and viscosities than those used in the external sides of dual loop ATCSs (e.g. Ammonia and HFE7000).

  7. Adaptation dynamics of the quasispecies model

    Indian Academy of Sciences (India)

    Kavita Jain

    2008-08-01

    We study the adaptation dynamics of an initially maladapted population evolving via the elementary processes of mutation and selection. The evolution occurs on rugged fitness landscapes which are defined on the multi-dimensional genotypic space and have many local peaks separated by low fitness valleys. We mainly focus on the Eigen’s model that describes the deterministic dynamics of an infinite number of self-replicating molecules. In the stationary state, for small mutation rates such a population forms a quasispecies which consists of the fittest genotype and its closely related mutants. The quasispecies dynamics on rugged fitness landscape follow a punctuated (or step-like) pattern in which a population jumps from a low fitness peak to a higher one, stays there for a considerable time before shifting the peak again and eventually reaches the global maximum of the fitness landscape. We calculate exactly several properties of this dynamical process within a simplified version of the quasispecies model.

  8. Adaptation dynamics of the quasispecies model

    Science.gov (United States)

    Jain, Kavita

    2009-02-01

    We study the adaptation dynamics of an initially maladapted population evolving via the elementary processes of mutation and selection. The evolution occurs on rugged fitness landscapes which are defined on the multi-dimensional genotypic space and have many local peaks separated by low fitness valleys. We mainly focus on the Eigen's model that describes the deterministic dynamics of an infinite number of self-replicating molecules. In the stationary state, for small mutation rates such a population forms a {\\it quasispecies} which consists of the fittest genotype and its closely related mutants. The quasispecies dynamics on rugged fitness landscape follow a punctuated (or step-like) pattern in which a population jumps from a low fitness peak to a higher one, stays there for a considerable time before shifting the peak again and eventually reaches the global maximum of the fitness landscape. We calculate exactly several properties of this dynamical process within a simplified version of the quasispecies model.

  9. Adaptive Event-Triggered Control Based on Heuristic Dynamic Programming for Nonlinear Discrete-Time Systems.

    Science.gov (United States)

    Dong, Lu; Zhong, Xiangnan; Sun, Changyin; He, Haibo

    2016-04-08

    This paper presents the design of a novel adaptive event-triggered control method based on the heuristic dynamic programming (HDP) technique for nonlinear discrete-time systems with unknown system dynamics. In the proposed method, the control law is only updated when the event-triggered condition is violated. Compared with the periodic updates in the traditional adaptive dynamic programming (ADP) control, the proposed method can reduce the computation and transmission cost. An actor-critic framework is used to learn the optimal event-triggered control law and the value function. Furthermore, a model network is designed to estimate the system state vector. The main contribution of this paper is to design a new trigger threshold for discrete-time systems. A detailed Lyapunov stability analysis shows that our proposed event-triggered controller can asymptotically stabilize the discrete-time systems. Finally, we test our method on two different discrete-time systems, and the simulation results are included.

  10. Optical ballast and adaptive dynamic stable resonator

    Institute of Scientific and Technical Information of China (English)

    Zhang Guang-Yin; Jiao Zhi-Yong; Guo Shu-Guang; Zhang Xiao-Hua; Gu Xue-Wen; Yan Cai-Fan; Wu Ding-Er; Song Feng

    2004-01-01

    In this paper a new concept of ‘optical ballast' is put forward. Optical ballast is a kind of device that can be used to decrease the variation and fluctuation of the propagation characteristics of light beams caused by the disturbance of refractive index of the medium. To illustrate the idea clearly and concretely, a fully adaptive dynamic stable solid-state laser resonator is presented as application example of optical ballast.

  11. A Dynamic Programming Approach to Adaptive Fractionation

    CERN Document Server

    Ramakrishnan, Jagdish; Bortfeld, Thomas; Tsitsiklis, John

    2011-01-01

    We formulate a previously introduced adaptive fractionation problem in a dynamic programming (DP) framework and explore various solution techniques. The two messages of this paper are: (i) the DP model is a useful framework for studying adaptive radiation therapy, particularly adaptive fractionation, and (ii) there is a potential for substantial decrease in dose to the primary organ-at-risk (OAR), or equivalently increase in tumor escalation, when using an adaptive fraction size. The essence of adaptive fractionation is to increase the fraction size when observing a "favorable" anatomy or when the tumor and OAR are far apart and to decrease the fraction size when they are close together. Given that a fixed prescribed dose must be delivered to the tumor over the course of the treatment, such an approach results in a lower cumulative dose to the OAR when compared to that resulting from standard fractionation. We first establish a benchmark by using the DP algorithm to solve the problem exactly. In this case, we...

  12. Synaptic dynamics: linear model and adaptation algorithm.

    Science.gov (United States)

    Yousefi, Ali; Dibazar, Alireza A; Berger, Theodore W

    2014-08-01

    In this research, temporal processing in brain neural circuitries is addressed by a dynamic model of synaptic connections in which the synapse model accounts for both pre- and post-synaptic processes determining its temporal dynamics and strength. Neurons, which are excited by the post-synaptic potentials of hundred of the synapses, build the computational engine capable of processing dynamic neural stimuli. Temporal dynamics in neural models with dynamic synapses will be analyzed, and learning algorithms for synaptic adaptation of neural networks with hundreds of synaptic connections are proposed. The paper starts by introducing a linear approximate model for the temporal dynamics of synaptic transmission. The proposed linear model substantially simplifies the analysis and training of spiking neural networks. Furthermore, it is capable of replicating the synaptic response of the non-linear facilitation-depression model with an accuracy better than 92.5%. In the second part of the paper, a supervised spike-in-spike-out learning rule for synaptic adaptation in dynamic synapse neural networks (DSNN) is proposed. The proposed learning rule is a biologically plausible process, and it is capable of simultaneously adjusting both pre- and post-synaptic components of individual synapses. The last section of the paper starts with presenting the rigorous analysis of the learning algorithm in a system identification task with hundreds of synaptic connections which confirms the learning algorithm's accuracy, repeatability and scalability. The DSNN is utilized to predict the spiking activity of cortical neurons and pattern recognition tasks. The DSNN model is demonstrated to be a generative model capable of producing different cortical neuron spiking patterns and CA1 Pyramidal neurons recordings. A single-layer DSNN classifier on a benchmark pattern recognition task outperforms a 2-Layer Neural Network and GMM classifiers while having fewer numbers of free parameters and

  13. Adaptive Nonlinear Model Predictive Control Using an On-line Support Vector Regression Updating Strategy

    Institute of Scientific and Technical Information of China (English)

    Ping Wang; Chaohe Yang; Xuemin Tian; Dexian Huang

    2014-01-01

    The performance of data-driven models relies heavily on the amount and quality of training samples, so it might deteriorate significantly in the regions where samples are scarce. The objective of this paper is to develop an on-line SVR model updating strategy to track the change in the process characteristics efficiently with affordable computational burden. This is achieved by adding a new sample that violates the Karush-Kuhn-Tucker condi-tions of the existing SVR model and by deleting the old sample that has the maximum distance with respect to the newly added sample in feature space. The benefits offered by such an updating strategy are exploited to develop an adaptive model-based control scheme, where model updating and control task perform alternately. The effectiveness of the adaptive controller is demonstrated by simulation study on a continuous stirred tank reactor. The results reveal that the adaptive MPC scheme outperforms its non-adaptive counterpart for large-magnitude set point changes and variations in process parameters.

  14. The effect of retinal image error update rate on human vestibulo-ocular reflex gain adaptation.

    Science.gov (United States)

    Fadaee, Shannon B; Migliaccio, Americo A

    2016-04-01

    The primary function of the angular vestibulo-ocular reflex (VOR) is to stabilise images on the retina during head movements. Retinal image movement is the likely feedback signal that drives VOR modification/adaptation for different viewing contexts. However, it is not clear whether a retinal image position or velocity error is used primarily as the feedback signal. Recent studies examining this signal are limited because they used near viewing to modify the VOR. However, it is not known whether near viewing drives VOR adaptation or is a pre-programmed contextual cue that modifies the VOR. Our study is based on analysis of the VOR evoked by horizontal head impulses during an established adaptation task. Fourteen human subjects underwent incremental unilateral VOR adaptation training and were tested using the scleral search coil technique over three separate sessions. The update rate of the laser target position (source of the retinal image error signal) used to drive VOR adaptation was different for each session [50 (once every 20 ms), 20 and 15/35 Hz]. Our results show unilateral VOR adaptation occurred at 50 and 20 Hz for both the active (23.0 ± 9.6 and 11.9 ± 9.1% increase on adapting side, respectively) and passive VOR (13.5 ± 14.9, 10.4 ± 12.2%). At 15 Hz, unilateral adaptation no longer occurred in the subject group for both the active and passive VOR, whereas individually, 4/9 subjects tested at 15 Hz had significant adaptation. Our findings suggest that 1-2 retinal image position error signals every 100 ms (i.e. target position update rate 15-20 Hz) are sufficient to drive VOR adaptation.

  15. Adaptive optics scanning laser ophthalmoscope imaging: technology update.

    Science.gov (United States)

    Merino, David; Loza-Alvarez, Pablo

    2016-01-01

    Adaptive optics (AO) retinal imaging has become very popular in the past few years, especially within the ophthalmic research community. Several different retinal techniques, such as fundus imaging cameras or optical coherence tomography systems, have been coupled with AO in order to produce impressive images showing individual cell mosaics over different layers of the in vivo human retina. The combination of AO with scanning laser ophthalmoscopy has been extensively used to generate impressive images of the human retina with unprecedented resolution, showing individual photoreceptor cells, retinal pigment epithelium cells, as well as microscopic capillary vessels, or the nerve fiber layer. Over the past few years, the technique has evolved to develop several different applications not only in the clinic but also in different animal models, thanks to technological developments in the field. These developments have specific applications to different fields of investigation, which are not limited to the study of retinal diseases but also to the understanding of the retinal function and vision science. This review is an attempt to summarize these developments in an understandable and brief manner in order to guide the reader into the possibilities that AO scanning laser ophthalmoscopy offers, as well as its limitations, which should be taken into account when planning on using it.

  16. Adaptive optics scanning laser ophthalmoscope imaging: technology update

    Directory of Open Access Journals (Sweden)

    Merino D

    2016-04-01

    Full Text Available David Merino, Pablo Loza-Alvarez The Institute of Photonic Sciences (ICFO, The Barcelona Institute of Science and Technology, Castelldefels, Barcelona, Spain Abstract: Adaptive optics (AO retinal imaging has become very popular in the past few years, especially within the ophthalmic research community. Several different retinal techniques, such as fundus imaging cameras or optical coherence tomography systems, have been coupled with AO in order to produce impressive images showing individual cell mosaics over different layers of the in vivo human retina. The combination of AO with scanning laser ophthalmoscopy has been extensively used to generate impressive images of the human retina with unprecedented resolution, showing individual photoreceptor cells, retinal pigment epithelium cells, as well as microscopic capillary vessels, or the nerve fiber layer. Over the past few years, the technique has evolved to develop several different applications not only in the clinic but also in different animal models, thanks to technological developments in the field. These developments have specific applications to different fields of investigation, which are not limited to the study of retinal diseases but also to the understanding of the retinal function and vision science. This review is an attempt to summarize these developments in an understandable and brief manner in order to guide the reader into the possibilities that AO scanning laser ophthalmoscopy offers, as well as its limitations, which should be taken into account when planning on using it. Keywords: high-resolution, in vivo retinal imaging, AOSLO

  17. Choreographies and Behavioural Contracts on the Way to Dynamic Updates

    Directory of Open Access Journals (Sweden)

    Mario Bravetti

    2014-11-01

    Full Text Available We survey our work on choreographies and behavioural contracts in multiparty interactions. In particular theories of behavioural contracts are presented which enable reasoning about correct service composition (contract compliance and service substitutability (contract refinement preorder under different assumptions concerning service communication: synchronous address or name based communication with patient non-preemptable or impatient invocations, or asynchronous communication. Correspondingly relations between behavioural contracts and choreographic descriptions are considered, where a contract for each communicating party is, e.g., derived by projection. The considered relations are induced as the maximal preoders which preserve contract compliance and global traces: we show maximality to hold (permitting services to be discovered/substituted independently for each party when contract refinement preorders with all the above asymmetric communication means are considered and, instead, not to hold if the standard symmetric CCS/pi-calculus communication is considered (or when directly relating choreographies to behavioral contracts via a preorder, no matter the communication mean. The obtained maximal preorders are then characterized in terms of a new form of testing, called compliance testing, where not only tests must succeed but also the system under test (thus relating to controllability theory, and compared with classical preorders such as may/must testing, trace inclusion, etc. Finally, recent work about adaptable choreographies and behavioural contracts is presented, where the theory above is extended to update mechanisms allowing choreographies/contracts to be modified at run-time by internal (self-adaptation or external intervention.

  18. Strategy updating rules and strategy distributions in dynamical multiagent systems

    Science.gov (United States)

    Hod, Shahar; Nakar, Ehud

    2003-08-01

    In the evolutionary version of the minority game, agents update their strategies (gene value p) in order to improve their performance. Motivated by the recent intriguing results obtained for prize-to-fine ratios, which are smaller than unity, we explore the system’s dynamics with a strategy updating rule of the form p→p±δp (0⩽p⩽1). We find that the strategy distribution depends strongly on the values of the prize-to-fine ratio R, the length scale δp, and the type of boundary condition used. We show that these parameters determine the amplitude and the frequency of the temporal oscillations observed in the gene space. These regular oscillations are shown to be the main factors which determine the strategy distribution of the population. In addition, we find that the agents characterized by p=1/2 (a coin-tossing strategy) have the best chances of survival at asymptotically long times, regardless of the value of δp and the boundary conditions used.

  19. Adaptive update using visual models for lifting-based motion-compensated temporal filtering

    Science.gov (United States)

    Li, Song; Xiong, H. K.; Wu, Feng; Chen, Hong

    2005-03-01

    Motion compensated temporal filtering is a useful framework for fully scalable video compression schemes. However, when supposed motion models cannot represent a real motion perfectly, both the temporal high and the temporal low frequency sub-bands may contain artificial edges, which possibly lead to a decreased coding efficiency, and ghost artifacts appear in the reconstructed video sequence at lower bit rates or in case of temporal scaling. We propose a new technique that is based on utilizing visual models to mitigate ghosting artifacts in the temporal low frequency sub-bands. Specifically, we propose content adaptive update schemes where visual models are used to determine image dependent upper bounds on information to be updated. Experimental results show that the proposed algorithm can significantly improve subjective visual quality of the low-pass temporal frames and at the same time, coding performance can catch or exceed the classical update steps.

  20. Dynamics and Control of Adaptive Shells with Curvature Transformations

    OpenAIRE

    1995-01-01

    Adaptive structures with controllable geometries and shapes are rather useful in many engineering applications, such as adaptive wings, variable focus mirrors, adaptive machines, micro-electromechanical systems, etc. Dynamics and feedback control effectiveness of adaptive shells whose curvatures are actively controlled and continuously changed are evaluated. An adaptive piezoelectric laminated cylindrical shell composite with continuous curvature changes is studied, and its natural frequencie...

  1. Cardiac fluid dynamics anticipates heart adaptation.

    Science.gov (United States)

    Pedrizzetti, Gianni; Martiniello, Alfonso R; Bianchi, Valter; D'Onofrio, Antonio; Caso, Pio; Tonti, Giovanni

    2015-01-21

    Hemodynamic forces represent an epigenetic factor during heart development and are supposed to influence the pathology of the grown heart. Cardiac blood motion is characterized by a vortical dynamics, and it is common belief that the cardiac vortex has a role in disease progressions or regression. Here we provide a preliminary demonstration about the relevance of maladaptive intra-cardiac vortex dynamics in the geometrical adaptation of the dysfunctional heart. We employed an in vivo model of patients who present a stable normal heart function in virtue of the cardiac resynchronization therapy (CRT, bi-ventricular pace-maker) and who are expected to develop left ventricle remodeling if pace-maker was switched off. Intra-ventricular fluid dynamics is analyzed by echocardiography (Echo-PIV). Under normal conditions, the flow presents a longitudinal alignment of the intraventricular hemodynamic forces. When pacing is temporarily switched off, flow forces develop a misalignment hammering onto lateral walls, despite no other electro-mechanical change is noticed. Hemodynamic forces result to be the first event that evokes a physiological activity anticipating cardiac changes and could help in the prediction of longer term heart adaptations.

  2. Emerging hierarchies in dynamically adapting webs

    Science.gov (United States)

    Katifori, Eleni; Graewer, Johannes; Magnasco, Marcelo; Modes, Carl

    Transport networks play a key role across four realms of eukaryotic life: slime molds, fungi, plants, and animals. In addition to the developmental algorithms that build them, many also employ adaptive strategies to respond to stimuli, damage, and other environmental changes. We model these adapting network architectures using a generic dynamical system on weighted graphs and find in simulation that these networks ultimately develop a hierarchical organization of the final weighted architecture accompanied by the formation of a system-spanning backbone. We quantify the hierarchical organization of the networks by developing an algorithm that decomposes the architecture to multiple scales and analyzes how the organization in each scale relates to that of the scale above and below it. The methodologies developed in this work are applicable to a wide range of systems including the slime mold physarum polycephalum, human microvasculature, and force chains in granular media.

  3. Key Techniques for Dynamic Updating of National Fundamental Geographic Information Database

    Directory of Open Access Journals (Sweden)

    WANG Donghua

    2015-07-01

    Full Text Available One of the most important missions of fundamental surveying and mapping work is to keep the fundamental geographic information fresh. In this respect, National Administration of Surveying, Mapping and Geoinformation has launched the project of dynamic updating of national fundamental geographic information database since 2012, which aims to update 1:50 000, 1:250 000 and 1:1 000 000 national fundamental geographic information database continuously and quickly, by updating and publishing once a year. This paper introduces the general technical thinking of dynamic updating, states main technical methods, such as dynamic updating of fundamental database, linkage updating of derived databases, and multi-tense database management and service and so on, and finally introduces main technical characteristics and engineering applications.

  4. Object Tracking Using Adaptive Covariance Descriptor and Clustering-Based Model Updating for Visual Surveillance

    Directory of Open Access Journals (Sweden)

    Lei Qin

    2014-05-01

    Full Text Available We propose a novel approach for tracking an arbitrary object in video sequences for visual surveillance. The first contribution of this work is an automatic feature extraction method that is able to extract compact discriminative features from a feature pool before computing the region covariance descriptor. As the feature extraction method is adaptive to a specific object of interest, we refer to the region covariance descriptor computed using the extracted features as the adaptive covariance descriptor. The second contribution is to propose a weakly supervised method for updating the object appearance model during tracking. The method performs a mean-shift clustering procedure among the tracking result samples accumulated during a period of time and selects a group of reliable samples for updating the object appearance model. As such, the object appearance model is kept up-to-date and is prevented from contamination even in case of tracking mistakes. We conducted comparing experiments on real-world video sequences, which confirmed the effectiveness of the proposed approaches. The tracking system that integrates the adaptive covariance descriptor and the clustering-based model updating method accomplished stable object tracking on challenging video sequences.

  5. A Model for Dynamic Adaptive Coscheduling

    Institute of Scientific and Technical Information of China (English)

    LU Sanglu; ZHOU Xiaobo; XIE Li

    1999-01-01

    This paper proposes a dynamic adaptive coscheduling modelDASIC to take advantage of excess available resources in anetwork of workstations (NOW). Besides coscheduling related subtasksdynamically, DASIC can scale up or down the process space dependingupon the number of available processors on an NOW. Based on thedynamic idle processor group (IPG), DASIC employs three modules: thecoscheduling module, the scalable scheduling module and the loadbalancing module, and uses six algorithms to achieve scalability. Asimplified DASIC was also implemented, and experimental results arepresented in this paper, which show that it can maximize systemutilization, and achieve task parallelism as much as possible.

  6. Adaptation dynamics in densely clustered chemoreceptors.

    Directory of Open Access Journals (Sweden)

    William Pontius

    Full Text Available In many sensory systems, transmembrane receptors are spatially organized in large clusters. Such arrangement may facilitate signal amplification and the integration of multiple stimuli. However, this organization likely also affects the kinetics of signaling since the cytoplasmic enzymes that modulate the activity of the receptors must localize to the cluster prior to receptor modification. Here we examine how these spatial considerations shape signaling dynamics at rest and in response to stimuli. As a model system, we use the chemotaxis pathway of Escherichia coli, a canonical system for the study of how organisms sense, respond, and adapt to environmental stimuli. In bacterial chemotaxis, adaptation is mediated by two enzymes that localize to the clustered receptors and modulate their activity through methylation-demethylation. Using a novel stochastic simulation, we show that distributive receptor methylation is necessary for successful adaptation to stimulus and also leads to large fluctuations in receptor activity in the steady state. These fluctuations arise from noise in the number of localized enzymes combined with saturated modification kinetics between the localized enzymes and the receptor substrate. An analytical model explains how saturated enzyme kinetics and large fluctuations can coexist with an adapted state robust to variation in the expression levels of the pathway constituents, a key requirement to ensure the functionality of individual cells within a population. This contrasts with the well-mixed covalent modification system studied by Goldbeter and Koshland in which mean activity becomes ultrasensitive to protein abundances when the enzymes operate at saturation. Large fluctuations in receptor activity have been quantified experimentally and may benefit the cell by enhancing its ability to explore empty environments and track shallow nutrient gradients. Here we clarify the mechanistic relationship of these large

  7. PAQ: Persistent Adaptive Query Middleware for Dynamic Environments

    Science.gov (United States)

    Rajamani, Vasanth; Julien, Christine; Payton, Jamie; Roman, Gruia-Catalin

    Pervasive computing applications often entail continuous monitoring tasks, issuing persistent queries that return continuously updated views of the operational environment. We present PAQ, a middleware that supports applications' needs by approximating a persistent query as a sequence of one-time queries. PAQ introduces an integration strategy abstraction that allows composition of one-time query responses into streams representing sophisticated spatio-temporal phenomena of interest. A distinguishing feature of our middleware is the realization that the suitability of a persistent query's result is a function of the application's tolerance for accuracy weighed against the associated overhead costs. In PAQ, programmers can specify an inquiry strategy that dictates how information is gathered. Since network dynamics impact the suitability of a particular inquiry strategy, PAQ associates an introspection strategy with a persistent query, that evaluates the quality of the query's results. The result of introspection can trigger application-defined adaptation strategies that alter the nature of the query. PAQ's simple API makes developing adaptive querying systems easily realizable. We present the key abstractions, describe their implementations, and demonstrate the middleware's usefulness through application examples and evaluation.

  8. Adaptive typography for dynamic mapping environments

    Science.gov (United States)

    Bardon, Didier

    1991-08-01

    When typography moves across a map, it passes over areas of different colors, densities, and textures. In such a dynamic environment, the aspect of typography must be constantly adapted to provide disernibility for every new background. Adaptive typography undergoes two adaptive operations: background control and contrast control. The background control prevents the features of the map (edges, lines, abrupt changes of densities) from destroying the integrity of the letterform. This is achieved by smoothing the features of the map in the area where a text label is displayed. The modified area is limited to the space covered by the characters of the label. Dispositions are taken to insure that the smoothing operation does not introduce any new visual noise. The contrast control assures that there are sufficient lightness differences between the typography and its ever-changing background. For every new situation, background color and foreground color are compared and the foreground color lightness is adjusted according to a chosen contrast value. Criteria and methods of choosing the appropriate contrast value are presented as well as the experiments that led to them.

  9. Method and system for training dynamic nonlinear adaptive filters which have embedded memory

    Science.gov (United States)

    Rabinowitz, Matthew (Inventor)

    2002-01-01

    Described herein is a method and system for training nonlinear adaptive filters (or neural networks) which have embedded memory. Such memory can arise in a multi-layer finite impulse response (FIR) architecture, or an infinite impulse response (IIR) architecture. We focus on filter architectures with separate linear dynamic components and static nonlinear components. Such filters can be structured so as to restrict their degrees of computational freedom based on a priori knowledge about the dynamic operation to be emulated. The method is detailed for an FIR architecture which consists of linear FIR filters together with nonlinear generalized single layer subnets. For the IIR case, we extend the methodology to a general nonlinear architecture which uses feedback. For these dynamic architectures, we describe how one can apply optimization techniques which make updates closer to the Newton direction than those of a steepest descent method, such as backpropagation. We detail a novel adaptive modified Gauss-Newton optimization technique, which uses an adaptive learning rate to determine both the magnitude and direction of update steps. For a wide range of adaptive filtering applications, the new training algorithm converges faster and to a smaller value of cost than both steepest-descent methods such as backpropagation-through-time, and standard quasi-Newton methods. We apply the algorithm to modeling the inverse of a nonlinear dynamic tracking system 5, as well as a nonlinear amplifier 6.

  10. A single-rate context-dependent learning process underlies rapid adaptation to familiar object dynamics.

    Directory of Open Access Journals (Sweden)

    James N Ingram

    2011-09-01

    Full Text Available Motor learning has been extensively studied using dynamic (force-field perturbations. These induce movement errors that result in adaptive changes to the motor commands. Several state-space models have been developed to explain how trial-by-trial errors drive the progressive adaptation observed in such studies. These models have been applied to adaptation involving novel dynamics, which typically occurs over tens to hundreds of trials, and which appears to be mediated by a dual-rate adaptation process. In contrast, when manipulating objects with familiar dynamics, subjects adapt rapidly within a few trials. Here, we apply state-space models to familiar dynamics, asking whether adaptation is mediated by a single-rate or dual-rate process. Previously, we reported a task in which subjects rotate an object with known dynamics. By presenting the object at different visual orientations, adaptation was shown to be context-specific, with limited generalization to novel orientations. Here we show that a multiple-context state-space model, with a generalization function tuned to visual object orientation, can reproduce the time-course of adaptation and de-adaptation as well as the observed context-dependent behavior. In contrast to the dual-rate process associated with novel dynamics, we show that a single-rate process mediates adaptation to familiar object dynamics. The model predicts that during exposure to the object across multiple orientations, there will be a degree of independence for adaptation and de-adaptation within each context, and that the states associated with all contexts will slowly de-adapt during exposure in one particular context. We confirm these predictions in two new experiments. Results of the current study thus highlight similarities and differences in the processes engaged during exposure to novel versus familiar dynamics. In both cases, adaptation is mediated by multiple context-specific representations. In the case of familiar

  11. Updating beliefs and combining evidence in adaptive forest management under climate change

    DEFF Research Database (Denmark)

    Yousefpour, Rasoul; Temperli, Christian; Bugmann, Harald;

    2013-01-01

    We study climate uncertainty and how managers' beliefs about climate change develop and influence their decisions. We develop an approach for updating knowledge and beliefs based on the observation of forest and climate variables and illustrate its application for the adaptive management of an even......-aged Norway spruce (Picea abies L. Karst) forest in the Black Forest, Germany. We simulated forest development under a range of climate change scenarios and forest management alternatives. Our analysis used Bayesian updating and Dempster's rule of combination to simulate how observations of climate and forest...... variables may influence a decision maker's beliefs about climate development and thereby management decisions. While forest managers may be inclined to rely on observed forest variables to infer climate change and impacts, we found that observation of climate state, e.g. temperature or precipitation...

  12. Towards Trustworthy Adaptive Case Management with Dynamic Condition Response Graphs

    DEFF Research Database (Denmark)

    Mukkamala, Raghava Rao; Hildebrandt, Thomas; Slaats, Tijs

    2013-01-01

    We describe how the declarative Dynamic Condition Response (DCR) Graphs process model can be used for trustworthy adaptive case management by leveraging the flexible execution, dynamic composition and adaptation supported by DCR Graphs. The dynamically composed and adapted graphs are verified...... for deadlock freedom and liveness in the SPIN model checker by utilizing a mapping from DCR Graphs to PROMELA code. We exemplify the approach by a small workflow extracted from a field study at a danish hospital....

  13. Complex and adaptive dynamical systems a primer

    CERN Document Server

    Gros, Claudius

    2015-01-01

    This primer offers readers an introduction to the central concepts that form our modern understanding of complex and emergent behavior, together with detailed coverage of accompanying mathematical methods. All calculations are presented step by step and are easy to follow. This new fourth edition has been fully reorganized and includes new chapters, figures and exercises. The core aspects of modern complex system sciences are presented in the first chapters, covering network theory, dynamical systems, bifurcation and catastrophe theory, chaos and adaptive processes, together with the principle of self-organization in reaction-diffusion systems and social animals. Modern information theoretical principles are treated in further chapters, together with the concept of self-organized criticality, gene regulation networks, hypercycles and coevolutionary avalanches, synchronization phenomena, absorbing phase transitions and the cognitive system approach to the brain. Technical course prerequisites are the standard ...

  14. Complex and adaptive dynamical systems a primer

    CERN Document Server

    Gros, Claudius

    2013-01-01

    Complex system theory is rapidly developing and gaining importance, providing tools and concepts central to our modern understanding of emergent phenomena. This primer offers an introduction to this area together with detailed coverage of the mathematics involved. All calculations are presented step by step and are straightforward to follow. This new third edition comes with new material, figures and exercises. Network theory, dynamical systems and information theory, the core of modern complex system sciences, are developed in the first three chapters, covering basic concepts and phenomena like small-world networks, bifurcation theory and information entropy. Further chapters use a modular approach to address the most important concepts in complex system sciences, with the emergence and self-organization playing a central role. Prominent examples are self-organized criticality in adaptive systems, life at the edge of chaos, hypercycles and coevolutionary avalanches, synchronization phenomena, absorbing phase...

  15. Adaptive control of force microscope cantilever dynamics

    Science.gov (United States)

    Jensen, S. E.; Dougherty, W. M.; Garbini, J. L.; Sidles, J. A.

    2007-09-01

    Magnetic resonance force microscopy (MRFM) and other emerging scanning probe microscopies entail the detection of attonewton-scale forces. Requisite force sensitivities are achieved through the use of soft force microscope cantilevers as high resonant-Q micromechanical oscillators. In practice, the dynamics of these oscillators are greatly improved by the application of force feedback control computed in real time by a digital signal processor (DSP). Improvements include increased sensitive bandwidth, reduced oscillator ring up/down time, and reduced cantilever thermal vibration amplitude. However, when the cantilever tip and the sample are in close proximity, electrostatic and Casimir tip-sample force gradients can significantly alter the cantilever resonance frequency, foiling fixed-gain narrow-band control schemes. We report an improved, adaptive control algorithm that uses a Hilbert transform technique to continuously measure the vibration frequency of the thermally-excited cantilever and seamlessly adjust the DSP program coefficients. The closed-loop vibration amplitude is typically 0.05 nm. This adaptive algorithm enables narrow-band formally-optimal control over a wide range of resonance frequencies, and preserves the thermally-limited signal to noise ratio (SNR).

  16. Update on Optical Design of Adaptive Optics System at Lick Observatory

    Energy Technology Data Exchange (ETDEWEB)

    Bauman, B J; Gavel, D T; Waltjen, K E; Freeze, G J; Hurd, R L; Gates, E I; Max, C E; Olivier, S S; Pennington, D M

    2001-07-31

    In 1999, we presented our plan to upgrade the adaptive optics (AO) system on the Lick Observatory Shane telescope (3m) from a prototype instrument pressed into field service to a facility instrument. This paper updates the progress of that plan and details several important improvements in the alignment and calibration of the AO bench. The paper also includes a discussion of the problems seen in the original design of the tip/tilt (t/t) sensor used in laser guide star mode, and how these problems were corrected with excellent results.

  17. Real Time Updating Genetic Network Programming for Adapting to the Change of Stock Prices

    Science.gov (United States)

    Chen, Yan; Mabu, Shingo; Shimada, Kaoru; Hirasawa, Kotaro

    The key in stock trading model is to take the right actions for trading at the right time, primarily based on the accurate forecast of future stock trends. Since an effective trading with given information of stock prices needs an intelligent strategy for the decision making, we applied Genetic Network Programming (GNP) to creating a stock trading model. In this paper, we propose a new method called Real Time Updating Genetic Network Programming (RTU-GNP) for adapting to the change of stock prices. There are three important points in this paper: First, the RTU-GNP method makes a stock trading decision considering both the recommendable information of technical indices and the candlestick charts according to the real time stock prices. Second, we combine RTU-GNP with a Sarsa learning algorithm to create the programs efficiently. Also, sub-nodes are introduced in each judgment and processing node to determine appropriate actions (buying/selling) and to select appropriate stock price information depending on the situation. Third, a Real Time Updating system has been firstly introduced in our paper considering the change of the trend of stock prices. The experimental results on the Japanese stock market show that the trading model with the proposed RTU-GNP method outperforms other models without real time updating. We also compared the experimental results using the proposed method with Buy&Hold method to confirm its effectiveness, and it is clarified that the proposed trading model can obtain much higher profits than Buy&Hold method.

  18. Accurate location estimation of moving object with energy constraint & adaptive update algorithms to save data

    CERN Document Server

    Semwal, Vijay Bhaskar; Bhaskar, Vinay S; Sati, Meenakshi

    2011-01-01

    In research paper "Accurate estimation of the target location of object with energy constraint & Adaptive Update Algorithms to Save Data" one of the central issues in sensor networks is track the location, of moving object which have overhead of saving data, an accurate estimation of the target location of object with energy constraint .We do not have any mechanism which control and maintain data .The wireless communication bandwidth is also very limited. Some field which is using this technique are flood and typhoon detection, forest fire detection, temperature and humidity and ones we have these information use these information back to a central air conditioning and ventilation system. In this research paper, we propose protocol based on the prediction and adaptive based algorithm which is using less sensor node reduced by an accurate estimation of the target location. we are using minimum three sensor node to get the accurate position .We can extend it upto four or five to find more accurate location ...

  19. Adaptive dynamics of extortion and compliance.

    Directory of Open Access Journals (Sweden)

    Christian Hilbe

    Full Text Available Direct reciprocity is a mechanism for the evolution of cooperation. For the iterated prisoner's dilemma, a new class of strategies has recently been described, the so-called zero-determinant strategies. Using such a strategy, a player can unilaterally enforce a linear relationship between his own payoff and the co-player's payoff. In particular the player may act in such a way that it becomes optimal for the co-player to cooperate unconditionally. In this way, a player can manipulate and extort his co-player, thereby ensuring that the own payoff never falls below the co-player's payoff. However, using a compliant strategy instead, a player can also ensure that his own payoff never exceeds the co-player's payoff. Here, we use adaptive dynamics to study when evolution leads to extortion and when it leads to compliance. We find a remarkable cyclic dynamics: in sufficiently large populations, extortioners play a transient role, helping the population to move from selfish strategies to compliance. Compliant strategies, however, can be subverted by altruists, which in turn give rise to selfish strategies. Whether cooperative strategies are favored in the long run critically depends on the size of the population; we show that cooperation is most abundant in large populations, in which case average payoffs approach the social optimum. Our results are not restricted to the case of the prisoners dilemma, but can be extended to other social dilemmas, such as the snowdrift game. Iterated social dilemmas in large populations do not lead to the evolution of strategies that aim to dominate their co-player. Instead, generosity succeeds.

  20. Adaptive dynamics of extortion and compliance.

    Science.gov (United States)

    Hilbe, Christian; Nowak, Martin A; Traulsen, Arne

    2013-01-01

    Direct reciprocity is a mechanism for the evolution of cooperation. For the iterated prisoner's dilemma, a new class of strategies has recently been described, the so-called zero-determinant strategies. Using such a strategy, a player can unilaterally enforce a linear relationship between his own payoff and the co-player's payoff. In particular the player may act in such a way that it becomes optimal for the co-player to cooperate unconditionally. In this way, a player can manipulate and extort his co-player, thereby ensuring that the own payoff never falls below the co-player's payoff. However, using a compliant strategy instead, a player can also ensure that his own payoff never exceeds the co-player's payoff. Here, we use adaptive dynamics to study when evolution leads to extortion and when it leads to compliance. We find a remarkable cyclic dynamics: in sufficiently large populations, extortioners play a transient role, helping the population to move from selfish strategies to compliance. Compliant strategies, however, can be subverted by altruists, which in turn give rise to selfish strategies. Whether cooperative strategies are favored in the long run critically depends on the size of the population; we show that cooperation is most abundant in large populations, in which case average payoffs approach the social optimum. Our results are not restricted to the case of the prisoners dilemma, but can be extended to other social dilemmas, such as the snowdrift game. Iterated social dilemmas in large populations do not lead to the evolution of strategies that aim to dominate their co-player. Instead, generosity succeeds.

  1. Dynamic finite element model updating of prestressed concrete continuous box-girder bridge

    Institute of Scientific and Technical Information of China (English)

    Lin Xiankun; Zhang Lingmi; Guo Qintao; Zhang Yufeng

    2009-01-01

    The dynamic finite element model (FEM) of a prestressed concrete continuous box-girder bridge, called the Tongyang Canal Bridge, is built and updated based on the results of ambient vibration testing (AVT) using a real-coded accelerating genetic algorithm (RAGA). The objective functions are defined based on natural frequency and modal assurance criterion (MAC) metrics to evaluate the updated FEM. Two objective functions are defined to fully account for the relative errors and standard deviations of the natural frequencies and MAC between the AVT results and the updated FEM predictions. The dynamically updated FEM of the bridge can better represent its structural dynamics and serve as a baseline in long-term health monitoring, condition assessment and damage identification over the service life of the bridge.

  2. Adaptive Control of Robot Manipulators With Uncertain Kinematics and Dynamics

    OpenAIRE

    Wang, Hanlei

    2014-01-01

    In this paper, we investigate the adaptive control problem for robot manipulators with both the uncertain kinematics and dynamics. We propose two adaptive control schemes to realize the objective of task-space trajectory tracking irrespective of the uncertain kinematics and dynamics. The proposed controllers have the desirable separation property, and we also show that the first adaptive controller with appropriate modifications can yield improved performance, without the expense of conservat...

  3. Dynamic test and finite element model updating of bridge structures based on ambient vibration

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    The dynamic characteristics of bridge structures are the basis of structural dynamic response and seismic analysis,and are also an important target of health condition monitoring.In this paper,a three-dimensional finite-element model is first established for a highway bridge over a railroad on No.312 National Highway.Based on design drawings,the dynamic characteristics of the bridge are studied using finite element analysis and ambient vibration measurements.Thus,a set of data is selected based on sensitivity analysis and optimization theory;the finite element model of the bridge is updated.The numerical and experimental results show that the updated method is more simple and effective,the updated finite element model can reflect the dynamic characteristics of the bridge better,and it can be used to predict the dynamic response under complex external forces.It is also helpful for further damage identification and health condition monitoring.

  4. The Hitchhiker’s Guide to Adaptive Dynamics

    Directory of Open Access Journals (Sweden)

    Jacob Johansson

    2013-06-01

    Full Text Available Adaptive dynamics is a mathematical framework for studying evolution. It extends evolutionary game theory to account for more realistic ecological dynamics and it can incorporate both frequency- and density-dependent selection. This is a practical guide to adaptive dynamics that aims to illustrate how the methodology can be applied to the study of specific systems. The theory is presented in detail for a single, monomorphic, asexually reproducing population. We explain the necessary terminology to understand the basic arguments in models based on adaptive dynamics, including invasion fitness, the selection gradient, pairwise invasibility plots (PIP, evolutionarily singular strategies, and the canonical equation. The presentation is supported with a worked-out example of evolution of arrival times in migratory birds. We show how the adaptive dynamics methodology can be extended to study evolution in polymorphic populations using trait evolution plots (TEPs. We give an overview of literature that generalises adaptive dynamics techniques to other scenarios, such as sexual, diploid populations, and spatially-structured populations. We conclude by discussing how adaptive dynamics relates to evolutionary game theory and how adaptive-dynamics techniques can be used in speciation research.

  5. Finite-element-model updating using computational intelligence techniques applications to structural dynamics

    CERN Document Server

    Marwala, Tshilidzi

    2010-01-01

    Finite element models (FEMs) are widely used to understand the dynamic behaviour of various systems. FEM updating allows FEMs to be tuned better to reflect measured data and may be conducted using two different statistical frameworks: the maximum likelihood approach and Bayesian approaches. Finite Element Model Updating Using Computational Intelligence Techniques applies both strategies to the field of structural mechanics, an area vital for aerospace, civil and mechanical engineering. Vibration data is used for the updating process. Following an introduction a number of computational intelligence techniques to facilitate the updating process are proposed; they include: • multi-layer perceptron neural networks for real-time FEM updating; • particle swarm and genetic-algorithm-based optimization methods to accommodate the demands of global versus local optimization models; • simulated annealing to put the methodologies into a sound statistical basis; and • response surface methods and expectation m...

  6. The Branching Bifurcation of Adaptive Dynamics

    Science.gov (United States)

    Della Rossa, Fabio; Dercole, Fabio; Landi, Pietro

    2015-06-01

    We unfold the bifurcation involving the loss of evolutionary stability of an equilibrium of the canonical equation of Adaptive Dynamics (AD). The equation deterministically describes the expected long-term evolution of inheritable traits — phenotypes or strategies — of coevolving populations, in the limit of rare and small mutations. In the vicinity of a stable equilibrium of the AD canonical equation, a mutant type can invade and coexist with the present — resident — types, whereas the fittest always win far from equilibrium. After coexistence, residents and mutants effectively diversify, according to the enlarged canonical equation, only if natural selection favors outer rather than intermediate traits — the equilibrium being evolutionarily unstable, rather than stable. Though the conditions for evolutionary branching — the joint effect of resident-mutant coexistence and evolutionary instability — have been known for long, the unfolding of the bifurcation has remained a missing tile of AD, the reason being related to the nonsmoothness of the mutant invasion fitness after branching. In this paper, we develop a methodology that allows the approximation of the invasion fitness after branching in terms of the expansion of the (smooth) fitness before branching. We then derive a canonical model for the branching bifurcation and perform its unfolding around the loss of evolutionary stability. We cast our analysis in the simplest (but classical) setting of asexual, unstructured populations living in an isolated, homogeneous, and constant abiotic environment; individual traits are one-dimensional; intra- as well as inter-specific ecological interactions are described in the vicinity of a stationary regime.

  7. Evolution of Word-updating Dynamical Systems (WDS) on Directed Graphs

    Institute of Scientific and Technical Information of China (English)

    ZHENG Jie

    2009-01-01

    This paper continues the research on theoretical foundations for computer simulation. We introduce the concept of word-updating dynamical systems (WDS) on directed graphs, which is a kind of generalization of sequential dynamical systems (SDS) on graphs. Some properties on WDS, especially some results on NOR -WDS,which are different from that on NOR -SDS, are obtained.

  8. Dynamic maintenance of majority information in constant time per update

    DEFF Research Database (Denmark)

    Frandsen, Gudmund Skovbjerg; Skyum, Sven

    1997-01-01

    We show how to maintain information about the existence of a majority colour in a set of elements under insertion and deletion of single elements using O(1) time and at most 4 equality tests on colours per update. No ordering information is used....

  9. Dynamic updating of hippocampal object representations reflects new conceptual knowledge.

    Science.gov (United States)

    Mack, Michael L; Love, Bradley C; Preston, Alison R

    2016-11-15

    Concepts organize the relationship among individual stimuli or events by highlighting shared features. Often, new goals require updating conceptual knowledge to reflect relationships based on different goal-relevant features. Here, our aim is to determine how hippocampal (HPC) object representations are organized and updated to reflect changing conceptual knowledge. Participants learned two classification tasks in which successful learning required attention to different stimulus features, thus providing a means to index how representations of individual stimuli are reorganized according to changing task goals. We used a computational learning model to capture how people attended to goal-relevant features and organized object representations based on those features during learning. Using representational similarity analyses of functional magnetic resonance imaging data, we demonstrate that neural representations in left anterior HPC correspond with model predictions of concept organization. Moreover, we show that during early learning, when concept updating is most consequential, HPC is functionally coupled with prefrontal regions. Based on these findings, we propose that when task goals change, object representations in HPC can be organized in new ways, resulting in updated concepts that highlight the features most critical to the new goal.

  10. Nonlinear Dynamic Model-Based Adaptive Control of a Solenoid-Valve System

    Directory of Open Access Journals (Sweden)

    DongBin Lee

    2012-01-01

    Full Text Available In this paper, a nonlinear model-based adaptive control approach is proposed for a solenoid-valve system. The challenge is that solenoids and butterfly valves have uncertainties in multiple parameters in the nonlinear model; various kinds of physical appearance such as size and stroke, dynamic parameters including inertia, damping, and torque coefficients, and operational parameters especially, pipe diameters and flow velocities. These uncertainties are making the system not only difficult to adjust to the environment, but also further complicated to develop the appropriate control approach for meeting the system objectives. The main contribution of this research is the application of adaptive control theory and Lyapunov-type stability approach to design a controller for a dynamic model of the solenoid-valve system in the presence of those uncertainties. The control objectives such as set-point regulation, parameter compensation, and stability are supposed to be simultaneously accomplished. The error signals are first formulated based on the nonlinear dynamic models and then the control input is developed using the Lyapunov stability-type analysis to obtain the error bounded while overcoming the uncertainties. The parameter groups are updated by adaptation laws using a projection algorithm. Numerical simulation results are shown to demonstrate good performance of the proposed nonlinear model-based adaptive approach and to compare the performance of the same solenoid-valve system with a non-adaptive method as well.

  11. An updating method for structural dynamics models with unknown excitations

    Energy Technology Data Exchange (ETDEWEB)

    Louf, F; Charbonnel, P E; Ladeveze, P [LMT-Cachan (ENS Cachan/CNRS/Paris 6 University) 61, avenue du Prsident Wilson, F-94235 Cachan Cedex (France); Gratien, C [Astrium (EADS space transportation) - Service TE 343 66, Route de Verneuil, 78133 Les Mureaux Cedex (France)], E-mail: charbonnel@lmt.ens-cachan.fr, E-mail: ladeveze@lmt.ens-cachan.fr, E-mail: louf@lmt.ens-cachan.fr, E-mail: christian.gratien@astrium.eads.net

    2008-11-01

    This paper presents an extension of the Constitutive Relation Error (CRE) updating method to complex industrial structures, such as space launchers, for which tests carried out in the functional context can provide significant amounts of information. Indeed, since several sources of excitation are involved simultaneously, a flight test can be viewed as a multiple test. However, there is a serious difficulty in that these sources of excitation are partially unknown. The CRE updating method enables one to obtain an estimate of these excitations. We present a first application of the method using a very simple finite element model of the Ariane V launcher along with measurements performed at the end of an atmospheric flight.

  12. Adaptive Sliding Mode Control of Dynamic Systems Using Double Loop Recurrent Neural Network Structure.

    Science.gov (United States)

    Fei, Juntao; Lu, Cheng

    2017-03-06

    In this paper, an adaptive sliding mode control system using a double loop recurrent neural network (DLRNN) structure is proposed for a class of nonlinear dynamic systems. A new three-layer RNN is proposed to approximate unknown dynamics with two different kinds of feedback loops where the firing weights and output signal calculated in the last step are stored and used as the feedback signals in each feedback loop. Since the new structure has combined the advantages of internal feedback NN and external feedback NN, it can acquire the internal state information while the output signal is also captured, thus the new designed DLRNN can achieve better approximation performance compared with the regular NNs without feedback loops or the regular RNNs with a single feedback loop. The new proposed DLRNN structure is employed in an equivalent controller to approximate the unknown nonlinear system dynamics, and the parameters of the DLRNN are updated online by adaptive laws to get favorable approximation performance. To investigate the effectiveness of the proposed controller, the designed adaptive sliding mode controller with the DLRNN is applied to a z-axis microelectromechanical system gyroscope to control the vibrating dynamics of the proof mass. Simulation results demonstrate that the proposed methodology can achieve good tracking property, and the comparisons of the approximation performance between radial basis function NN, RNN, and DLRNN show that the DLRNN can accurately estimate the unknown dynamics with a fast speed while the internal states of DLRNN are more stable.

  13. Dynamics and Control of Adaptive Shells with Curvature Transformations

    Directory of Open Access Journals (Sweden)

    H.S. Tzou

    1995-01-01

    Full Text Available Adaptive structures with controllable geometries and shapes are rather useful in many engineering applications, such as adaptive wings, variable focus mirrors, adaptive machines, micro-electromechanical systems, etc. Dynamics and feedback control effectiveness of adaptive shells whose curvatures are actively controlled and continuously changed are evaluated. An adaptive piezoelectric laminated cylindrical shell composite with continuous curvature changes is studied, and its natural frequencies and controlled damping ratios are evaluated. The curvature change of the adaptive shell starts from an open shallow shell (30° and ends with a deep cylindrical shell (360°. Dynamic characteristics and control effectiveness (via the proportional velocity feedback of this series of shells are investigated and compared at every 30° curvature change. Analytical solutions suggest that the lower modes are sensitive to curvature changes and the higher modes are relatively insensitive.

  14. A Neural Dynamic Architecture for Reaching and Grasping Integrates Perception and Movement Generation and Enables On-Line Updating

    Science.gov (United States)

    Knips, Guido; Zibner, Stephan K. U.; Reimann, Hendrik; Schöner, Gregor

    2017-01-01

    Reaching for objects and grasping them is a fundamental skill for any autonomous robot that interacts with its environment. Although this skill seems trivial to adults, who effortlessly pick up even objects they have never seen before, it is hard for other animals, for human infants, and for most autonomous robots. Any time during movement preparation and execution, human reaching movement are updated if the visual scene changes (with a delay of about 100 ms). The capability for online updating highlights how tightly perception, movement planning, and movement generation are integrated in humans. Here, we report on an effort to reproduce this tight integration in a neural dynamic process model of reaching and grasping that covers the complete path from visual perception to movement generation within a unified modeling framework, Dynamic Field Theory. All requisite processes are realized as time-continuous dynamical systems that model the evolution in time of neural population activation. Population level neural processes bring about the attentional selection of objects, the estimation of object shape and pose, and the mapping of pose parameters to suitable movement parameters. Once a target object has been selected, its pose parameters couple into the neural dynamics of movement generation so that changes of pose are propagated through the architecture to update the performed movement online. Implementing the neural architecture on an anthropomorphic robot arm equipped with a Kinect sensor, we evaluate the model by grasping wooden objects. Their size, shape, and pose are estimated from a neural model of scene perception that is based on feature fields. The sequential organization of a reach and grasp act emerges from a sequence of dynamic instabilities within a neural dynamics of behavioral organization, that effectively switches the neural controllers from one phase of the action to the next. Trajectory formation itself is driven by a dynamical systems version of

  15. A Neural Dynamic Architecture for Reaching and Grasping Integrates Perception and Movement Generation and Enables On-Line Updating.

    Science.gov (United States)

    Knips, Guido; Zibner, Stephan K U; Reimann, Hendrik; Schöner, Gregor

    2017-01-01

    Reaching for objects and grasping them is a fundamental skill for any autonomous robot that interacts with its environment. Although this skill seems trivial to adults, who effortlessly pick up even objects they have never seen before, it is hard for other animals, for human infants, and for most autonomous robots. Any time during movement preparation and execution, human reaching movement are updated if the visual scene changes (with a delay of about 100 ms). The capability for online updating highlights how tightly perception, movement planning, and movement generation are integrated in humans. Here, we report on an effort to reproduce this tight integration in a neural dynamic process model of reaching and grasping that covers the complete path from visual perception to movement generation within a unified modeling framework, Dynamic Field Theory. All requisite processes are realized as time-continuous dynamical systems that model the evolution in time of neural population activation. Population level neural processes bring about the attentional selection of objects, the estimation of object shape and pose, and the mapping of pose parameters to suitable movement parameters. Once a target object has been selected, its pose parameters couple into the neural dynamics of movement generation so that changes of pose are propagated through the architecture to update the performed movement online. Implementing the neural architecture on an anthropomorphic robot arm equipped with a Kinect sensor, we evaluate the model by grasping wooden objects. Their size, shape, and pose are estimated from a neural model of scene perception that is based on feature fields. The sequential organization of a reach and grasp act emerges from a sequence of dynamic instabilities within a neural dynamics of behavioral organization, that effectively switches the neural controllers from one phase of the action to the next. Trajectory formation itself is driven by a dynamical systems version of

  16. Global network reorganization during dynamic adaptations of Bacillus subtilis metabolism

    DEFF Research Database (Denmark)

    Buescher, Joerg Martin; Liebermeister, Wolfram; Jules, Matthieu

    2012-01-01

    Adaptation of cells to environmental changes requires dynamic interactions between metabolic and regulatory networks, but studies typically address only one or a few layers of regulation. For nutritional shifts between two preferred carbon sources of Bacillus subtilis, we combined statistical...

  17. DyNAvectors: dynamic constitutional vectors for adaptive DNA transfection.

    Science.gov (United States)

    Clima, Lilia; Peptanariu, Dragos; Pinteala, Mariana; Salic, Adrian; Barboiu, Mihail

    2015-12-25

    Dynamic constitutional frameworks, based on squalene, PEG and PEI components, reversibly connected to core centers, allow the efficient identification of adaptive vectors for good DNA transfection efficiency and are well tolerated by mammalian cells.

  18. Adaptive Network Dynamics and Evolution of Leadership in Collective Migration

    CERN Document Server

    Pais, Darren

    2013-01-01

    The evolution of leadership in migratory populations depends not only on costs and benefits of leadership investments but also on the opportunities for individuals to rely on cues from others through social interactions. We derive an analytically tractable adaptive dynamic network model of collective migration with fast timescale migration dynamics and slow timescale adaptive dynamics of individual leadership investment and social interaction. For large populations, our analysis of bifurcations with respect to investment cost explains the observed hysteretic effect associated with recovery of migration in fragmented environments. Further, we show a minimum connectivity threshold above which there is evolutionary branching into leader and follower populations. For small populations, we show how the topology of the underlying social interaction network influences the emergence and location of leaders in the adaptive system. Our model and analysis can describe other adaptive network dynamics involving collective...

  19. Dynamic Software Updating with Gosh! Current Status and the Road Ahead

    DEFF Research Database (Denmark)

    Gregersen, Allan Raundahl; Rasmussen, Michael; Jørgensen, Bo Nørregaard

    2013-01-01

    Any non-trivial software system has to be upgraded regularly to incorporate bug fixes and security patches or simply to keep up with the inevitable evolution in end-user requirements. Software upgrading is challenging, especially when it comes to online upgrading of running systems. In this paper......, we present the current status of Gosh!, a dynamic-software-updating system for Java, which provides comprehensive support for changing class definitions of live objects, including adding, removing and moving fields, methods, classes and interfaces anywhere in the inheritance hierarchy. Prior...... to the acquisition by zeroturnaround.com, Gosh! was known as Javeleon. In this paper we demonstrate the capabilities of Gosh! by performing a dynamic updating experiment on five consecutive revisions of the classical arcade game Breakout. Based on the result of this experiment we show that dynamic updating of class...

  20. Adaptive Dynamics of Regulatory Networks: Size Matters

    Directory of Open Access Journals (Sweden)

    2009-03-01

    Full Text Available To accomplish adaptability, all living organisms are constructed of regulatory networks on different levels which are capable to differentially respond to a variety of environmental inputs. Structure of regulatory networks determines their phenotypical plasticity, that is, the degree of detail and appropriateness of regulatory replies to environmental or developmental challenges. This regulatory network structure is encoded within the genotype. Our conceptual simulation study investigates how network structure constrains the evolution of networks and their adaptive abilities. The focus is on the structural parameter network size. We show that small regulatory networks adapt fast, but not as good as larger networks in the longer perspective. Selection leads to an optimal network size dependent on heterogeneity of the environment and time pressure of adaptation. Optimal mutation rates are higher for smaller networks. We put special emphasis on discussing our simulation results on the background of functional observations from experimental and evolutionary biology.

  1. Adaptive Dynamics of Regulatory Networks: Size Matters

    Directory of Open Access Journals (Sweden)

    Martinetz Thomas

    2009-01-01

    Full Text Available To accomplish adaptability, all living organisms are constructed of regulatory networks on different levels which are capable to differentially respond to a variety of environmental inputs. Structure of regulatory networks determines their phenotypical plasticity, that is, the degree of detail and appropriateness of regulatory replies to environmental or developmental challenges. This regulatory network structure is encoded within the genotype. Our conceptual simulation study investigates how network structure constrains the evolution of networks and their adaptive abilities. The focus is on the structural parameter network size. We show that small regulatory networks adapt fast, but not as good as larger networks in the longer perspective. Selection leads to an optimal network size dependent on heterogeneity of the environment and time pressure of adaptation. Optimal mutation rates are higher for smaller networks. We put special emphasis on discussing our simulation results on the background of functional observations from experimental and evolutionary biology.

  2. System Dynamics and Adaptive Control for MEMS Gyroscope Sensor

    OpenAIRE

    Juntao Fei; Hongfei Ding

    2010-01-01

    This paper presents an adaptive control approach for Micro-Electro-Mechanical Systems (MEMS) z-axis gyroscope sensor. The dynamical model of MEMS gyroscope sensor is derived and adaptive state tracking control for MEMS gyroscope is developed. The proposed adaptive control approaches can estimate the angular velocity and the damping and stiffness coefficients including the coupling terms due to the fabrication imperfection. The stability of the closed-loop systems is established with the propo...

  3. System Dynamics and Adaptive Control for MEMS Gyroscope Sensor

    OpenAIRE

    Juntao Fei; Hongfei Ding

    2011-01-01

    This paper presents an adaptive control approach for Micro-Electro-Mechanical Systems (MEMS) z-axis gyroscope sensor. The dynamical model of MEMS gyroscope sensor is derived and adaptive state tracking control for MEMS gyroscope is developed. The proposed adaptive control approaches can estimate the angular velocity and the damping and stiffness coefficients including the coupling terms due to the fabrication imperfection. The stability of the closed-loop systems is established with the propo...

  4. Truncated adaptation design for decentralised neural dynamic surface control of interconnected nonlinear systems under input saturation

    Science.gov (United States)

    Gao, Shigen; Dong, Hairong; Lyu, Shihang; Ning, Bin

    2016-07-01

    This paper studies decentralised neural adaptive control of a class of interconnected nonlinear systems, each subsystem is in the presence of input saturation and external disturbance and has independent system order. Using a novel truncated adaptation design, dynamic surface control technique and minimal-learning-parameters algorithm, the proposed method circumvents the problems of 'explosion of complexity' and 'dimension curse' that exist in the traditional backstepping design. Comparing to the methodology that neural weights are online updated in the controllers, only one scalar needs to be updated in the controllers of each subsystem when dealing with unknown systematic dynamics. Radial basis function neural networks (NNs) are used in the online approximation of unknown systematic dynamics. It is proved using Lyapunov stability theory that all the signals in the closed-loop system are semi-globally uniformly ultimately bounded. The tracking errors of each subsystems, the amplitude of NN approximation residuals and external disturbances can be attenuated to arbitrarily small by tuning proper design parameters. Simulation results are given to demonstrate the effectiveness of the proposed method.

  5. Dynamic Adaptation in Child-Adult Language Interaction

    Science.gov (United States)

    van Dijk, Marijn; van Geert, Paul; Korecky-Kröll, Katharina; Maillochon, Isabelle; Laaha, Sabine; Dressler, Wolfgang U.; Bassano, Dominique

    2013-01-01

    When speaking to young children, adults adapt their language to that of the child. In this article, we suggest that this child-directed speech (CDS) is the result of a transactional process of dynamic adaptation between the child and the adult. The study compares developmental trajectories of three children to those of the CDS of their caregivers.…

  6. Dynamic Adaptation in Child-Adult Language Interaction

    NARCIS (Netherlands)

    van Dijk, Marijn; van Geert, Paul; Korecky-Kroell, Katharina; Maillochon, Isabelle; Laaha, Sabine; Dressler, Wolfgang U.; Bassano, Dominique

    2013-01-01

    When speaking to young children, adults adapt their language to that of the child. In this article, we suggest that this child-directed speech (CDS) is the result of a transactional process of dynamic adaptation between the child and the adult. The study compares developmental trajectories of three

  7. Multiple Iteration of Weight Updates for Least Mean Square Adaptive Filter in Active Noise Control Application

    Directory of Open Access Journals (Sweden)

    Mustafa Rahimie

    2017-01-01

    Full Text Available The method of least mean square (LMS is the commonly used algorithm in Adaptive filter due to its simplicity and robustness in implementation. In Active Noise Control application, a filtered reference signal is used prior to LMS algorithm to overcome the constraint on stability and convergence performance of the system due to the existence of the auxiliary path. This is known as Filtered-X LMS algorithm. In conventional Filtered-X LMS algorithm, each filter weight is updated once on every audio sample. This paper proposes the improved version of Filtered-X LMS algorithm with the use of multiple iteration of filter weight on every sample of audio signal. The proposed work uses field programmable gate arrays to realize real-time simulation on hardware for the noise signal of 500 Hz. Results from the real-time hardware simulations have shown much faster error convergence and better adaptation performance for different selections of learning constant μ, as compared with the conventional method.

  8. Robust adaptive output stabilization using dynamic normalizing signal

    Institute of Scientific and Technical Information of China (English)

    Haixia SU; Xuejun XIE; Haikuan LIU

    2007-01-01

    For a class of nonlinear systems with dynamic uncertainties,robust adaptive stabilization problem is considered in this paper.Firstly,by introducing an observer,an augmented system is obtained.Based on the system,we construct an exp-ISpS Lyapunov function for the unmodeled dynamics,prove that the unmodeled dynamics is exp-ISpS,and then obtain a dynamic normalizing signal to counteract the dynamic disturbances.By the backstepping technique,an adaptive controller is given,it is proved that all the signals in the adaptive control system are globally uniformly ultimately bounded,and the output can be regulated to the origin with any prescribed accuracy.A simulation example further demonstrates the efficiency of the control scheme.

  9. Development of a cyber-physical experimental platform for real-time dynamic model updating

    Science.gov (United States)

    Song, Wei; Dyke, Shirley

    2013-05-01

    Model updating procedures are traditionally performed off-line. With the significant recent advances in embedded systems and the related real-time computing capabilities, online or real-time, model updating can be performed to inform decision making and controller actions. The applications for real-time model updating are mainly in the areas of (i) condition diagnosis and prognosis of engineering systems; and (ii) control systems that benefit from accurate modeling of the system plant. Herein, the development of a cyber-physical real-time model updating experimental platform, including real-time computing environment, model updating algorithm, hardware architecture and testbed, is described. Results from two challenging experimental implementations are presented to illustrate the performance of this cyber-physical platform in achieving the goal of updating nonlinear systems in real-time. The experiments consider typical nonlinear engineering systems that exhibit hysteresis. Among the available algorithms capable of identification of such complex nonlinearities, the unscented Kalman filter (UKF) is selected for these experiments as an effective method to update nonlinear dynamic system models under realistic conditions. The implementation of the platform is discussed for successful completion of these experiments, including required timing constraints and overall evaluation of the system.

  10. Neural dynamics for mobile robot adaptive control

    OpenAIRE

    Oubbati, Mohamed

    2006-01-01

    In this thesis, we investigate how dynamics in recurrent neural networks can be used to solve some specific mobile robot problems. We have designed a motion control approach based on a novel recurrent neural network. The advantage of this approach is that, no knowledge about the dynamic model is required, and no synaptic weight changing is needed in presence of time varying parameters. Furthermore, this approach allows a single fixed-weight network to act as a dynamic controller for several d...

  11. Applicability and efficiency of near-optimal spatial encoding for dynamically adaptive MRI.

    Science.gov (United States)

    Zientara, G P; Panych, L P; Jolesz, F A

    1998-02-01

    Adaptive near-optimal MRI spatial encoding entails, for the acquisition of each image update in a dynamic series, the computation of encodes in the form of a linear algebra-derived orthogonal basis set determined from an image estimate. The origins of adaptive encoding relevant to MRI are reviewed. Sources of error of this approach are identified from the linear algebraic perspective where MRI data acquisition is viewed as the projection of information from the field-of-view onto the encoding basis set. The definitions of ideal and non-ideal encoding follow, with nonideal encoding characterized by the principal angles between two vector spaces. An analysis of the distribution of principal angles is introduced and applied in several example cases to quantitatively describe the suitability of a basis set derived from a specific image estimate for the spatial encoding of a given field-of-view. The robustness of adaptive near-optimal spatial encoding for dynamic MRI is favorably shown by results computed using singular value decomposition encoding that simulates specific instances of worst case data acquisition when all objects have changed or new objects have appeared in the field-of-view. The mathematical analysis and simulations presented clarify the applicability and efficiency of adaptively determined near-optimal spatial encoding throughout a range of circumstances as may typically occur during use of dynamic MRI.

  12. Adaptive Synchronization in Small-World Dynamical Networks

    Institute of Scientific and Technical Information of China (English)

    ZOU Yan-li; ZHU Jie; LUO Xiao-shu

    2007-01-01

    Adaptive synchronization in NW small-world dynamical networks was studied. Firstly, an adaptive synchronization method is presented and explained. Then, it is applied to two different classes of dynamical networks,one is a class-B network, small-world connected R(o)ssler oscillators, the other is a class-A network, small-world connected Chua's circuits. The simulation verifies the validity of the presented method. It also shows that the adaptive synchronization method is robust to the variations of the node systems parameters. So the presented method can be used in networks whose node systems have unknown or time-varying parameters.

  13. Genetic Algorithms in Dynamical Systems Optimisation and Adaptation

    NARCIS (Netherlands)

    Reus, N.M. de; Visser, E.K.; Bruggeman, B.

    1998-01-01

    Both in the design of dynamical systems, ranging from control systems to state estimators as in the adaptation of these systems the use of genetic algorithms is worth studying. This paper presents some approaches for using genetic algorithms in dynamical systems. The layouts and specific uses are di

  14. System Dynamics and Adaptive Control for MEMS Gyroscope Sensor

    Directory of Open Access Journals (Sweden)

    Juntao Fei

    2011-01-01

    Full Text Available This paper presents an adaptive control approach for Micro-Electro-Mechanical Systems (MEMS z-axis gyroscope sensor. The dynamical model of MEMS gyroscope sensor is derived and adaptive state tracking control for MEMS gyroscope is developed. The proposed adaptive control approaches can estimate the angular velocity and the damping and stiffness coefficients including the coupling terms due to the fabrication imperfection. The stability of the closed-loop systems is established with the proposed adaptive control strategy. Numerical simulation is investigated to verify the effectiveness of the proposed control scheme.

  15. Quantitative Adaptation Analytics for Assessing Dynamic Systems of Systems.

    Energy Technology Data Exchange (ETDEWEB)

    Gauthier, John H.; Miner, Nadine E.; Wilson, Michael L.; Le, Hai D.; Kao, Gio K; Melander, Darryl J.; Longsine, Dennis Earl [Sandia National Laboratories, Unknown, Unknown; Vander Meer, Robert Charles,

    2015-01-01

    Our society is increasingly reliant on systems and interoperating collections of systems, known as systems of systems (SoS). These SoS are often subject to changing missions (e.g., nation- building, arms-control treaties), threats (e.g., asymmetric warfare, terrorism), natural environments (e.g., climate, weather, natural disasters) and budgets. How well can SoS adapt to these types of dynamic conditions? This report details the results of a three year Laboratory Directed Research and Development (LDRD) project aimed at developing metrics and methodologies for quantifying the adaptability of systems and SoS. Work products include: derivation of a set of adaptability metrics, a method for combining the metrics into a system of systems adaptability index (SoSAI) used to compare adaptability of SoS designs, development of a prototype dynamic SoS (proto-dSoS) simulation environment which provides the ability to investigate the validity of the adaptability metric set, and two test cases that evaluate the usefulness of a subset of the adaptability metrics and SoSAI for distinguishing good from poor adaptability in a SoS. Intellectual property results include three patents pending: A Method For Quantifying Relative System Adaptability, Method for Evaluating System Performance, and A Method for Determining Systems Re-Tasking.

  16. Adaptation and inertia in dynamic environments

    DEFF Research Database (Denmark)

    Stieglitz, Nils; Knudsen, Thorbjørn; Becker, Markus C.

    2016-01-01

    , in dynamic environments, the best-performing organizations are generally more inert than less successful organizations. Managerial summary: Our research helps managers to understand under what business conditions investments into exploration and strategic flexibility are more likely to pay off. Dynamic...... business environments characterized by persistent trends and by large, infrequently occurring structural shocks reward strategic pursuit of temporary advantage. Thus, exploration and strategic flexibility are preferred strategies. In contrast, the challenge in frequently changing environments with fleeting...

  17. Adaptive finite difference methods in fluid dynamics

    Science.gov (United States)

    Berger, Marsha J.

    1987-01-01

    An adaptive method to solve partial differential equations in fluid mechanics is presented. The approach requires internal boundary conditions that must be conservative, data structures for keeping track of several layers of fine grid patches, error estimation, and heuristics for automatic grid generation. In practical calculations gains in computer efficiency up to 10 over nonadaptive methods are observed. The whole procedure takes 3000 lines of FORTRAN code.

  18. An Integrated Platform for Dynamic Software Updating and its Application in Self-* systems

    DEFF Research Database (Denmark)

    Gregersen, Allan Raundahl; Jørgensen, Bo Nørregaard; Hadaytullah

    2012-01-01

    frameworks, component systems and application servers, Javeleon currently provides tight integration with the NetBeans Platform, facilitating dynamic updating for applications built on top of the NetBeans Platform in an unconstrained manner. Javeleon supports state-preserving unanticipated runtime evolution...

  19. Using Microsoft Dynamics AX 2012 updated for version R2

    CERN Document Server

    Luszczak, Andreas

    2013-01-01

    Precise descriptions and instructions enable users, students and consultants to easily understand Microsoft Dynamics AX 2012. Microsoft offers Dynamics AX as its premium ERP solution to support large and mid-sized organizations with a complete business management solution which is easy to use. Going through a simple but comprehensive case study - the sample company 'Anso Technologies Inc.' - this book provides the required knowledge to handle all basic business processes in Dynamics AX. Exercises are there to train the processes and functionality, also making this book a good choice for self-s

  20. Using Microsoft Dynamics AX 2012 updated for version R3

    CERN Document Server

    Luszczak, Andreas

    2015-01-01

    Precise descriptions and instructions enable users, students and consultants to understand MS Dynamics AX 2012 rapidly. Microsoft offers Dynamics AX as its premium ERP solution, supporting large and mid-sized organizations with a complete business management solution which is easy to use. Going through a simple but comprehensive case study - the sample company 'Anso Technologies Inc.' - this book provides the required knowledge to handle all basic business processes in Dynamics AX. Exercises are there to train the processes and functionality, also making this book a good choice for self-study.

  1. Analog forecasting with dynamics-adapted kernels

    Science.gov (United States)

    Zhao, Zhizhen; Giannakis, Dimitrios

    2016-09-01

    Analog forecasting is a nonparametric technique introduced by Lorenz in 1969 which predicts the evolution of states of a dynamical system (or observables defined on the states) by following the evolution of the sample in a historical record of observations which most closely resembles the current initial data. Here, we introduce a suite of forecasting methods which improve traditional analog forecasting by combining ideas from kernel methods developed in harmonic analysis and machine learning and state-space reconstruction for dynamical systems. A key ingredient of our approach is to replace single-analog forecasting with weighted ensembles of analogs constructed using local similarity kernels. The kernels used here employ a number of dynamics-dependent features designed to improve forecast skill, including Takens’ delay-coordinate maps (to recover information in the initial data lost through partial observations) and a directional dependence on the dynamical vector field generating the data. Mathematically, our approach is closely related to kernel methods for out-of-sample extension of functions, and we discuss alternative strategies based on the Nyström method and the multiscale Laplacian pyramids technique. We illustrate these techniques in applications to forecasting in a low-order deterministic model for atmospheric dynamics with chaotic metastability, and interannual-scale forecasting in the North Pacific sector of a comprehensive climate model. We find that forecasts based on kernel-weighted ensembles have significantly higher skill than the conventional approach following a single analog.

  2. Nonlinear adaptive synchronization rule for identification of a large amount of parameters in dynamical models

    Energy Technology Data Exchange (ETDEWEB)

    Ma Huanfei [Center for Computational Systems Biology, Fudan University, Shanghai 200433 (China)] [School of Computer Science, Fudan University, Shanghai 200433 (China); Lin Wei, E-mail: wlin@fudan.edu.c [Center for Computational Systems Biology, Fudan University, Shanghai 200433 (China)] [School of Mathematical Sciences, Fudan University, Shanghai 200433 (China)] [Key Laboratory of Mathematics for Nonlinear Sciences (Fudan University), Ministry of Education (China)] [CAS-MPG Partner Institute for Computational Biology, Chinese Academy of Sciences, Shanghai 200031 (China)

    2009-12-28

    The existing adaptive synchronization technique based on the stability theory and invariance principle of dynamical systems, though theoretically proved to be valid for parameters identification in specific models, is always showing slow convergence rate and even failed in practice when the number of parameters becomes large. Here, for parameters update, a novel nonlinear adaptive rule is proposed to accelerate the rate. Its feasibility is validated by analytical arguments as well as by specific parameters identification in the Lotka-Volterra model with multiple species. Two adjustable factors in this rule influence the identification accuracy, which means that a proper choice of these factors leads to an optimal performance of this rule. In addition, a feasible method for avoiding the occurrence of the approximate linear dependence among terms with parameters on the synchronized manifold is also proposed.

  3. Analog Forecasting with Dynamics-Adapted Kernels

    CERN Document Server

    Zhao, Zhizhen

    2014-01-01

    Analog forecasting is a non-parametric technique introduced by Lorenz in 1969 which predicts the evolution of states of a dynamical system (or observables defined on the states) by following the evolution of the sample in a historical record of observations which most closely resembles the current initial data. Here, we introduce a suite of forecasting methods which improve traditional analog forecasting by combining ideas from state-space reconstruction for dynamical systems and kernel methods developed in harmonic analysis and machine learning. The first improvement is to augment the dimension of the initial data using Takens' delay-coordinate maps to recover information in the initial data lost through partial observations. Then, instead of using Euclidean distances between the states, weighted ensembles of analogs are constructed according to similarity kernels in delay-coordinate space, featuring an explicit dependence on the dynamical vector field generating the data. The eigenvalues and eigenfunctions ...

  4. Dynamic grid adaptation for computational magnetohydrodynamics

    NARCIS (Netherlands)

    Keppens, R.; Nool, M.; Zegeling, P. A.; Goedbloed, J. P.; Bubak, M.; Williams, R.; Afsarmanesh, H.; Hertzberger, B.

    2000-01-01

    In many plasma physical and astrophysical problems, both linear and nonlinear effects can lead to global dynamics that induce, or occur simultaneously with, local phenomena. For example, a magnetically confined plasma column can potentially posses global magnetohydrodynamic (MHD) eigenmodes with an

  5. Adaptive Strategies for Dynamic Pricing Agents

    NARCIS (Netherlands)

    S. Ramezani (Sara); P.A.N. Bosman (Peter); J.A. La Poutré (Han)

    2011-01-01

    htmlabstractDynamic Pricing (DyP) is a form of Revenue Management in which the price of a (usually) perishable good is changed over time to increase revenue. It is an effective method that has become even more relevant and useful with the emergence of Internet firms and the possibility of readily

  6. On Sustaining Dynamic Adaptation of Context-Aware Services

    Directory of Open Access Journals (Sweden)

    Boudjemaa Boudaa

    2015-03-01

    Full Text Available The modern human is getting more and more mobile having access to online services by using mobile cutting-edge computational devices. In the last decade, the field of context-aware services had led to emerge several works. However, most of the proposed approaches have not provided clear adaptation strategies in case of unforeseen contexts. Dealing with this last at runtime is also another crucial need that has been ignored in their proposals. This paper aims to propose a generic dynamic adaptation process as a phase in a model-driven development life-cycle for context-aware services using the MAPE-K control loop to meet the runtime adaptation. This process is validated by implementing an illustrative application on FraSCAti platform. The main benefit of the proposed process is to sustain the self-reconfiguration of such services at model and code levels by enabling successive dynamic adaptations depending on the changing context.

  7. Brain-wide neuronal dynamics during motor adaptation in zebrafish.

    Science.gov (United States)

    Ahrens, Misha B; Li, Jennifer M; Orger, Michael B; Robson, Drew N; Schier, Alexander F; Engert, Florian; Portugues, Ruben

    2012-05-09

    A fundamental question in neuroscience is how entire neural circuits generate behaviour and adapt it to changes in sensory feedback. Here we use two-photon calcium imaging to record the activity of large populations of neurons at the cellular level, throughout the brain of larval zebrafish expressing a genetically encoded calcium sensor, while the paralysed animals interact fictively with a virtual environment and rapidly adapt their motor output to changes in visual feedback. We decompose the network dynamics involved in adaptive locomotion into four types of neuronal response properties, and provide anatomical maps of the corresponding sites. A subset of these signals occurred during behavioural adjustments and are candidates for the functional elements that drive motor learning. Lesions to the inferior olive indicate a specific functional role for olivocerebellar circuitry in adaptive locomotion. This study enables the analysis of brain-wide dynamics at single-cell resolution during behaviour.

  8. Adaptive Fuzzy Dynamic Surface Control for Uncertain Nonlinear Systems

    Institute of Scientific and Technical Information of China (English)

    Xiao-Yuan Luo; Zhi-Hao Zhu; Xin-Ping Guan

    2009-01-01

    In this paper, a robust adaptive fuzzy dynamic surface control for a class of uncertain nonlinear systems is proposed. A novel adaptive fuzzy dynamic surface model is built to approximate the uncertain nonlinear functions by only one fuzzy logic system. The approximation capability of this model is proved and the model is implemented to solve the problem that too many approximators are used in the controller design of uncertain nonlinear systems. The shortage of "explosion of complexity" in backstepping design procedure is overcome by using the proposed dynamic surface control method. It is proved by constructing appropriate Lyapunov candidates that all signals of closed-loop systems are semi-globaily uniformly ultimate bounded. Also, this novel controller stabilizes the states of uncertain nonlinear systems faster than the adaptive sliding mode controller (SMC). Two simulation examples are provided to illustrate the effectiveness of the control approach proposed in this paper.

  9. A Dynamic Adaptive Layered Multicast Congestion Control Mechanism

    Institute of Scientific and Technical Information of China (English)

    REN Liyong; LU Xianliang; WEI Qingsong; ZHOU Xu

    2003-01-01

    To solve the problem that most of existing layered multicast protocols cannot adapt to dynamic network conditions because their layers are coarsely granulated and static, a new congestion control mechanism for dynamic adaptive layered multicast(DALM) is presented. In this mechanism, a novel feedback aggregating algorithm is put forward, which can dynamically determine the number of layers and the rate of each layer, and can efficiently improve network bandwidth utilization ratio.Additionally, because all layers is transmitted in only one group, the intricate and time-consuming internet group management protocol(IGMP) operations, caused by receiver joining a new layer or leaving the topmost subscribed layer, are thoroughly eliminated. And this mechanism also avoids other problems resulted from multiple groups. Simulation results show that DALM is adaptive and TCP friendly.

  10. Dynamic causal modelling of electrographic seizure activity using Bayesian belief updating.

    Science.gov (United States)

    Cooray, Gerald K; Sengupta, Biswa; Douglas, Pamela K; Friston, Karl

    2016-01-15

    Seizure activity in EEG recordings can persist for hours with seizure dynamics changing rapidly over time and space. To characterise the spatiotemporal evolution of seizure activity, large data sets often need to be analysed. Dynamic causal modelling (DCM) can be used to estimate the synaptic drivers of cortical dynamics during a seizure; however, the requisite (Bayesian) inversion procedure is computationally expensive. In this note, we describe a straightforward procedure, within the DCM framework, that provides efficient inversion of seizure activity measured with non-invasive and invasive physiological recordings; namely, EEG/ECoG. We describe the theoretical background behind a Bayesian belief updating scheme for DCM. The scheme is tested on simulated and empirical seizure activity (recorded both invasively and non-invasively) and compared with standard Bayesian inversion. We show that the Bayesian belief updating scheme provides similar estimates of time-varying synaptic parameters, compared to standard schemes, indicating no significant qualitative change in accuracy. The difference in variance explained was small (less than 5%). The updating method was substantially more efficient, taking approximately 5-10min compared to approximately 1-2h. Moreover, the setup of the model under the updating scheme allows for a clear specification of how neuronal variables fluctuate over separable timescales. This method now allows us to investigate the effect of fast (neuronal) activity on slow fluctuations in (synaptic) parameters, paving a way forward to understand how seizure activity is generated.

  11. Adaptive feedback synchronisation of complex dynamical network with discrete-time communications and delayed nodes

    Science.gov (United States)

    Wang, Tong; Ding, Yongsheng; Zhang, Lei; Hao, Kuangrong

    2016-08-01

    This paper considered the synchronisation of continuous complex dynamical networks with discrete-time communications and delayed nodes. The nodes in the dynamical networks act in the continuous manner, while the communications between nodes are discrete-time; that is, they communicate with others only at discrete time instants. The communication intervals in communication period can be uncertain and variable. By using a piecewise Lyapunov-Krasovskii function to govern the characteristics of the discrete communication instants, we investigate the adaptive feedback synchronisation and a criterion is derived to guarantee the existence of the desired controllers. The globally exponential synchronisation can be achieved by the controllers under the updating laws. Finally, two numerical examples including globally coupled network and nearest-neighbour coupled networks are presented to demonstrate the validity and effectiveness of the proposed control scheme.

  12. PRINCIPAL COMPONENT DECOMPOSITION BASED FINITE ELEMENT MODEL UPDATING FOR STRAIN-RATE-DEPENDENCE NONLINEAR DYNAMIC PROBLEMS

    Institute of Scientific and Technical Information of China (English)

    GUO Qintao; ZHANG Lingmi; TAO Zheng

    2008-01-01

    Thin wall component is utilized to absorb impact energy of a structure. However, the dynamic behavior of such thin-walled structure is highly non-linear with material, geometry and boundary non-linearity. A model updating and validation procedure is proposed to build accurate finite element model of a frame structure with a non-linear thin-walled component for dynamic analysis. Design of experiments (DOE) and principal component decomposition (PCD) approach are applied to extract dynamic feature from nonlinear impact response for correlation of impact test result and FE model of the non-linear structure. A strain-rate-dependent non-linear model updating method is then developed to build accurate FE model of the structure. Computer simulation and a real frame structure with a highly non-linear thin-walled component are employed to demonstrate the feasibility and effectiveness of the proposed approach.

  13. A dynamical theory of speciation on holey adaptive landscapes

    CERN Document Server

    Gavrilets, S

    1998-01-01

    The metaphor of holey adaptive landscapes provides a pictorial representation of the process of speciation as a consequence of genetic divergence. In this metaphor, biological populations diverge along connected clusters of well-fit genotypes in a multidimensional adaptive landscape and become reproductively isolated species when they come to be on opposite sides of a ``hole'' in the adaptive landscape. No crossing of any adaptive valleys is required. I formulate and study a series of simple models describing the dynamics of speciation on holey adaptive landscapes driven by mutation and random genetic drift. Unlike most previous models that concentrate only on some stages of speciation, the models studied here describe the complete process of speciation from initiation until completion. The evolutionary factors included are selection (reproductive isolation), random genetic drift, mutation, recombination, and migration. In these models, pre- and post-mating reproductive isolation is a consequence of cumulativ...

  14. Efficient compensation handling via subjective updates

    NARCIS (Netherlands)

    J. Dedeić (Jovana); J. Pantović (Jovanka); J.A. Pérez Parra (Jorge)

    2017-01-01

    textabstractProgramming abstractions for compensation handling and dynamic update are crucial in specifying reliable interacting systems, such as Collective Adaptive Systems (CAS). Compensations and updates both specify how a system reacts in response to exceptional events. Prior work showed that

  15. Robust adaptive dynamic programming and feedback stabilization of nonlinear systems.

    Science.gov (United States)

    Jiang, Yu; Jiang, Zhong-Ping

    2014-05-01

    This paper studies the robust optimal control design for a class of uncertain nonlinear systems from a perspective of robust adaptive dynamic programming (RADP). The objective is to fill up a gap in the past literature of adaptive dynamic programming (ADP) where dynamic uncertainties or unmodeled dynamics are not addressed. A key strategy is to integrate tools from modern nonlinear control theory, such as the robust redesign and the backstepping techniques as well as the nonlinear small-gain theorem, with the theory of ADP. The proposed RADP methodology can be viewed as an extension of ADP to uncertain nonlinear systems. Practical learning algorithms are developed in this paper, and have been applied to the controller design problems for a jet engine and a one-machine power system.

  16. Adaptive control of ROVs with actuator dynamics and saturation

    Directory of Open Access Journals (Sweden)

    Ola-Erik Fjellstad

    1992-07-01

    Full Text Available A direct model reference adaptive controller (MRAC is derived for an underwater vehicle with significant thruster dynamics and limited thruster power. The reference model decomposition (RMD technique is used to compensate for the thruster dynamics. A reference model adjustment (RMA technique modifying the reference model acceleration is used to avoid thruster saturation. The design methods are simulated for the yawing motion of an underwater vehicle.

  17. Adaptive explicit Magnus numerical method for nonlinear dynamical systems

    Institute of Scientific and Technical Information of China (English)

    LI Wen-cheng; DENG Zi-chen

    2008-01-01

    Based on the new explicit Magnus expansion developed for nonlinear equations defined on a matrix Lie group,an efficient numerical method is proposed for nonlinear dynamical systems.To improve computational efficiency,the integration step size can be adaptively controlled.Validity and effectiveness of the method are shown by application to several nonlinear dynamical systems including the Duffing system,the van der Pol system with strong stiffness,and the nonlinear Hamiltonian pendulum system.

  18. Dynamic multimedia stream adaptation and rate control for heterogeneous networks

    Institute of Scientific and Technical Information of China (English)

    SZWABE Andrzej; SCHORR Andreas; HAUCK Franz J.; KASSLER Andreas J.

    2006-01-01

    Dynamic adaptation of multimedia content is seen as an important feature of next generation networks and pervasive systems enabling terminals and applications to adapt to changes in e.g. context, access network, and available Quality-of-Service(QoS) due to mobility of users, devices or sessions. We present the architecture of a multimedia stream adaptation service which enables communication between terminals having heterogeneous hardware and software capabilities and served by heterogeneous networks. The service runs on special content adaptation nodes which can be placed at any location within the network. The flexible structure of our architecture allows using a variety of different adaptation engines. A generic transcoding engine is used to change the codec of streams. An MPEG-21 Digital Item Adaptation (DIA) based transformation engine allows adjusting the data rate of scalable media streams. An intelligent decision-taking engine implements adaptive flow control which takes into account current network QoS parameters and congestion information. Measurements demonstrate the quality gains achieved through adaptive congestion control mechanisms under conditions typical for a heterogeneous network.

  19. Dynamics and Adaptive Control for Stability Recovery of Damaged Aircraft

    Science.gov (United States)

    Nguyen, Nhan; Krishnakumar, Kalmanje; Kaneshige, John; Nespeca, Pascal

    2006-01-01

    This paper presents a recent study of a damaged generic transport model as part of a NASA research project to investigate adaptive control methods for stability recovery of damaged aircraft operating in off-nominal flight conditions under damage and or failures. Aerodynamic modeling of damage effects is performed using an aerodynamic code to assess changes in the stability and control derivatives of a generic transport aircraft. Certain types of damage such as damage to one of the wings or horizontal stabilizers can cause the aircraft to become asymmetric, thus resulting in a coupling between the longitudinal and lateral motions. Flight dynamics for a general asymmetric aircraft is derived to account for changes in the center of gravity that can compromise the stability of the damaged aircraft. An iterative trim analysis for the translational motion is developed to refine the trim procedure by accounting for the effects of the control surface deflection. A hybrid direct-indirect neural network, adaptive flight control is proposed as an adaptive law for stabilizing the rotational motion of the damaged aircraft. The indirect adaptation is designed to estimate the plant dynamics of the damaged aircraft in conjunction with the direct adaptation that computes the control augmentation. Two approaches are presented 1) an adaptive law derived from the Lyapunov stability theory to ensure that the signals are bounded, and 2) a recursive least-square method for parameter identification. A hardware-in-the-loop simulation is conducted and demonstrates the effectiveness of the direct neural network adaptive flight control in the stability recovery of the damaged aircraft. A preliminary simulation of the hybrid adaptive flight control has been performed and initial data have shown the effectiveness of the proposed hybrid approach. Future work will include further investigations and high-fidelity simulations of the proposed hybrid adaptive Bight control approach.

  20. A pose-based structural dynamic model updating method for serial modular robots

    Science.gov (United States)

    Mohamed, Richard Phillip; Xi, Fengfeng (Jeff); Chen, Tianyan

    2017-02-01

    A new approach is presented for updating the structural dynamic component models of serial modular robots using experimental data from component tests such that the updated model of the entire robot assembly can provide accurate results in any pose. To accomplish this, a test-analysis component mode synthesis (CMS) model with fixed-free component boundaries is implemented to directly compare measured frequency response functions (FRFs) from vibration experiments of individual modules. The experimental boundary conditions are made to emulate module connection interfaces and can enable individual joint and link modules to be tested in arbitrary poses. By doing so, changes in the joint dynamics can be observed and more FRF data points can be obtained from experiments to be used in the updating process. Because this process yields an overdetermined system of equations, a direct search method with nonlinear constraints on the resonances and antiresonances is used to update the FRFs of the analytical component models. The effectiveness of the method is demonstrated with experimental case studies on an adjustable modular linkage system. Overall, the method can enable virtual testing of modular robot systems without the need to perform further testing on entire assemblies.

  1. Robust adaptive control of nonlinearly parameterized systems with unmodeled dynamics

    Institute of Scientific and Technical Information of China (English)

    LIU Yu-sheng; CHEN Jiang; LI Xing-yuan

    2006-01-01

    Many physical systems such as biochemical processes and machines with friction are of nonlinearly parameterized systems with uncertainties.How to control such systems effectively is one of the most challenging problems.This paper presents a robust adaptive controller for a significant class of nonlinearly parameterized systems.The controller can be used in cases where there exist parameter and nonlinear uncertainties,unmodeled dynamics and unknown bounded disturbances.The design of the controller is based on the control Lyapunov function method.A dynamic signal is introduced and adaptive nonlinear damping terms are used to restrain the effects of unmodeled dynamics,nonlinear uncertainties and unknown bounded disturbances.The backstepping procedure is employed to overcome the complexity in the design.With the proposed method,the estimation of the unknown parameters of the system is not required and there is only one adaptive parameter no matter how high the order of the system is and how many unknown parameters.there are.It is proved theoretically that the proposed robust adaptive control scheme guarantees the stability of nonlinearly parameterized system.Furthermore,all the states approach the equilibrium in arbitrary precision by choosing some design constants appropriately.Simulation results illustrate the effectiveness of the proposed robust adaptive controller.

  2. Sex speeds adaptation by altering the dynamics of molecular evolution.

    Science.gov (United States)

    McDonald, Michael J; Rice, Daniel P; Desai, Michael M

    2016-03-10

    Sex and recombination are pervasive throughout nature despite their substantial costs. Understanding the evolutionary forces that maintain these phenomena is a central challenge in biology. One longstanding hypothesis argues that sex is beneficial because recombination speeds adaptation. Theory has proposed several distinct population genetic mechanisms that could underlie this advantage. For example, sex can promote the fixation of beneficial mutations either by alleviating interference competition (the Fisher-Muller effect) or by separating them from deleterious load (the ruby in the rubbish effect). Previous experiments confirm that sex can increase the rate of adaptation, but these studies did not observe the evolutionary dynamics that drive this effect at the genomic level. Here we present the first, to our knowledge, comparison between the sequence-level dynamics of adaptation in experimental sexual and asexual Saccharomyces cerevisiae populations, which allows us to identify the specific mechanisms by which sex speeds adaptation. We find that sex alters the molecular signatures of evolution by changing the spectrum of mutations that fix, and confirm theoretical predictions that it does so by alleviating clonal interference. We also show that substantially deleterious mutations hitchhike to fixation in adapting asexual populations. In contrast, recombination prevents such mutations from fixing. Our results demonstrate that sex both speeds adaptation and alters its molecular signature by allowing natural selection to more efficiently sort beneficial from deleterious mutations.

  3. Plant toxicity, adaptive herbivory, and plant community dynamics

    Science.gov (United States)

    Zhilan Feng; Rongsong Liu; Donald L. DeAngelis; John P. Bryant; Knut Kielland; F. Stuart Chapin; Robert K. Swihart

    2009-01-01

    We model effects of interspecific plant competition, herbivory, and a plant's toxic defenses against herbivores on vegetation dynamics. The model predicts that, when a generalist herbivore feeds in the absence of plant toxins, adaptive foraging generally increases the probability of coexistence of plant species populations, because the herbivore switches more of...

  4. Global Network Reorganization During Dynamic Adaptations of Bacillus subtilis Metabolism

    NARCIS (Netherlands)

    Buescher, Joerg Martin; Liebermeister, Wolfram; Jules, Matthieu; Uhr, Markus; Muntel, Jan; Botella, Eric; Hessling, Bernd; Kleijn, Roelco Jacobus; Le Chat, Ludovic; Lecointe, Francois; Maeder, Ulrike; Nicolas, Pierre; Piersma, Sjouke; Ruegheimer, Frank; Becher, Doerte; Bessieres, Philippe; Bidnenko, Elena; Denham, Emma L.; Dervyn, Etienne; Devine, Kevin M.; Doherty, Geoff; Drulhe, Samuel; Felicori, Liza; Fogg, Mark J.; Goelzer, Anne; Hansen, Annette; Harwood, Colin R.; Hecker, Michael; Hubner, Sebastian; Hultschig, Claus; Jarmer, Hanne; Klipp, Edda; Leduc, Aurelie; Lewis, Peter; Molina, Frank; Noirot, Philippe; Peres, Sabine; Pigeonneau, Nathalie; Pohl, Susanne; Rasmussen, Simon; Rinn, Bernd; Schaffer, Marc; Schnidder, Julian; Schwikowski, Benno; Van Dijl, Jan Maarten; Veiga, Patrick; Walsh, Sean; Wilkinson, Anthony J.; Stelling, Joerg; Aymerich, Stephane; Sauer, Uwe

    2012-01-01

    Adaptation of cells to environmental changes requires dynamic interactions between metabolic and regulatory networks, but studies typically address only one or a few layers of regulation. For nutritional shifts between two preferred carbon sources of Bacillus subtilis, we combined statistical and

  5. Global Network Reorganization During Dynamic Adaptations of Bacillus subtilis Metabolism

    NARCIS (Netherlands)

    Buescher, Joerg Martin; Liebermeister, Wolfram; Jules, Matthieu; Uhr, Markus; Muntel, Jan; Botella, Eric; Hessling, Bernd; Kleijn, Roelco Jacobus; Le Chat, Ludovic; Lecointe, Francois; Maeder, Ulrike; Nicolas, Pierre; Piersma, Sjouke; Ruegheimer, Frank; Becher, Doerte; Bessieres, Philippe; Bidnenko, Elena; Denham, Emma L.; Dervyn, Etienne; Devine, Kevin M.; Doherty, Geoff; Drulhe, Samuel; Felicori, Liza; Fogg, Mark J.; Goelzer, Anne; Hansen, Annette; Harwood, Colin R.; Hecker, Michael; Hubner, Sebastian; Hultschig, Claus; Jarmer, Hanne; Klipp, Edda; Leduc, Aurelie; Lewis, Peter; Molina, Frank; Noirot, Philippe; Peres, Sabine; Pigeonneau, Nathalie; Pohl, Susanne; Rasmussen, Simon; Rinn, Bernd; Schaffer, Marc; Schnidder, Julian; Schwikowski, Benno; Van Dijl, Jan Maarten; Veiga, Patrick; Walsh, Sean; Wilkinson, Anthony J.; Stelling, Joerg; Aymerich, Stephane; Sauer, Uwe

    2012-01-01

    Adaptation of cells to environmental changes requires dynamic interactions between metabolic and regulatory networks, but studies typically address only one or a few layers of regulation. For nutritional shifts between two preferred carbon sources of Bacillus subtilis, we combined statistical and mo

  6. Dynamic Adaptive Neural Network Arrays: A Neuromorphic Architecture

    Energy Technology Data Exchange (ETDEWEB)

    Disney, Adam [University of Tennessee (UT); Reynolds, John [University of Tennessee (UT)

    2015-01-01

    Dynamic Adaptive Neural Network Array (DANNA) is a neuromorphic hardware implementation. It differs from most other neuromorphic projects in that it allows for programmability of structure, and it is trained or designed using evolutionary optimization. This paper describes the DANNA structure, how DANNA is trained using evolutionary optimization, and an application of DANNA to a very simple classification task.

  7. Adaptive Delta-Sigma Modulation for Enhanced Input Dynamic Range

    Directory of Open Access Journals (Sweden)

    Clemens M. Zierhofer

    2008-06-01

    Full Text Available An adaptive delta-sigma modulator of 1st order with one-bit quantization is presented. Adaptation is instantaneous and based on an exponential law. The feedback signal is a multibit discrete-level signal generated by a digital-to-analog converter (DAC. Compared to a nonadaptive delta-sigma modulator of 1st order, the input dynamic range is significantly enhanced. The gain in dynamic range is 6 dB per bit defining the feedback amplitude. The influence of nonideal DAC performance is discussed. It is demonstrated that an implementation of the system is realistic with standard CMOS technology. To relax the requirements to the one-bit quantizer, the quantizer input signal is amplified adaptively (Q-Switching.

  8. Adaptive Delta-Sigma Modulation for Enhanced Input Dynamic Range

    Science.gov (United States)

    Zierhofer, Clemens M.

    2006-12-01

    An adaptive delta-sigma modulator of 1st order with one-bit quantization is presented. Adaptation is instantaneous and based on an exponential law. The feedback signal is a multibit discrete-level signal generated by a digital-to-analog converter (DAC). Compared to a nonadaptive delta-sigma modulator of 1st order, the input dynamic range is significantly enhanced. The gain in dynamic range is 6 dB per bit defining the feedback amplitude. The influence of nonideal DAC performance is discussed. It is demonstrated that an implementation of the system is realistic with standard CMOS technology. To relax the requirements to the one-bit quantizer, the quantizer input signal is amplified adaptively (Q-Switching).

  9. Epidemic Dynamics On Information-Driven Adaptive Networks

    CERN Document Server

    Zhan, Xiu-Xiu; Sun, Gui-Quan; Zhang, Zi-Ke

    2015-01-01

    can evolve simultaneously. For the information-driven adaptive process, susceptible (infected) individuals who have abilities to recognize the disease would break the links of their infected (susceptible) neighbors to prevent the epidemic from further spreading. Simulation results and numerical analyses based on the pairwise approach indicate that the information-driven adaptive process can not only slow down the speed of epidemic spreading, but can also diminish the epidemic prevalence at the final state significantly. In addition, the disease spreading and information diffusion pattern on the lattice give a visual representation about how the disease is trapped into an isolated field with the information-driven adaptive process. Furthermore, we perform the local bifurcation analysis on four types of dynamical regions, including healthy, oscillatory, bistable and endemic, to understand the evolution of the observed dynamical behaviors. This work may shed some lights on understanding how information affects h...

  10. Adapting Dynamic Mathematical Models to a Pilot Anaerobic Digestion Reactor

    Directory of Open Access Journals (Sweden)

    F. Haugen, R. Bakke, and B. Lie

    2013-04-01

    Full Text Available A dynamic model has been adapted to a pilot anaerobic reactor fed diarymanure. Both steady-state data from online sensors and laboratory analysis anddynamic operational data from online sensors are used in the model adaptation.The model is based on material balances, and comprises four state variables,namely biodegradable volatile solids, volatile fatty acids, acid generatingmicrobes (acidogens, and methane generating microbes (methanogens. The modelcan predict the methane gas flow produced in the reactor. The model may beused for optimal reactor design and operation, state-estimation and control.Also, a dynamic model for the reactor temperature based on energy balance ofthe liquid in the reactor is adapted. This model may be used for optimizationand control when energy and economy are taken into account.

  11. Dynamic learning and memory, synaptic plasticity and neurogenesis: An update

    Directory of Open Access Journals (Sweden)

    Ales eStuchlik

    2014-04-01

    Full Text Available Mammalian memory is the result of the interaction of millions of neurons in the brain and their coordinated activity. Candidate mechanisms for memory are synaptic plasticity changes, such as long-term potentiation (LTP. LTP is essentially an electrophysiological phenomenon manifested in hours-lasting increase on postsynaptic potentials after synapse tetanization. It is thought to ensure long-term changes in synaptic efficacy in distributed networks, leading to persistent changes in the behavioral patterns, actions and choices, which are often interpreted as the retention of information, i.e., memory. Interestingly, new neurons are born in the mammalian brain and adult hippocampal neurogenesis is proposed to provide a substrate for dynamic and flexible aspects of behavior such as pattern separation, prevention of interference, flexibility of behavior and memory resolution. This work provides a brief review on the memory and involvement of LTP and adult neurogenesis in memory phenomena.

  12. Adaptive steady-state stabilization for nonlinear dynamical systems

    Science.gov (United States)

    Braun, David J.

    2008-07-01

    By means of LaSalle’s invariance principle, we propose an adaptive controller with the aim of stabilizing an unstable steady state for a wide class of nonlinear dynamical systems. The control technique does not require analytical knowledge of the system dynamics and operates without any explicit knowledge of the desired steady-state position. The control input is achieved using only system states with no computer analysis of the dynamics. The proposed strategy is tested on Lorentz, van der Pol, and pendulum equations.

  13. Gradient-based adaptation of continuous dynamic model structures

    Science.gov (United States)

    La Cava, William G.; Danai, Kourosh

    2016-01-01

    A gradient-based method of symbolic adaptation is introduced for a class of continuous dynamic models. The proposed model structure adaptation method starts with the first-principles model of the system and adapts its structure after adjusting its individual components in symbolic form. A key contribution of this work is its introduction of the model's parameter sensitivity as the measure of symbolic changes to the model. This measure, which is essential to defining the structural sensitivity of the model, not only accommodates algebraic evaluation of candidate models in lieu of more computationally expensive simulation-based evaluation, but also makes possible the implementation of gradient-based optimisation in symbolic adaptation. The proposed method is applied to models of several virtual and real-world systems that demonstrate its potential utility.

  14. Dual adaptive dynamic control of mobile robots using neural networks.

    Science.gov (United States)

    Bugeja, Marvin K; Fabri, Simon G; Camilleri, Liberato

    2009-02-01

    This paper proposes two novel dual adaptive neural control schemes for the dynamic control of nonholonomic mobile robots. The two schemes are developed in discrete time, and the robot's nonlinear dynamic functions are assumed to be unknown. Gaussian radial basis function and sigmoidal multilayer perceptron neural networks are used for function approximation. In each scheme, the unknown network parameters are estimated stochastically in real time, and no preliminary offline neural network training is used. In contrast to other adaptive techniques hitherto proposed in the literature on mobile robots, the dual control laws presented in this paper do not rely on the heuristic certainty equivalence property but account for the uncertainty in the estimates. This results in a major improvement in tracking performance, despite the plant uncertainty and unmodeled dynamics. Monte Carlo simulation and statistical hypothesis testing are used to illustrate the effectiveness of the two proposed stochastic controllers as applied to the trajectory-tracking problem of a differentially driven wheeled mobile robot.

  15. Decentralized adaptive synchronization of an uncertain complex delayed dynamical network

    Institute of Scientific and Technical Information of China (English)

    Weisong ZHONG; Jun ZHAO; Georgi M.DIMIROVSKI

    2009-01-01

    In this paper,we investigate the locally and globally adaptive synchronization problem for an uncertain complex dynamical network with time-varying coupling delays based on the decentralized control.The coupling terms here are bounded by high-order polynomials with known gains that are ubiquitous in a large class of complex dynamical networks.We generalize the usual technology of searching for an appropriate coordinates transformation to change the network dynamics into a series of decoupled lower-dimensional systems.Several adaptive synchronization criteria are derived by constructing the Lyapunov-Krasovskii functional and Barbalat lemma,and the proposed criteria are simple in form and convenient for the practical engineering design.Numerical simulations illustrated by a nearest-neighbor coupling network verify the effectiveness of the proposed synchronization scheme.

  16. A framework to update Hofstede's cultural value indices: economic dynamics and institutional stability

    OpenAIRE

    Linghui Tang; Peter E Koveos

    2008-01-01

    This study offers an update of the Hofstede cultural value dimensions. We argue that changes in economic conditions are the source of cultural dynamics, while the endurance of institutional characteristics provides the foundation for cultural stability. It is found that national wealth, measured by GDP per capita, has a curvilinear relationship with individualism, long-term orientation, and power distance scores. Relatively speaking, uncertainty avoidance and masculinity mainly reflect some r...

  17. Vehicle Sliding Mode Control with Adaptive Upper Bounds: Static versus Dynamic Allocation to Saturated Tire Forces

    Directory of Open Access Journals (Sweden)

    Ali Tavasoli

    2012-01-01

    Full Text Available Nonlinear vehicle control allocation is achieved through distributing the task of vehicle control among individual tire forces, which are constrained to nonlinear saturation conditions. A high-level sliding mode control with adaptive upper bounds is considered to assess the body yaw moment and lateral force for the vehicle motion. The proposed controller only requires the online adaptation of control gains without acquiring the knowledge of upper bounds on system uncertainties. Static and dynamic control allocation approaches have been formulated to distribute high-level control objectives among the system inputs. For static control allocation, the interior-point method is applied to solve the formulated nonlinear optimization problem. Based on the dynamic control allocation method, a dynamic update law is derived to allocate vehicle control to tire forces. The allocated tire forces are fed into a low-level control module, where the applied torque and active steering angle at each wheel are determined through a slip-ratio controller and an inverse tire model. Computer simulations are used to prove the significant effects of the proposed control allocation methods on improving the stability and handling performance. The advantages and limitations of each method have been discussed, and conclusions have been derived.

  18. Strategic tradeoffs in competitor dynamics on adaptive networks

    CERN Document Server

    Hébert-Dufresne, Laurent; Noël, Pierre-André; Young, Jean-Gabriel; Libby, Eric

    2016-01-01

    Non-linear competitor dynamics have been studied on several non-trivial but static network structures. We consider a general model on adaptive networks and interpret the resulting structure as a signature of competitor strategies. We combine the voter model with a directed stochastic block model to encode how a strategy targets competitors (i.e., an aggressive strategy) or its own type (i.e., a defensive strategy). We solve the dynamics in particular cases with tradeoffs between aggressiveness and defensiveness. These tradeoffs yield interesting behaviors such as long transient dynamics, sensitive dependence to initial conditions, and non-transitive dynamics. Not only are such results reminiscent of classic voting paradoxes but they also translate to a dynamical view of political campaign strategies. Finally, while in a two competitor system there exists an optimal strategy that balances aggressiveness and defensiveness, three competitor systems have no such solution. The introduction of extreme strategies ca...

  19. Context Aware Adaptive Service based Dynamic Channel Allocation Approach for Providing an Optimal QoS over MANET

    Directory of Open Access Journals (Sweden)

    A. Ayyasamy

    2014-07-01

    Full Text Available Large variations in network Quality of Service (QoS in terms of bandwidth, latency and jitter may occur during media transfer over mobile ad-hoc networks. Applications need to adapt their functionality according to dynamic change of their QoS update. This paper proposes an enhanced service based platform to provide adaptive network management services to higher level application layer components. The Context Aware Adaptive Service (COAAS is a middleware architecture for service adaptation based on ad hoc network and service awareness. COAAS is structured in such a way that it can provide QoS awareness to streaming applications as well manage dynamic ad hoc network resources using an adaptive channel allocation approach. The overall architecture of COAAS framework includes core components to connection establishment, connection monitor, connection controller and policy manager. Adaptive channel allocation defined as object based component helps in dynamic binding during run time implemented using JXTA and J2ME using CDC [15] toolkit to demonstrate the performance of a mobile setup as a conference application.

  20. Nonlinear structural joint model updating based on instantaneous characteristics of dynamic responses

    Science.gov (United States)

    Wang, Zuo-Cai; Xin, Yu; Ren, Wei-Xin

    2016-08-01

    This paper proposes a new nonlinear joint model updating method for shear type structures based on the instantaneous characteristics of the decomposed structural dynamic responses. To obtain an accurate representation of a nonlinear system's dynamics, the nonlinear joint model is described as the nonlinear spring element with bilinear stiffness. The instantaneous frequencies and amplitudes of the decomposed mono-component are first extracted by the analytical mode decomposition (AMD) method. Then, an objective function based on the residuals of the instantaneous frequencies and amplitudes between the experimental structure and the nonlinear model is created for the nonlinear joint model updating. The optimal values of the nonlinear joint model parameters are obtained by minimizing the objective function using the simulated annealing global optimization method. To validate the effectiveness of the proposed method, a single-story shear type structure subjected to earthquake and harmonic excitations is simulated as a numerical example. Then, a beam structure with multiple local nonlinear elements subjected to earthquake excitation is also simulated. The nonlinear beam structure is updated based on the global and local model using the proposed method. The results show that the proposed local nonlinear model updating method is more effective for structures with multiple local nonlinear elements. Finally, the proposed method is verified by the shake table test of a real high voltage switch structure. The accuracy of the proposed method is quantified both in numerical and experimental applications using the defined error indices. Both the numerical and experimental results have shown that the proposed method can effectively update the nonlinear joint model.

  1. Eco-evolutionary feedbacks, adaptive dynamics and evolutionary rescue theory

    Science.gov (United States)

    Ferriere, Regis; Legendre, Stéphane

    2013-01-01

    Adaptive dynamics theory has been devised to account for feedbacks between ecological and evolutionary processes. Doing so opens new dimensions to and raises new challenges about evolutionary rescue. Adaptive dynamics theory predicts that successive trait substitutions driven by eco-evolutionary feedbacks can gradually erode population size or growth rate, thus potentially raising the extinction risk. Even a single trait substitution can suffice to degrade population viability drastically at once and cause ‘evolutionary suicide’. In a changing environment, a population may track a viable evolutionary attractor that leads to evolutionary suicide, a phenomenon called ‘evolutionary trapping’. Evolutionary trapping and suicide are commonly observed in adaptive dynamics models in which the smooth variation of traits causes catastrophic changes in ecological state. In the face of trapping and suicide, evolutionary rescue requires that the population overcome evolutionary threats generated by the adaptive process itself. Evolutionary repellors play an important role in determining how variation in environmental conditions correlates with the occurrence of evolutionary trapping and suicide, and what evolutionary pathways rescue may follow. In contrast with standard predictions of evolutionary rescue theory, low genetic variation may attenuate the threat of evolutionary suicide and small population sizes may facilitate escape from evolutionary traps. PMID:23209163

  2. Nonhydrostatic adaptive mesh dynamics for multiscale climate models (Invited)

    Science.gov (United States)

    Collins, W.; Johansen, H.; McCorquodale, P.; Colella, P.; Ullrich, P. A.

    2013-12-01

    Many of the atmospheric phenomena with the greatest potential impact in future warmer climates are inherently multiscale. Such meteorological systems include hurricanes and tropical cyclones, atmospheric rivers, and other types of hydrometeorological extremes. These phenomena are challenging to simulate in conventional climate models due to the relatively coarse uniform model resolutions relative to the native nonhydrostatic scales of the phenomonological dynamics. To enable studies of these systems with sufficient local resolution for the multiscale dynamics yet with sufficient speed for climate-change studies, we have adapted existing adaptive mesh dynamics for the DOE-NSF Community Atmosphere Model (CAM). In this talk, we present an adaptive, conservative finite volume approach for moist non-hydrostatic atmospheric dynamics. The approach is based on the compressible Euler equations on 3D thin spherical shells, where the radial direction is treated implicitly (using a fourth-order Runga-Kutta IMEX scheme) to eliminate time step constraints from vertical acoustic waves. Refinement is performed only in the horizontal directions. The spatial discretization is the equiangular cubed-sphere mapping, with a fourth-order accurate discretization to compute flux averages on faces. By using both space-and time-adaptive mesh refinement, the solver allocates computational effort only where greater accuracy is needed. The resulting method is demonstrated to be fourth-order accurate for model problems, and robust at solution discontinuities and stable for large aspect ratios. We present comparisons using a simplified physics package for dycore comparisons of moist physics. Hadley cell lifting an advected tracer into upper atmosphere, with horizontal adaptivity

  3. Scale-free dynamics of somatic adaptability in immune system

    CERN Document Server

    Saito, Shiro

    2009-01-01

    The long-time dynamics of somatic adaptability in immune system is simulated by a simple physical model. The immune system described by the model exhibits a scale free behavior as is observed in living systems. The balance between the positive and negative feedbacks of the model leads to a robust immune system where the positive one corresponds to the formation of memory cells and the negative one to immunosuppression. Also the immunosenescence of the system is discussed based on the time-dependence of the epigenetic landscape of the adaptive immune cells in the shape space.

  4. Applications of image metrics in dynamic scene adaptation

    Science.gov (United States)

    Sadjadi, Firooz A.

    1992-08-01

    One of the major problems in dealing with the changes in the information contented a scene which is one of the characteristics of any dynamic scene is how adapt to these variations such that the performance of any automatic scene analyzer such as object recognizer be at its optimum. In this paper we examine the use of image and signal metrics for characterizing any scene variations and then we describe an automated system for the extraction of these quality measures and finally we will show how these metrics can be used for the automatic adaptation of an object recognition system and the resulting jump in the performance of this system.

  5. Adaptive Dynamic Process Scheduling on Distributed Memory Parallel Computers

    Directory of Open Access Journals (Sweden)

    Wei Shu

    1994-01-01

    Full Text Available One of the challenges in programming distributed memory parallel machines is deciding how to allocate work to processors. This problem is particularly important for computations with unpredictable dynamic behaviors or irregular structures. We present a scheme for dynamic scheduling of medium-grained processes that is useful in this context. The adaptive contracting within neighborhood (ACWN is a dynamic, distributed, load-dependent, and scalable scheme. It deals with dynamic and unpredictable creation of processes and adapts to different systems. The scheme is described and contrasted with two other schemes that have been proposed in this context, namely the randomized allocation and the gradient model. The performance of the three schemes on an Intel iPSC/2 hypercube is presented and analyzed. The experimental results show that even though the ACWN algorithm incurs somewhat larger overhead than the randomized allocation, it achieves better performance in most cases due to its adaptiveness. Its feature of quickly spreading the work helps it outperform the gradient model in performance and scalability.

  6. Error bounds of adaptive dynamic programming algorithms for solving undiscounted optimal control problems.

    Science.gov (United States)

    Liu, Derong; Li, Hongliang; Wang, Ding

    2015-06-01

    In this paper, we establish error bounds of adaptive dynamic programming algorithms for solving undiscounted infinite-horizon optimal control problems of discrete-time deterministic nonlinear systems. We consider approximation errors in the update equations of both value function and control policy. We utilize a new assumption instead of the contraction assumption in discounted optimal control problems. We establish the error bounds for approximate value iteration based on a new error condition. Furthermore, we also establish the error bounds for approximate policy iteration and approximate optimistic policy iteration algorithms. It is shown that the iterative approximate value function can converge to a finite neighborhood of the optimal value function under some conditions. To implement the developed algorithms, critic and action neural networks are used to approximate the value function and control policy, respectively. Finally, a simulation example is given to demonstrate the effectiveness of the developed algorithms.

  7. Discrete-Time Local Value Iteration Adaptive Dynamic Programming: Admissibility and Termination Analysis.

    Science.gov (United States)

    Wei, Qinglai; Liu, Derong; Lin, Qiao

    2016-08-03

    In this paper, a novel local value iteration adaptive dynamic programming (ADP) algorithm is developed to solve infinite horizon optimal control problems for discrete-time nonlinear systems. The focuses of this paper are to study admissibility properties and the termination criteria of discrete-time local value iteration ADP algorithms. In the discrete-time local value iteration ADP algorithm, the iterative value functions and the iterative control laws are both updated in a given subset of the state space in each iteration, instead of the whole state space. For the first time, admissibility properties of iterative control laws are analyzed for the local value iteration ADP algorithm. New termination criteria are established, which terminate the iterative local ADP algorithm with an admissible approximate optimal control law. Finally, simulation results are given to illustrate the performance of the developed algorithm.

  8. Adaptive lag synchronization of uncertain dynamical systems with time delays via simple transmission lag feedback

    Institute of Scientific and Technical Information of China (English)

    Gu Wei-Dong; Sun Zhi-Yong; Wu Xiao-Ming; Yu Chang-Bin

    2013-01-01

    In this paper we present an adaptive scheme to achieve lag synchronization for uncertain dynamical systems with time delays and unknown parameters.In contrast to the nonlinear feedback scheme reported in the previous literature,the proposed controller is a linear one which only involves simple feedback information from the drive system with signal propagation lags.Besides,the unknown parameters can also be identified via the proposed updating laws in spite of the existence of model delays and transmission lags,as long as the linear independence condition between the related function elements is satisfied.Two examples,i.e.,the Mackey-Glass model with single delay and the Lorenz system with multiple delays,are employed to show the effectiveness of this approach.Some robustness issues are also discussed,which shows that the proposed scheme is quite robust in switching and noisy environment.

  9. Market mood, adaptive beliefs and asset price dynamics

    Energy Technology Data Exchange (ETDEWEB)

    Dieci, Roberto [Dipartimento di Matematica per le Scienze Economiche e Sociali, University of Bologna, Bologna (Italy)]. E-mail: rdieci@rimini.unibo.it; Foroni, Ilaria [Dipartimento di Metodi Quantitativi per le Scienze Economiche e Aziendali, University of Milano ' Bicocca' , Milan (Italy); Gardini, Laura [Istituto di Scienze Economiche, University of Urbino, Urbino (Italy); He Xuezhong [School of Finance and Economics, University of Technology, Sydney (Australia)

    2006-08-15

    Empirical evidence has suggested that, facing different trading strategies and complicated decision, the proportions of agents relying on particular strategies may stay at constant level or vary over time. This paper presents a simple 'dynamic market fraction' model of two groups of traders, fundamentalists and trend followers, under a market maker scenario. Market mood and evolutionary adaption are characterized by fixed and adaptive switching fraction among two groups, respectively. Using local stability and bifurcation analysis, as well as numerical simulation, the role played by the key parameters in the market behaviour is examined. Particular attention is paid to the impact of the market fraction, determined by the fixed proportions of confident fundamentalists and trend followers, and by the proportion of adaptively rational agents, who adopt different strategies over time depending on realized profits.

  10. Adaptive dynamic programming with applications in optimal control

    CERN Document Server

    Liu, Derong; Wang, Ding; Yang, Xiong; Li, Hongliang

    2017-01-01

    This book covers the most recent developments in adaptive dynamic programming (ADP). The text begins with a thorough background review of ADP making sure that readers are sufficiently familiar with the fundamentals. In the core of the book, the authors address first discrete- and then continuous-time systems. Coverage of discrete-time systems starts with a more general form of value iteration to demonstrate its convergence, optimality, and stability with complete and thorough theoretical analysis. A more realistic form of value iteration is studied where value function approximations are assumed to have finite errors. Adaptive Dynamic Programming also details another avenue of the ADP approach: policy iteration. Both basic and generalized forms of policy-iteration-based ADP are studied with complete and thorough theoretical analysis in terms of convergence, optimality, stability, and error bounds. Among continuous-time systems, the control of affine and nonaffine nonlinear systems is studied using the ADP app...

  11. Cascaded adaptive control of ocean vehicles with significant actuator dynamics

    Directory of Open Access Journals (Sweden)

    Thor I. Fossen

    1994-04-01

    Full Text Available This paper presents a cascade adaptive control scheme for marine vehicles where the non-linear equations of motion include a model of the actuator dynamics. The adaptive controller does not require the parameters of the vehicle dynamics and the actuator time constants to be known a priori. Both the velocity and position tracking errors are shown to converge to zero by applying Barbalat's lemma. Global asymptotic stability is proven for the velocity scheme while the position/attitude controller is only proven to be convergent. Furthermore, all parameter estimates are shown to be bounded. Computer simulations of an ROV speed control system and an autopilot for automatic ship steering are used to illustrate the design methodology.

  12. Speaker adapted dynamic lexicons containing phonetic deviations of words

    Institute of Scientific and Technical Information of China (English)

    Bahram VAZIRNEZHAD; Farshad ALMASGANJ; Seyed Mohammad AHADI; Ari CHANEN

    2009-01-01

    Speaker variability is an important source of speech variations which makes continuous speech recognition a difficult task. Adapting automatic speech recognition (ASR) models to the speaker variations is a well-known strategy to cope with the challenge. Almost all such techniques focus on developing adaptation solutions within the acoustic models of the ASR systems. Although variations of the acoustic features constitute an important portion of the inter-speaker variations, they do not cover variations at the phonetic level. Phonetic variations are known to form an important part of variations which are influenced by both micro-segmental and suprasegmental factors. Inter-speaker phonetic variations are influenced by the structure and anatomy of a speaker's articulatory system and also his/her speaking style which is driven by many speaker background characteristics such as accent, gender, age, socioeconomic and educational class. The effect of inter-speaker variations in the feature space may cause explicit phone recognition errors. These errors can be compensated later by having appropriate pronunciation variants for the lexicon entries which consider likely phone misclassifications besides pronunciation. In this paper, we introduce speaker adaptive dynamic pronunciation models, which generate different lexicons for various speaker clusters and different ranges of speech rate. The models are hybrids of speaker adapted contextual rules and dynamic generalized decision trees, which take into account word phonological structures, rate of speech, unigram probabilities and stress to generate pronunciation variants of words. Employing the set of speaker adapted dynamic lexicons in a Farsi (Persian) continuous speech recognition task results in word error rate reductions of as much as 10.1% in a speaker-dependent scenario and 7.4% in a speaker-independent scenario.

  13. Parallel Data Cube Storage Structure for Range Sum Queries and Dynamic Updates

    Institute of Scientific and Technical Information of China (English)

    Hong Gao; Jian-Zhong Li

    2005-01-01

    I/O parallelism is considered to be a promising approach to achieving high performance in parallel data warehousing systems where huge amounts of data and complex analytical queries have to be processed. This paper proposes a parallel secondary data cube storage structure (PHC for short) to efficiently support the processing of range sum queries and dynamic updates on data cube using parallel computing systems. Based on PHC, two parallel algorithms for processing range sum queries and updates are proposed also. Both the algorithms have the same time complexity, O(loga n/P). The analytical and experimental results show that PHC and the parallel algorithms have high performance and achieve optimum speedup.

  14. Multi-loop adaptive internal model control based on a dynamic partial least squares model

    Institute of Scientific and Technical Information of China (English)

    Zhao ZHAO; Bin HU; Jun LIANG

    2011-01-01

    A multi-loop adaptive internal model control (IMC) strategy based on a dynamic partial least squares (PLS) framework is proposed to account for plant model errors caused by slow aging, drift in operational conditions, or environmental changes. Since PLS decomposition structure enables multi-loop controller design within latent spaces, a multivariable adaptive control scheme can be converted easily into several independent univariable control loops in the PLS space. In each latent subspace,once the model error exceeds a specific threshold, online adaptation rules are implemented separately to correct the plant model mismatch via a recursive least squares (RLS) algorithm. Because the IMC extracts the inverse of the minimum part of the internal model as its structure, the IMC controller is self-tuned by explicitly updating the parameters, which are parts of the internal model.Both parameter convergence and system stability are briefly analyzed, and proved to be effective. Finally, the proposed control scheme is tested and evaluated using a widely-used benchmark of a multi-input multi-output (MIMO) system with pure delay.

  15. Dynamic modeling, property investigation, and adaptive controller design of serial robotic manipulators modeled with structural compliance

    Science.gov (United States)

    Tesar, Delbert; Tosunoglu, Sabri; Lin, Shyng-Her

    1990-01-01

    Research results on general serial robotic manipulators modeled with structural compliances are presented. Two compliant manipulator modeling approaches, distributed and lumped parameter models, are used in this study. System dynamic equations for both compliant models are derived by using the first and second order influence coefficients. Also, the properties of compliant manipulator system dynamics are investigated. One of the properties, which is defined as inaccessibility of vibratory modes, is shown to display a distinct character associated with compliant manipulators. This property indicates the impact of robot geometry on the control of structural oscillations. Example studies are provided to illustrate the physical interpretation of inaccessibility of vibratory modes. Two types of controllers are designed for compliant manipulators modeled by either lumped or distributed parameter techniques. In order to maintain the generality of the results, neither linearization is introduced. Example simulations are given to demonstrate the controller performance. The second type controller is also built for general serial robot arms and is adaptive in nature which can estimate uncertain payload parameters on-line and simultaneously maintain trajectory tracking properties. The relation between manipulator motion tracking capability and convergence of parameter estimation properties is discussed through example case studies. The effect of control input update delays on adaptive controller performance is also studied.

  16. Adaptive uniform grayscale coded aperture design for high dynamic range compressive spectral imaging

    Science.gov (United States)

    Diaz, Nelson; Rueda, Hoover; Arguello, Henry

    2016-05-01

    Imaging spectroscopy is an important area with many applications in surveillance, agriculture and medicine. The disadvantage of conventional spectroscopy techniques is that they collect the whole datacube. In contrast, compressive spectral imaging systems capture snapshot compressive projections, which are the input of reconstruction algorithms to yield the underlying datacube. Common compressive spectral imagers use coded apertures to perform the coded projections. The coded apertures are the key elements in these imagers since they define the sensing matrix of the system. The proper design of the coded aperture entries leads to a good quality in the reconstruction. In addition, the compressive measurements are prone to saturation due to the limited dynamic range of the sensor, hence the design of coded apertures must consider saturation. The saturation errors in compressive measurements are unbounded and compressive sensing recovery algorithms only provide solutions for bounded noise or bounded with high probability. In this paper it is proposed the design of uniform adaptive grayscale coded apertures (UAGCA) to improve the dynamic range of the estimated spectral images by reducing the saturation levels. The saturation is attenuated between snapshots using an adaptive filter which updates the entries of the grayscale coded aperture based on the previous snapshots. The coded apertures are optimized in terms of transmittance and number of grayscale levels. The advantage of the proposed method is the efficient use of the dynamic range of the image sensor. Extensive simulations show improvements in the image reconstruction of the proposed method compared with grayscale coded apertures (UGCA) and adaptive block-unblock coded apertures (ABCA) in up to 10 dB.

  17. Knowledge update in adaptive management of forest resources under climate change

    DEFF Research Database (Denmark)

    Yousefpour, Rasoul; Jacobsen, Jette Bredahl; Meilby, Henrik;

    2014-01-01

    : We simplify climate change outcomes to three possible trajectories of low, medium and high changes. We solve a hypothetical decision-making problem of tree species choice aiming at maximising the land expectation value (LEV) and based on the updated beliefs at each time step. Results: The economic...

  18. An evolutionary dynamics model adapted to eusocial insects.

    Directory of Open Access Journals (Sweden)

    Louise van Oudenhove

    Full Text Available This study aims to better understand the evolutionary processes allowing species coexistence in eusocial insect communities. We develop a mathematical model that applies adaptive dynamics theory to the evolutionary dynamics of eusocial insects, focusing on the colony as the unit of selection. The model links long-term evolutionary processes to ecological interactions among colonies and seasonal worker production within the colony. Colony population dynamics is defined by both worker production and colony reproduction. Random mutations occur in strategies, and mutant colonies enter the community. The interactions of colonies at the ecological timescale drive the evolution of strategies at the evolutionary timescale by natural selection. This model is used to study two specific traits in ants: worker body size and the degree of collective foraging. For both traits, trade-offs in competitive ability and other fitness components allows to determine conditions in which selection becomes disruptive. Our results illustrate that asymmetric competition underpins diversity in ant communities.

  19. Client-Driven Joint Cache Management and Rate Adaptation for Dynamic Adaptive Streaming over HTTP

    Directory of Open Access Journals (Sweden)

    Chenghao Liu

    2013-01-01

    Full Text Available Due to the fact that proxy-driven proxy cache management and the client-driven streaming solution of Dynamic Adaptive Streaming over HTTP (DASH are two independent processes, some difficulties and challenges arise in media data management at the proxy cache and rate adaptation at the DASH client. This paper presents a novel client-driven joint proxy cache management and DASH rate adaptation method, named CLICRA, which moves prefetching intelligence from the proxy cache to the client. Based on the philosophy of CLICRA, this paper proposes a rate adaptation algorithm, which selects bitrates for the next media segments to be requested by using the predicted buffered media time in the client. CLICRA is realized by conveying information on the segments that are likely to be fetched subsequently to the proxy cache so that it can use the information for prefetching. Simulation results show that the proposed method outperforms the conventional segment-fetch-time-based rate adaptation and the proxy-driven proxy cache management significantly not only in streaming quality at the client but also in bandwidth and storage usage in proxy caches.

  20. An Efficient Technique for Updating the Principal Component Analysis in Dynamic Databases

    Institute of Scientific and Technical Information of China (English)

    KuiCao; YucaiFeng

    2004-01-01

    Storage and retrieval of multimedia objects has become a requirement for many contemporary systems.For example,given an image database,one may want to retrieve all images that are similar to a query image.Asmany content-based retrieval techniques for digital imagery use a feature vector approach to represent image contents,it is desirable to reduce the dimensionality of the data,whilst maintaining as much of its original structure.Several dimensionality reduction techniques are available.The most popular one is PCA,which works well for static databases.In this paper,we present a novel scheme for performing PCA-based dimensionality reduction in dynamic databases.Instead of using the entire dataset,we only recompute the PCA transform matrix on the updating dataset.Note that the size of the updating dataset is usually much smaller than that of the entire data,this technique may reduce the PCA computation time complexity without losing exactness.In addition,the updates to the database are based on the existing dimensionality-reduced data vectors rather than the original high-dimensional data vectors,which may relieve the system overhead for the management of the original high-dimensional data.

  1. Synchronization dynamics in diverse ensemble of noisy phase oscillators with asynchronous phase updates

    Science.gov (United States)

    Belan, S.

    2015-12-01

    Decentralized control of autonomous phase oscillators integrated into networked systems is of great interest for many technological applications, from clock synchronization in sensor nets to coordinated motion in swarm robotics. In the simplest distributed synchronization scheme, each oscillator updates its phase from time to time to a new value equal to the average of its present phase and the phases of its neighbors. Here we describe the resulting synchronization dynamics within a mean-field model where the update actions of different oscillators are completely asynchronous. In particular, it is shown how the steady-state level of synchrony depends on noise intensity and frequency diversity for any given rate of updates. The central part of the analysis is devoted to the case when the correction rate positively correlates with the degree of macroscopic coherence. We demonstrate that depending on relation between correction rate and phase coherence the oscillators may exhibit both continuous and discontinuous transition from incoherence to synchrony upon the change of interaction constant. To illustrate our analytical results, numerical simulations have been performed for a large population of phase oscillators with the proposed type of coupling.

  2. Synchronization dynamics in diverse ensemble of noisy phase oscillators with asynchronous phase updates.

    Science.gov (United States)

    Belan, S

    2015-12-01

    Decentralized control of autonomous phase oscillators integrated into networked systems is of great interest for many technological applications, from clock synchronization in sensor nets to coordinated motion in swarm robotics. In the simplest distributed synchronization scheme, each oscillator updates its phase from time to time to a new value equal to the average of its present phase and the phases of its neighbors. Here we describe the resulting synchronization dynamics within a mean-field model where the update actions of different oscillators are completely asynchronous. In particular, it is shown how the steady-state level of synchrony depends on noise intensity and frequency diversity for any given rate of updates. The central part of the analysis is devoted to the case when the correction rate positively correlates with the degree of macroscopic coherence. We demonstrate that depending on relation between correction rate and phase coherence the oscillators may exhibit both continuous and discontinuous transition from incoherence to synchrony upon the change of interaction constant. To illustrate our analytical results, numerical simulations have been performed for a large population of phase oscillators with the proposed type of coupling.

  3. A DYNAMIC APPROACH FOR RATE ADAPTATION IN MOBILE ADHOC NETWORKS

    Directory of Open Access Journals (Sweden)

    Suganya Subramaniam

    2013-01-01

    Full Text Available A Mobile Ad hoc Network (MANET is a collection of mobile nodes with no fixed infrastructure. The absence of central authorization facility in dynamic and distributed environment affects the optimal utilization of resources like, throughput, power and bandwidth. Rate adaptation is the key technique to optimize the resource throughput. Some recently proposed rate adaptations use Request to Send/Clear to Send (RTS/CTS to suppress the collision effect by differentiating collisions from channel errors. This study presents a methodology to detect the misbehavior of nodes in MANET and proposed the new dynamic algorithm for rate adaptation which in turn can improve the throughput. The proposed approach is implemented in the distributed stipulating architecture with core and access routers. This method does not require additional probing overhead incurred by RTS/CTS exchanges and may be practically deployed without change in firmware. The collision and channel error occurrence will be detected by core router and intimated to the access router to choose alternate route and retain the current rate for transmission. The extensive simulation results demonstrate the effectiveness of proposed method by comparing with existing approaches.

  4. Generalization in adaptation to stable and unstable dynamics.

    Directory of Open Access Journals (Sweden)

    Abdelhamid Kadiallah

    Full Text Available Humans skillfully manipulate objects and tools despite the inherent instability. In order to succeed at these tasks, the sensorimotor control system must build an internal representation of both the force and mechanical impedance. As it is not practical to either learn or store motor commands for every possible future action, the sensorimotor control system generalizes a control strategy for a range of movements based on learning performed over a set of movements. Here, we introduce a computational model for this learning and generalization, which specifies how to learn feedforward muscle activity in a function of the state space. Specifically, by incorporating co-activation as a function of error into the feedback command, we are able to derive an algorithm from a gradient descent minimization of motion error and effort, subject to maintaining a stability margin. This algorithm can be used to learn to coordinate any of a variety of motor primitives such as force fields, muscle synergies, physical models or artificial neural networks. This model for human learning and generalization is able to adapt to both stable and unstable dynamics, and provides a controller for generating efficient adaptive motor behavior in robots. Simulation results exhibit predictions consistent with all experiments on learning of novel dynamics requiring adaptation of force and impedance, and enable us to re-examine some of the previous interpretations of experiments on generalization.

  5. A Static Greedy and Dynamic Adaptive Thread Spawning Approach for Loop-Level Parallelism

    Institute of Scientific and Technical Information of China (English)

    李美蓉; 赵银亮; 陶悠; 王启明

    2014-01-01

    Thread-level speculation becomes more attractive for the exploitation of thread-level parallelism from irregular sequential applications. But it is common for speculative threads to fail to reach the expected parallel performance. The reason is that the performance of speculative threads is extremely complicated by the fact that it not only suffers from the imprecision of compiler-directed performance estimation due to ambiguous control and data dependences, but also depends on the underlying hardware configuration and program behaviors. Thus, this paper proposes a statically greedy and dynamically adaptive approach for loop-level speculation to dynamically determine the best loop level at runtime. It relies on the compiler to select and optimize all loop candidates greedily, which are then proceeded on the cost-benefit analysis of different loop nesting levels for the determination of the order of loop speculation. Under the runtime loop execution prediction, we dynamically schedule and update the order of loop speculation, and ensure the best loop level to be always parallelized. Two different policies are also examined to maximize overall performance. Compared with traditional static loop selection techniques, our approach can achieve comparable or better performance.

  6. Constitutional dynamic chemistry: bridge from supramolecular chemistry to adaptive chemistry.

    Science.gov (United States)

    Lehn, Jean-Marie

    2012-01-01

    Supramolecular chemistry aims at implementing highly complex chemical systems from molecular components held together by non-covalent intermolecular forces and effecting molecular recognition, catalysis and transport processes. A further step consists in the investigation of chemical systems undergoing self-organization, i.e. systems capable of spontaneously generating well-defined functional supramolecular architectures by self-assembly from their components, thus behaving as programmed chemical systems. Supramolecular chemistry is intrinsically a dynamic chemistry in view of the lability of the interactions connecting the molecular components of a supramolecular entity and the resulting ability of supramolecular species to exchange their constituents. The same holds for molecular chemistry when the molecular entity contains covalent bonds that may form and break reversibility, so as to allow a continuous change in constitution by reorganization and exchange of building blocks. These features define a Constitutional Dynamic Chemistry (CDC) on both the molecular and supramolecular levels.CDC introduces a paradigm shift with respect to constitutionally static chemistry. The latter relies on design for the generation of a target entity, whereas CDC takes advantage of dynamic diversity to allow variation and selection. The implementation of selection in chemistry introduces a fundamental change in outlook. Whereas self-organization by design strives to achieve full control over the output molecular or supramolecular entity by explicit programming, self-organization with selection operates on dynamic constitutional diversity in response to either internal or external factors to achieve adaptation.The merging of the features: -information and programmability, -dynamics and reversibility, -constitution and structural diversity, points to the emergence of adaptive and evolutive chemistry, towards a chemistry of complex matter.

  7. Organisational learning and self-adaptation in dynamic disaster environments.

    Science.gov (United States)

    Corbacioglu, Sitki; Kapucu, Naim

    2006-06-01

    This paper examines the problems associated with inter-organisational learning and adaptation in the dynamic environments that characterise disasters. The research uses both qualitative and quantitative methods to investigate whether organisational learning took place during and in the time in between five disaster response operations in Turkey. The availability of information and its exchange and distribution within and among organisational actors determine whether self-adaptation happens in the course of a disaster response operation. Organisational flexibility supported by an appropriate information infrastructure creates conditions conducive to essential interaction and permits the flow of information. The study found that no significant organisational learning occurred within Turkish disaster management following the earthquakes in Erzincan (1992), Dinar (1995) and Ceyhan (1998). By contrast, the 'symmetry-breaking' Marmara earthquake of 1999 initiated a 'double loop' learning process that led to change in the organisational, technical and cultural aspects of Turkish disaster management, as revealed by the Duzce earthquake response operations.

  8. Elucidating Microbial Adaptation Dynamics via Autonomous Exposure and Sampling

    Science.gov (United States)

    Grace, J. M.; Verseux, C.; Gentry, D.; Moffet, A.; Thayabaran, R.; Wong, N.; Rothschild, L.

    2013-12-01

    The adaptation of micro-organisms to their environments is a complex process of interaction between the pressures of the environment and of competition. Reducing this multifactorial process to environmental exposure in the laboratory is a common tool for elucidating individual mechanisms of evolution, such as mutation rates[Wielgoss et al., 2013]. Although such studies inform fundamental questions about the way adaptation and even speciation occur, they are often limited by labor-intensive manual techniques[Wassmann et al., 2010]. Current methods for controlled study of microbial adaptation limit the length of time, the depth of collected data, and the breadth of applied environmental conditions. Small idiosyncrasies in manual techniques can have large effects on outcomes; for example, there are significant variations in induced radiation resistances following similar repeated exposure protocols[Alcántara-Díaz et al., 2004; Goldman and Travisano, 2011]. We describe here a project under development to allow rapid cycling of multiple types of microbial environmental exposure. The system allows continuous autonomous monitoring and data collection of both single species and sampled communities, independently and concurrently providing multiple types of controlled environmental pressure (temperature, radiation, chemical presence or absence, and so on) to a microbial community in dynamic response to the ecosystem's current status. When combined with DNA sequencing and extraction, such a controlled environment can cast light on microbial functional development, population dynamics, inter- and intra-species competition, and microbe-environment interaction. The project's goal is to allow rapid, repeatable iteration of studies of both natural and artificial microbial adaptation. As an example, the same system can be used both to increase the pH of a wet soil aliquot over time while periodically sampling it for genetic activity analysis, or to repeatedly expose a culture of

  9. Direct Adaptive Aircraft Control Using Dynamic Cell Structure Neural Networks

    Science.gov (United States)

    Jorgensen, Charles C.

    1997-01-01

    A Dynamic Cell Structure (DCS) Neural Network was developed which learns topology representing networks (TRNS) of F-15 aircraft aerodynamic stability and control derivatives. The network is integrated into a direct adaptive tracking controller. The combination produces a robust adaptive architecture capable of handling multiple accident and off- nominal flight scenarios. This paper describes the DCS network and modifications to the parameter estimation procedure. The work represents one step towards an integrated real-time reconfiguration control architecture for rapid prototyping of new aircraft designs. Performance was evaluated using three off-line benchmarks and on-line nonlinear Virtual Reality simulation. Flight control was evaluated under scenarios including differential stabilator lock, soft sensor failure, control and stability derivative variations, and air turbulence.

  10. Age and Adaptation: Stronger Decision Updating about Real World Risks in Older Age.

    Science.gov (United States)

    Rolison, Jonathan J; Wood, Stacey; Hanoch, Yaniv

    2017-09-01

    In later life, people are faced with a multitude of risky decisions that concern their health, finance, and personal security. Older adults often exercise caution in situations that involve risk. In this research, we asked whether older adults are also more responsive to warnings about potential risk. An answer to this question could reveal a factor underlying increased cautiousness in older age. In Study 1, participants decided whether they would engage in risky activities (e.g., using an ATM machine in the street) in four realistic scenarios about which participants could be expected to have relevant knowledge or experience. They then made posterior decisions after listening to audio extracts of real reports relevant to each activity. In Study 2, we explored the role that emotions play in decision updating. As in Study 1, participants made prior and posterior decisions, with the exception that for each scenario the reports were presented in their original audio format (high emotive) or in a written transcript format (low emotive). Following each posterior decision, participants indicated their emotional valence and arousal responses to the reports. In both studies, older adults engaged in fewer risky activities than younger adults, indicative of increased cautiousness in older age, and exhibited stronger decision updating in response to the reports. Older adults also showed stronger emotional responses to the reports, even though emotional responses did not differ for audio and written transcript formats. Finally, age differences in emotional responses to the reports accounted for age differences in decision updating. © 2017 Society for Risk Analysis.

  11. Elucidating Microbial Adaptation Dynamics via Autonomous Exposure and Sampling

    Science.gov (United States)

    Grace, Joseph M.; Verseux, Cyprien; Gentry, Diana; Moffet, Amy; Thayabaran, Ramanen; Wong, Nathan; Rothschild, Lynn

    2013-01-01

    The adaptation of micro-organisms to their environments is a complex process of interaction between the pressures of the environment and of competition. Reducing this multifactorial process to environmental exposure in the laboratory is a common tool for elucidating individual mechanisms of evolution, such as mutation rates. Although such studies inform fundamental questions about the way adaptation and even speciation occur, they are often limited by labor-intensive manual techniques. Current methods for controlled study of microbial adaptation limit the length of time, the depth of collected data, and the breadth of applied environmental conditions. Small idiosyncrasies in manual techniques can have large effects on outcomes; for example, there are significant variations in induced radiation resistances following similar repeated exposure protocols. We describe here a project under development to allow rapid cycling of multiple types of microbial environmental exposure. The system allows continuous autonomous monitoring and data collection of both single species and sampled communities, independently and concurrently providing multiple types of controlled environmental pressure (temperature, radiation, chemical presence or absence, and so on) to a microbial community in dynamic response to the ecosystem's current status. When combined with DNA sequencing and extraction, such a controlled environment can cast light on microbial functional development, population dynamics, inter- and intra-species competition, and microbe-environment interaction. The project's goal is to allow rapid, repeatable iteration of studies of both natural and artificial microbial adaptation. As an example, the same system can be used both to increase the pH of a wet soil aliquot over time while periodically sampling it for genetic activity analysis, or to repeatedly expose a culture of bacteria to the presence of a toxic metal, automatically adjusting the level of toxicity based on the

  12. Dynamic Performance of Grid Converters using Adaptive DC Voltage Control

    DEFF Research Database (Denmark)

    Trintis, Ionut; Sun, Bo; Guerrero, Josep M.;

    2014-01-01

    This paper investigates a controller that ensures minimum operating dc-link voltage of a back-to-back converter system. The dc-link voltage adapts its reference based on the system state, reference given by an outer loop to the dc-link voltage controller. The operating dc-link voltage should...... be kept as low as possible to increase the power conversion efficiency and increase the reliability of converters. The dynamic performance of the proposed controller is investigated by simulations and experiments....

  13. Dynamic and adaptive data-management in ATLAS

    Energy Technology Data Exchange (ETDEWEB)

    Lassnig, Mario; Garonne, Vincent; Branco, Miguel; Molfetas, Angelos, E-mail: mario.lassnig@cern.c, E-mail: vincent.garonne@cern.c, E-mail: miguel.branco@cern.c, E-mail: angelos.molfetas@cern.c [CERN PH-ADP/DDM, 1211 Geneva (Switzerland); Faculty of Mathematics, Computer Science and Physics, University of Innsbruck (Austria)

    2010-04-01

    Distributed data-management on the grid is subject to huge uncertainties yet static policies govern its usage. Due to the unpredictability of user behaviour, the high-latency and the heterogeneous nature of the environment, distributed data-management on the grid is challenging. In this paper we present the first steps towards a future dynamic data-management system that adapts to the changing conditions and environment. Such a system would eliminate the number of manual interventions and remove unnecessary software layers, thereby providing a higher quality of service to the collaboration.

  14. Dynamic and adaptive data-management in ATLAS

    CERN Document Server

    Lassnig, M; Branco, M; Molfetas, A

    2010-01-01

    Distributed data-management on the grid is subject to huge uncertainties yet static policies govern its usage. Due to the unpredictability of user behaviour, the high-latency and the heterogeneous nature of the environment, distributed data-management on the grid is challenging. In this paper we present the first steps towards a future dynamic data-management system that adapts to the changing conditions and environment. Such a system would eliminate the number of manual interventions and remove unnecessary software layers, thereby providing a higher quality of service to the collaboration.

  15. Dynamics of Random Boolean Networks under Fully Asynchronous Stochastic Update Based on Linear Representation

    Science.gov (United States)

    Luo, Chao; Wang, Xingyuan

    2013-01-01

    A novel algebraic approach is proposed to study dynamics of asynchronous random Boolean networks where a random number of nodes can be updated at each time step (ARBNs). In this article, the logical equations of ARBNs are converted into the discrete-time linear representation and dynamical behaviors of systems are investigated. We provide a general formula of network transition matrices of ARBNs as well as a necessary and sufficient algebraic criterion to determine whether a group of given states compose an attractor of length in ARBNs. Consequently, algorithms are achieved to find all of the attractors and basins in ARBNs. Examples are showed to demonstrate the feasibility of the proposed scheme. PMID:23785502

  16. The updated geodetic mean dynamic topography model – DTU15MDT

    DEFF Research Database (Denmark)

    Knudsen, Per; Andersen, Ole Baltazar; Maximenko, Nikolai

    An update to the global mean dynamic topography model DTU13MDT is presented. For DTU15MDT the newer gravity model EIGEN-6C4 has been combined with the DTU15MSS mean sea surface model to construct this global mean dynamic topography model. The EIGEN-6C4 is derived using the full series of GOCE data...... re-tracked CRYOSAT-2 altimetry also, hence, increasing its resolution. Also, some issues in the Polar regions have been solved. Finally, the filtering was re-evaluated by adjusting the quasi-gaussian filter width to optimize the fit to drifter velocities. Subsequently, geostrophic surface currents...... were derived from the DTU15MDT. The results show that geostrophic surface currents associated with the mean circulation have been further improved and that currents having speeds down to below 4 cm/s have been recovered....

  17. Hydrodynamics in adaptive resolution particle simulations: Multiparticle collision dynamics

    Energy Technology Data Exchange (ETDEWEB)

    Alekseeva, Uliana, E-mail: Alekseeva@itc.rwth-aachen.de [Jülich Supercomputing Centre (JSC), Institute for Advanced Simulation (IAS), Forschungszentrum Jülich, D-52425 Jülich (Germany); German Research School for Simulation Sciences (GRS), Forschungszentrum Jülich, D-52425 Jülich (Germany); Winkler, Roland G., E-mail: r.winkler@fz-juelich.de [Theoretical Soft Matter and Biophysics, Institute for Advanced Simulation (IAS), Forschungszentrum Jülich, D-52425 Jülich (Germany); Sutmann, Godehard, E-mail: g.sutmann@fz-juelich.de [Jülich Supercomputing Centre (JSC), Institute for Advanced Simulation (IAS), Forschungszentrum Jülich, D-52425 Jülich (Germany); ICAMS, Ruhr-University Bochum, D-44801 Bochum (Germany)

    2016-06-01

    A new adaptive resolution technique for particle-based multi-level simulations of fluids is presented. In the approach, the representation of fluid and solvent particles is changed on the fly between an atomistic and a coarse-grained description. The present approach is based on a hybrid coupling of the multiparticle collision dynamics (MPC) method and molecular dynamics (MD), thereby coupling stochastic and deterministic particle-based methods. Hydrodynamics is examined by calculating velocity and current correlation functions for various mixed and coupled systems. We demonstrate that hydrodynamic properties of the mixed fluid are conserved by a suitable coupling of the two particle methods, and that the simulation results agree well with theoretical expectations.

  18. Opinion dynamics on a group structured adaptive network

    CERN Document Server

    Gargiulo, F

    2009-01-01

    Many models have been proposed to analyze the evolution of opinion structure due to the interaction of individuals in their social environment. Such models analyze the spreading of ideas both in completely interacting backgrounds and on social networks, where each person has a finite set of interlocutors.Moreover also the investigation on the topological structure of social networks has been object of several analysis, both from the theoretical and the empirical point of view. In this framework a particularly important area of study regards the community structure inside social networks.In this paper we analyze the reciprocal feedback between the opinions of the individuals and the structure of the interpersonal relationships at the level of community structures. For this purpose we define a group based random network and we study how this structure co-evolve with opinion dynamics processes. We observe that the adaptive network structure affects the opinion dynamics process helping the consensus formation. Th...

  19. Dynamics of epidemic diseases on a growing adaptive network

    Science.gov (United States)

    Demirel, Güven; Barter, Edmund; Gross, Thilo

    2017-02-01

    The study of epidemics on static networks has revealed important effects on disease prevalence of network topological features such as the variance of the degree distribution, i.e. the distribution of the number of neighbors of nodes, and the maximum degree. Here, we analyze an adaptive network where the degree distribution is not independent of epidemics but is shaped through disease-induced dynamics and mortality in a complex interplay. We study the dynamics of a network that grows according to a preferential attachment rule, while nodes are simultaneously removed from the network due to disease-induced mortality. We investigate the prevalence of the disease using individual-based simulations and a heterogeneous node approximation. Our results suggest that in this system in the thermodynamic limit no epidemic thresholds exist, while the interplay between network growth and epidemic spreading leads to exponential networks for any finite rate of infectiousness when the disease persists.

  20. Annual Reports & Seasonal Updates : Arctic Grayling Adaptive Management : Upper Centennial Valley : 2011-present

    Data.gov (United States)

    US Fish and Wildlife Service, Department of the Interior — The Arctic Grayling Adaptive Management Project is focused on identifying the limiting factor, or factors, for Arctic Grayling in the upper Centennial Valley of...

  1. Selective host molecules obtained by dynamic adaptive chemistry.

    Science.gov (United States)

    Matache, Mihaela; Bogdan, Elena; Hădade, Niculina D

    2014-02-17

    Up till 20 years ago, in order to endow molecules with function there were two mainstream lines of thought. One was to rationally design the positioning of chemical functionalities within candidate molecules, followed by an iterative synthesis-optimization process. The second was the use of a "brutal force" approach of combinatorial chemistry coupled with advanced screening for function. Although both methods provided important results, "rational design" often resulted in time-consuming efforts of modeling and synthesis only to find that the candidate molecule was not performing the designed job. "Combinatorial chemistry" suffered from a fundamental limitation related to the focusing of the libraries employed, often using lead compounds that limit its scope. Dynamic constitutional chemistry has developed as a combination of the two approaches above. Through the rational use of reversible chemical bonds together with a large plethora of precursor libraries, one is now able to build functional structures, ranging from quite simple molecules up to large polymeric structures. Thus, by introduction of the dynamic component within the molecular recognition processes, a new perspective of deciphering the world of the molecular events has aroused together with a new field of chemistry. Since its birth dynamic constitutional chemistry has continuously gained attention, in particular due to its ability to easily create from scratch outstanding molecular structures as well as the addition of adaptive features. The fundamental concepts defining the dynamic constitutional chemistry have been continuously extended to currently place it at the intersection between the supramolecular chemistry and newly defined adaptive chemistry, a pivotal feature towards evolutive chemistry. Copyright © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  2. Effect of Adaptive Delivery Capacity on Networked Traffic Dynamics

    Institute of Scientific and Technical Information of China (English)

    CAO Xian-Bin; DU Wen-Bo; CHEN Cai-Long; ZHANG Jun

    2011-01-01

    @@ We introduce an adaptive delivering capacity mechanism into the traffic dynamic model on scale-free networks under shortest path routing strategy and focus on its effect on the network capacity measured by the critical point(Rc) of phase transition from free flow to congestion.Under this mechanism,the total node's delivering capacity is fixed and the allocation of delivering capacity on node i is proportional to niφ,where ni is the queue length of node i and φ is the adjustable parameter.It is found that the network capacity monotonously increases with the increment of φ,but there exists an optimal value of parameter φ leading to the highest transportation efficiency measured by average travelling time(〈T〉).Our work may be helpful for optimal design of networked traffic dynamics.%We introduce an adaptive delivering capacity mechanism into the traffic dynamic model on scale-free networks under shortest path routing strategy and focus on its effect on the network capacity measured by the critical point (Rc) of phase transition from free flow to congestion.Under this mechanism, the total node's delivering capacity is fixed and the allocation of delivering capacity on node i is proportional to niφ, where ni is the queue length of node i and φ is the adjustable parameter.It is found that the network capacity monotonously increases with the increment of φ, but there exists an optimal value of parameter φ leading to the highest transportation efficiency measured by average travelling time (<T>).Our work may be helpful for optimal design of networked traffic dynamics.

  3. Event-Based Robust Control for Uncertain Nonlinear Systems Using Adaptive Dynamic Programming.

    Science.gov (United States)

    Zhang, Qichao; Zhao, Dongbin; Wang, Ding

    2016-10-18

    In this paper, the robust control problem for a class of continuous-time nonlinear system with unmatched uncertainties is investigated using an event-based control method. First, the robust control problem is transformed into a corresponding optimal control problem with an augmented control and an appropriate cost function. Under the event-based mechanism, we prove that the solution of the optimal control problem can asymptotically stabilize the uncertain system with an adaptive triggering condition. That is, the designed event-based controller is robust to the original uncertain system. Note that the event-based controller is updated only when the triggering condition is satisfied, which can save the communication resources between the plant and the controller. Then, a single network adaptive dynamic programming structure with experience replay technique is constructed to approach the optimal control policies. The stability of the closed-loop system with the event-based control policy and the augmented control policy is analyzed using the Lyapunov approach. Furthermore, we prove that the minimal intersample time is bounded by a nonzero positive constant, which excludes Zeno behavior during the learning process. Finally, two simulation examples are provided to demonstrate the effectiveness of the proposed control scheme.

  4. Frequency adaptation for enhanced radiation force amplitude in dynamic elastography.

    Science.gov (United States)

    Ouared, Abderrahmane; Montagnon, Emmanuel; Kazemirad, Siavash; Gaboury, Louis; Robidoux, André; Cloutier, Guy

    2015-08-01

    In remote dynamic elastography, the amplitude of the generated displacement field is directly related to the amplitude of the radiation force. Therefore, displacement improvement for better tissue characterization requires the optimization of the radiation force amplitude by increasing the push duration and/or the excitation amplitude applied on the transducer. The main problem of these approaches is that the Food and Drug Administration (FDA) thresholds for medical applications and transducer limitations may be easily exceeded. In the present study, the effect of the frequency used for the generation of the radiation force on the amplitude of the displacement field was investigated. We found that amplitudes of displacements generated by adapted radiation force sequences were greater than those generated by standard nonadapted ones (i.e., single push acoustic radiation force impulse and supersonic shear imaging). Gains in magnitude were between 20 to 158% for in vitro measurements on agar-gelatin phantoms, and 170 to 336% for ex vivo measurements on a human breast sample, depending on focus depths and attenuations of tested samples. The signal-to-noise ratio was also improved more than 4-fold with adapted sequences. We conclude that frequency adaptation is a complementary technique that is efficient for the optimization of displacement amplitudes. This technique can be used safely to optimize the deposited local acoustic energy without increasing the risk of damaging tissues and transducer elements.

  5. An Update on the Scholarly Networks on Resilience, Vulnerability, and Adaptation within the Human Dimensions of Global Environmental Change

    Directory of Open Access Journals (Sweden)

    Marco A. Janssen

    2007-12-01

    Full Text Available In Janssen et al. (2006, we presented a bibliometric analysis of the resilience, vulnerability, and adaptation knowledge domains within the research activities on human dimensions of global environmental change. We have updated the analysis because 2 years have gone by since the original analysis, and 1113 more publications can now be added to the database. We analyzed how the resulting 3399 publications between 1967 and 2007 are related in terms of co-authorship and citations. The rapid increase in the number of publications in the three knowledge domains continued over the last 2 years, and we still see an overlap between the knowledge domains. We were also able to identify the “hot” publications of the last 2 years.

  6. Model-free optimal controller design for continuous-time nonlinear systems by adaptive dynamic programming based on a precompensator.

    Science.gov (United States)

    Zhang, Jilie; Zhang, Huaguang; Liu, Zhenwei; Wang, Yingchun

    2015-07-01

    In this paper, we consider the problem of developing a controller for continuous-time nonlinear systems where the equations governing the system are unknown. Using the measurements, two new online schemes are presented for synthesizing a controller without building or assuming a model for the system, by two new implementation schemes based on adaptive dynamic programming (ADP). To circumvent the requirement of the prior knowledge for systems, a precompensator is introduced to construct an augmented system. The corresponding Hamilton-Jacobi-Bellman (HJB) equation is solved by adaptive dynamic programming, which consists of the least-squared technique, neural network approximator and policy iteration (PI) algorithm. The main idea of our method is to sample the information of state, state derivative and input to update the weighs of neural network by least-squared technique. The update process is implemented in the framework of PI. In this paper, two new implementation schemes are presented. Finally, several examples are given to illustrate the effectiveness of our schemes.

  7. Diagonal recurrent neural network based adaptive control of nonlinear dynamical systems using lyapunov stability criterion.

    Science.gov (United States)

    Kumar, Rajesh; Srivastava, Smriti; Gupta, J R P

    2017-03-01

    In this paper adaptive control of nonlinear dynamical systems using diagonal recurrent neural network (DRNN) is proposed. The structure of DRNN is a modification of fully connected recurrent neural network (FCRNN). Presence of self-recurrent neurons in the hidden layer of DRNN gives it an ability to capture the dynamic behaviour of the nonlinear plant under consideration (to be controlled). To ensure stability, update rules are developed using lyapunov stability criterion. These rules are then used for adjusting the various parameters of DRNN. The responses of plants obtained with DRNN are compared with those obtained when multi-layer feed forward neural network (MLFFNN) is used as a controller. Also, in example 4, FCRNN is also investigated and compared with DRNN and MLFFNN. Robustness of the proposed control scheme is also tested against parameter variations and disturbance signals. Four simulation examples including one-link robotic manipulator and inverted pendulum are considered on which the proposed controller is applied. The results so obtained show the superiority of DRNN over MLFFNN as a controller. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

  8. Analysis of dynamic deformation processes with adaptive KALMAN-filtering

    Science.gov (United States)

    Eichhorn, Andreas

    2007-05-01

    In this paper the approach of a full system analysis is shown quantifying a dynamic structural ("white-box"-) model for the calculation of thermal deformations of bar-shaped machine elements. The task was motivated from mechanical engineering searching new methods for the precise prediction and computational compensation of thermal influences in the heating and cooling phases of machine tools (i.e. robot arms, etc.). The quantification of thermal deformations under variable dynamic loads requires the modelling of the non-stationary spatial temperature distribution inside the object. Based upon FOURIERS law of heat flow the high-grade non-linear temperature gradient is represented by a system of partial differential equations within the framework of a dynamic Finite Element topology. It is shown that adaptive KALMAN-filtering is suitable to quantify relevant disturbance influences and to identify thermal parameters (i.e. thermal diffusivity) with a deviation of only 0,2%. As result an identified (and verified) parametric model for the realistic prediction respectively simulation of dynamic temperature processes is presented. Classifying the thermal bend as the main deformation quantity of bar-shaped machine tools, the temperature model is extended to a temperature deformation model. In lab tests thermal load steps are applied to an aluminum column. Independent control measurements show that the identified model can be used to predict the columns bend with a mean deviation (r.m.s.) smaller than 10 mgon. These results show that the deformation model is a precise predictor and suitable for realistic simulations of thermal deformations. Experiments with modified heat sources will be necessary to verify the model in further frequency spectra of dynamic thermal loads.

  9. Strategic tradeoffs in competitor dynamics on adaptive networks.

    Science.gov (United States)

    Hébert-Dufresne, Laurent; Allard, Antoine; Noël, Pierre-André; Young, Jean-Gabriel; Libby, Eric

    2017-08-08

    Recent empirical work highlights the heterogeneity of social competitions such as political campaigns: proponents of some ideologies seek debate and conversation, others create echo chambers. While symmetric and static network structure is typically used as a substrate to study such competitor dynamics, network structure can instead be interpreted as a signature of the competitor strategies, yielding competition dynamics on adaptive networks. Here we demonstrate that tradeoffs between aggressiveness and defensiveness (i.e., targeting adversaries vs. targeting like-minded individuals) creates paradoxical behaviour such as non-transitive dynamics. And while there is an optimal strategy in a two competitor system, three competitor systems have no such solution; the introduction of extreme strategies can easily affect the outcome of a competition, even if the extreme strategies have no chance of winning. Not only are these results reminiscent of classic paradoxical results from evolutionary game theory, but the structure of social networks created by our model can be mapped to particular forms of payoff matrices. Consequently, social structure can act as a measurable metric for social games which in turn allows us to provide a game theoretical perspective on online political debates.

  10. Free Molecular Heat Transfer Programs for Setup and Dynamic Updating the Conductors in Thermal Desktop

    Science.gov (United States)

    Malroy, Eric T.

    2007-01-01

    The programs, arrays and logic structure were developed to enable the dynamic update of conductors in thermal desktop. The MatLab program FMHTPRE.m processes the Thermal Desktop conductors and sets up the arrays. The user needs to manually copy portions of the output to different input regions in Thermal Desktop. Also, Fortran subroutines are provided that perform the actual updates to the conductors. The subroutines are setup for helium gas, but the equations can be modified for other gases. The maximum number of free molecular conductors allowed is 10,000 for a given radiation task. Additional radiation tasks for FMHT can be generated to account for more conductors. Modifications to the Fortran subroutines may be warranted, when the mode of heat transfer is in the mixed or continuum mode. The FMHT Thermal Desktop model should be activated by using the "Case Set Manager" once the model is setup. Careful setup of the model is needed to avoid excessive solve times.

  11. Adaptive Equalizer Using Selective Partial Update Algorithm and Selective Regressor Affine Projection Algorithm over Shallow Water Acoustic Channels

    Directory of Open Access Journals (Sweden)

    Masoumeh Soflaei

    2014-01-01

    Full Text Available One of the most important problems of reliable communications in shallow water channels is intersymbol interference (ISI which is due to scattering from surface and reflecting from bottom. Using adaptive equalizers in receiver is one of the best suggested ways for overcoming this problem. In this paper, we apply the family of selective regressor affine projection algorithms (SR-APA and the family of selective partial update APA (SPU-APA which have low computational complexity that is one of the important factors that influences adaptive equalizer performance. We apply experimental data from Strait of Hormuz for examining the efficiency of the proposed methods over shallow water channel. We observe that the values of the steady-state mean square error (MSE of SR-APA and SPU-APA decrease by 5.8 (dB and 5.5 (dB, respectively, in comparison with least mean square (LMS algorithm. Also the families of SPU-APA and SR-APA have better convergence speed than LMS type algorithm.

  12. Adaptable mission planning for kino-dynamic systems

    Science.gov (United States)

    Bush, Lawrence A. M.; Jimenez, Tony R.; Williams, Brian C.

    Autonomous systems can perform tasks that are dangerous, monotonous, or even impossible for humans. To approach the problem of planning for Unmanned Aerial Vehicles (UAVs) we present a hierarchical method that combines a high-level planner with a low-level planner. We pose the problem of high-level planning as a Selective Traveling Salesman Problem (STSP) and select the order in which to visit our science sites. We then use a kino-dynamic path planner to create a large number of intermediate waypoints. This is a complete system that combines high and low level planning to achieve a goal. This paper demonstrates the benefits gained by adaptable high-level plans versus static and greedy plans.

  13. Dynamics of adaptive immunity against phage in bacterial populations

    CERN Document Server

    Bradde, Serena; Tesileanu, Tiberiu; Balasubramanian, Vijay

    2015-01-01

    The CRISPR (clustered regularly interspaced short palindromic repeats) mechanism allows bacteria to adaptively defend against phages by acquiring short genomic sequences (spacers) that target specific sequences in the viral genome. We propose a population dynamical model where immunity can be both acquired and lost. The model predicts regimes where bacterial and phage populations can co-exist, others where the populations oscillate, and still others where one population is driven to extinction. Our model considers two key parameters: (1) ease of acquisition and (2) spacer effectiveness in conferring immunity. Analytical calculations and numerical simulations show that if spacers differ mainly in ease of acquisition, or if the probability of acquiring them is sufficiently high, bacteria develop a diverse population of spacers. On the other hand, if spacers differ mainly in their effectiveness, their final distribution will be highly peaked, akin to a "winner-take-all" scenario, leading to a specialized spacer ...

  14. Adaptive Dynamic Surface Control for Generator Excitation Control System

    Directory of Open Access Journals (Sweden)

    Zhang Xiu-yu

    2014-01-01

    Full Text Available For the generator excitation control system which is equipped with static var compensator (SVC and unknown parameters, a novel adaptive dynamic surface control scheme is proposed based on neural network and tracking error transformed function with the following features: (1 the transformation of the excitation generator model to the linear systems is omitted; (2 the prespecified performance of the tracking error can be guaranteed by combining with the tracking error transformed function; (3 the computational burden is greatly reduced by estimating the norm of the weighted vector of neural network instead of the weighted vector itself; therefore, it is more suitable for the real time control; and (4 the explosion of complicity problem inherent in the backstepping control can be eliminated. It is proved that the new scheme can make the system semiglobally uniformly ultimately bounded. Simulation results show the effectiveness of this control scheme.

  15. Status Update and Closed-Loop Performance of the Magellan Adaptive Optics VisAO Camera

    CERN Document Server

    Kopon, Derek; Males, Jared; Gasho, Victor; Morzinski, Katie; Follette, Katherine

    2014-01-01

    We present laboratory results of the closed-loop performance of the Magellan Adaptive Optics (AO) Adaptive Secondary Mirror (ASM), pyramid wavefront sensor (PWFS), and VisAO visible adaptive optics camera. The Magellan AO system is a 585-actuator low-emissivity high-throughput system scheduled for first light on the 6.5 meter Magellan Clay telescope in November 2012. Using a dichroic beamsplitter near the telescope focal plane, the AO system will be able to simultaneously perform visible (500-1000 nm) AO science with our VisAO camera and either 10 micron or 3-5 micron science using either the BLINC/MIRAC4 or CLIO cameras, respectively. The ASM, PWS, and VisAO camera have undergone final system tests in the solar test tower at the Arcetri Institute in Florence, Italy, reaching Strehls of 37% in i'-band with 400 modes and simulated turbulence of 14 cm ro at v-band. We present images and test results of the assembled VisAO system, which includes our prototype advanced Atmospheric Dispersion Corrector (ADC), prot...

  16. Adaptive thermo-fluid moving boundary computations for interfacial dynamics

    Institute of Scientific and Technical Information of China (English)

    Chih-Kuang Kuan; Jaeheon Sim; Wei Shyy

    2012-01-01

    In this study,we present adaptive moving boundary computation technique with parallel implementation on a distributed memory multi-processor system for large scale thermo-fluid and interfacial flow computations.The solver utilizes Eulerian-Lagrangian method to track moving (Lagrangian) interfaces explicitly on the stationary (Eulerian)Cartesian grid where the flow fields are computed. We address the domain decomposition strategies of EulerianLagrangian method by illustrating its intricate complexity of the computation involved on two different spaces interactively and consequently,and then propose a trade-off approach aiming for parallel scalability.Spatial domain decomposition is adopted for both Eulerian and Lagrangian domain due to easy load balancing and data locality for minimum communication between processors.In addition,parallel cell-based unstructured adaptive mesh refinement (AMR)technique is implemented for the flexible local refinement and even-distributed computational workload among processors.Selected cases are presented to highlight the computational capabilities,including Faraday type interfacial waves with capillary and gravitational forcing,flows around varied geometric configurations and induced by boundary conditions and/or body forces,and thermo-fluid dynamics with phase change.With the aid of the present techniques,large scale challenging moving boundary problems can be effectively addressed.

  17. Video Vehicle Detection Based on Self-Adaptive Background Update%自适应背景更新的视频车辆检测

    Institute of Scientific and Technical Information of China (English)

    顾洋

    2012-01-01

    针对视频车辆检测技术会因气象等环境变化,尤其在动态检测大范围、多目标的情况下,检测移动车辆图像的分割和检测的效果存在问题,采用一种用于数字图像处理和计算机视觉的函数库openCV,设计出一种基于背景更新的自适应车辆对象检测法,用于视频检测和统计车流量,比较准确地测量出车辆对象.%Problems associated with the effects of image segmentation and detection of vehicle movement result from environmental changes, such as climate change, particularly under the condition of large-scale, multi-object dynamic detection. To address the problems, a vehicle object detection method based on self-adaptive background update is designed by using openCV DB for digital image processing and computer vision. This method can be used to detect videos and process the data of vehicle flow, aimed at precisely detecting vehicle objects.

  18. Cluster Optimization and Parallelization of Simulations with Dynamically Adaptive Grids

    KAUST Repository

    Schreiber, Martin

    2013-01-01

    The present paper studies solvers for partial differential equations that work on dynamically adaptive grids stemming from spacetrees. Due to the underlying tree formalism, such grids efficiently can be decomposed into connected grid regions (clusters) on-the-fly. A graph on those clusters classified according to their grid invariancy, workload, multi-core affinity, and further meta data represents the inter-cluster communication. While stationary clusters already can be handled more efficiently than their dynamic counterparts, we propose to treat them as atomic grid entities and introduce a skip mechanism that allows the grid traversal to omit those regions completely. The communication graph ensures that the cluster data nevertheless are kept consistent, and several shared memory parallelization strategies are feasible. A hyperbolic benchmark that has to remesh selected mesh regions iteratively to preserve conforming tessellations acts as benchmark for the present work. We discuss runtime improvements resulting from the skip mechanism and the implications on shared memory performance and load balancing. © 2013 Springer-Verlag.

  19. Loss Aversion, Adaptive Beliefs, and Asset Pricing Dynamics

    Directory of Open Access Journals (Sweden)

    Kamal Samy Selim

    2015-01-01

    Full Text Available We study asset pricing dynamics in artificial financial markets model. The financial market is populated with agents following two heterogeneous trading beliefs, the technical and the fundamental prediction rules. Agents switch between trading rules with respect to their past performance. The agents are loss averse over asset price fluctuations. Loss aversion behaviour depends on the past performance of the trading strategies in terms of an evolutionary fitness measure. We propose a novel application of the prospect theory to agent-based modelling, and by simulation, the effect of evolutionary fitness measure on adaptive belief system is investigated. For comparison, we study pricing dynamics of a financial market populated with chartists perceive losses and gains symmetrically. One of our contributions is validating the agent-based models using real financial data of the Egyptian Stock Exchange. We find that our framework can explain important stylized facts in financial time series, such as random walk price behaviour, bubbles and crashes, fat-tailed return distributions, power-law tails in the distribution of returns, excess volatility, volatility clustering, the absence of autocorrelation in raw returns, and the power-law autocorrelations in absolute returns. In addition to this, we find that loss aversion improves market quality and market stability.

  20. Regular database update logics

    NARCIS (Netherlands)

    Spruit, Paul; Wieringa, Roel; Meyer, John-Jules

    2001-01-01

    We study regular first-order update logic (FUL), which is a variant of regular dynamic logic in which updates to function symbols as well as to predicate symbols are possible. We fi1rst study FUL without making assumptions about atomic updates. Second, we look at relational algebra update logic (RAU

  1. Probing the Dynamic Updating of Value in Schizophrenia Using a Sensory-Specific Satiety Paradigm.

    Science.gov (United States)

    Waltz, James A; Brown, Jaime K; Gold, James M; Ross, Thomas J; Salmeron, Betty J; Stein, Elliot A

    2015-09-01

    It has been proposed that both positive and negative symptoms in schizophrenia (SZ) may derive, at least in part, from a disrupted ability to accurately and flexibly represent the value of stimuli and actions. To assess relationships between dimensions of psychopathology in SZ, and the tendency to devalue food stimuli, on which subjects were fed to satiety, we administered a sensory-specific satiety (SSS) paradigm to 42 SZ patients and 44 controls. In each of 2 sessions, subjects received 16 0.7-ml squirts of each of 2 rewarding foods and 32 squirts of a control solution, using syringes. In between the 2 sessions, each subject was instructed to drink one of the foods until he/she felt "full, but not uncomfortable." At 10 regular intervals, interspersed throughout the 2 sessions, subjects rated each liquid for pleasantness, using a Likert-type scale. Mann-Whitney U-tests revealed group differences in SSS effects. Within-group tests revealed that, while controls showed an effect of satiety that was sensory specific, patients showed an effect of satiety that was not, devaluing the sated and unsated foods similarly. In SZ patients, we observed correlations between the magnitude of SSS effects and measures of both positive and negative symptoms. We argue that the ability to flexibly and rapidly update representations of the value of stimuli and actions figures critically in the ability of patients with psychotic illness to process salient events and adaptively engage in goal-directed behavior.

  2. 'Ome' on the range: update on high-altitude acclimatization/adaptation and disease.

    Science.gov (United States)

    Luo, Yongjun; Wang, Yuxiao; Lu, Hongxiang; Gao, Yuqi

    2014-11-01

    The main physiological challenge in high-altitude plateau environments is hypoxia. When people living in a plain environment migrate to the plateau, they face the threat of hypoxia. Most people can acclimatize to high altitudes; the acclimatization process mainly consists of short-term hyperventilation and long-term compensation by increased oxygen uptake, transport, and use due to increased red blood cell mass, myoglobin, and mitochondria. If individuals cannot acclimatize to high altitude, they may suffer from a high-altitude disease, such as acute mountain disease (AMS), high-altitude pulmonary edema (HAPE), high-altitude cerebral edema (HACE) or chronic mountain sickness (CMS). Because some individuals are more susceptible to high altitude diseases than others, the incidence of these high-altitude diseases is variable and cannot be predicted. Studying "omes" using genomics, proteomics, metabolomics, transcriptomics, lipidomics, immunomics, glycomics and RNomics can help us understand the factors that mediate susceptibility to high altitude illnesses. Moreover, analysis of the "omes" using a systems biology approach may provide a greater understanding of high-altitude illness pathogenesis and improve the efficiency of the diagnosis and treatment of high-altitude illnesses in the future. Below, we summarize the current literature regarding the role of "omes" in high-altitude acclimatization/adaptation and disease and discuss key research gaps to better understand the contribution of "omes" to high-altitude illness susceptibility.

  3. Funding for Adaptive Optics in the United States by the National Science Foundation 2006-2009: An Update

    CERN Document Server

    Frogel, Jay A

    2009-01-01

    In 2006 I published an article in GeminiFocus that examined funding for astronomical adaptive optics related technology and instrumentation in the United States from 1995 through mid-2006. That article concluded that based on projections then current, AO implementation on public and private telescopes in the U.S. will soon seriously lag that on the ESO VLT as measured by funds available. It called for a significant infusion of public funds for AO development and implementation so that when combined with private funds, the U.S. astronomical community as a whole would be able to take full advantage of AO systems on both public and private telescopes. In 2006 I estimated that the total amount of public (NSF) funds that would be available in 2009 for AO related non-science activities would be about $6M. This article updates the analysis done in my previous article. I show that for 2009 the funds for AO related non-science activities are about $7M in spite of the termination of the AODP program. Federal stimulus f...

  4. An LPV Adaptive Observer for Updating a Map Applied to an MAF Sensor in a Diesel Engine.

    Science.gov (United States)

    Liu, Zhiyuan; Wang, Changhui

    2015-10-23

    In this paper, a new method for mass air flow (MAF) sensor error compensation and an online updating error map (or lookup table) due to installation and aging in a diesel engine is developed. Since the MAF sensor error is dependent on the engine operating point, the error model is represented as a two-dimensional (2D) map with two inputs, fuel mass injection quantity and engine speed. Meanwhile, the 2D map representing the MAF sensor error is described as a piecewise bilinear interpolation model, which can be written as a dot product between the regression vector and parameter vector using a membership function. With the combination of the 2D map regression model and the diesel engine air path system, an LPV adaptive observer with low computational load is designed to estimate states and parameters jointly. The convergence of the proposed algorithm is proven under the conditions of persistent excitation and given inequalities. The observer is validated against the simulation data from engine software enDYNA provided by Tesis. The results demonstrate that the operating point-dependent error of the MAF sensor can be approximated acceptably by the 2D map from the proposed method.

  5. Function-valued adaptive dynamics and optimal control theory.

    Science.gov (United States)

    Parvinen, Kalle; Heino, Mikko; Dieckmann, Ulf

    2013-09-01

    In this article we further develop the theory of adaptive dynamics of function-valued traits. Previous work has concentrated on models for which invasion fitness can be written as an integral in which the integrand for each argument value is a function of the strategy value at that argument value only. For this type of models of direct effect, singular strategies can be found using the calculus of variations, with singular strategies needing to satisfy Euler's equation with environmental feedback. In a broader, more mechanistically oriented class of models, the function-valued strategy affects a process described by differential equations, and fitness can be expressed as an integral in which the integrand for each argument value depends both on the strategy and on process variables at that argument value. In general, the calculus of variations cannot help analyzing this much broader class of models. Here we explain how to find singular strategies in this class of process-mediated models using optimal control theory. In particular, we show that singular strategies need to satisfy Pontryagin's maximum principle with environmental feedback. We demonstrate the utility of this approach by studying the evolution of strategies determining seasonal flowering schedules.

  6. A dynamically adaptive lattice Boltzmann method for thermal convection problems

    Directory of Open Access Journals (Sweden)

    Feldhusen Kai

    2016-12-01

    Full Text Available Utilizing the Boussinesq approximation, a double-population incompressible thermal lattice Boltzmann method (LBM for forced and natural convection in two and three space dimensions is developed and validated. A block-structured dynamic adaptive mesh refinement (AMR procedure tailored for the LBM is applied to enable computationally efficient simulations of moderate to high Rayleigh number flows which are characterized by a large scale disparity in boundary layers and free stream flow. As test cases, the analytically accessible problem of a two-dimensional (2D forced convection flow through two porous plates and the non-Cartesian configuration of a heated rotating cylinder are considered. The objective of the latter is to advance the boundary conditions for an accurate treatment of curved boundaries and to demonstrate the effect on the solution. The effectiveness of the overall approach is demonstrated for the natural convection benchmark of a 2D cavity with differentially heated walls at Rayleigh numbers from 103 up to 108. To demonstrate the benefit of the employed AMR procedure for three-dimensional (3D problems, results from the natural convection in a cubic cavity at Rayleigh numbers from 103 up to 105 are compared with benchmark results.

  7. Plant toxicity, adaptive herbivory, and plant community dynamics

    Science.gov (United States)

    Feng, Z.; Liu, R.; DeAngelis, D.L.; Bryant, J.P.; Kielland, K.; Stuart, Chapin F.; Swihart, R.K.

    2009-01-01

    We model effects of interspecific plant competition, herbivory, and a plant's toxic defenses against herbivores on vegetation dynamics. The model predicts that, when a generalist herbivore feeds in the absence of plant toxins, adaptive foraging generally increases the probability of coexistence of plant species populations, because the herbivore switches more of its effort to whichever plant species is more common and accessible. In contrast, toxin-determined selective herbivory can drive plant succession toward dominance by the more toxic species, as previously documented in boreal forests and prairies. When the toxin concentrations in different plant species are similar, but species have different toxins with nonadditive effects, herbivores tend to diversify foraging efforts to avoid high intakes of any one toxin. This diversification leads the herbivore to focus more feeding on the less common plant species. Thus, uncommon plants may experience depensatory mortality from herbivory, reducing local species diversity. The depensatory effect of herbivory may inhibit the invasion of other plant species that are more palatable or have different toxins. These predictions were tested and confirmed in the Alaskan boreal forest. ?? 2009 Springer Science+Business Media, LLC.

  8. The Intrinsic Cause-Effect Power of Discrete Dynamical Systems—From Elementary Cellular Automata to Adapting Animats

    Directory of Open Access Journals (Sweden)

    Larissa Albantakis

    2015-07-01

    Full Text Available Current approaches to characterize the complexity of dynamical systems usually rely on state-space trajectories. In this article instead we focus on causal structure, treating discrete dynamical systems as directed causal graphs—systems of elements implementing local update functions. This allows us to characterize the system’s intrinsic cause-effect structure by applying the mathematical and conceptual tools developed within the framework of integrated information theory (IIT. In particular, we assess the number of irreducible mechanisms (concepts and the total amount of integrated conceptual information Φ specified by a system. We analyze: (i elementary cellular automata (ECA; and (ii small, adaptive logic-gate networks (“animats”, similar to ECA in structure but evolving by interacting with an environment. We show that, in general, an integrated cause-effect structure with many concepts and high Φ is likely to have high dynamical complexity. Importantly, while a dynamical analysis describes what is “happening” in a system from the extrinsic perspective of an observer, the analysis of its cause-effect structure reveals what a system “is” from its own intrinsic perspective, exposing its dynamical and evolutionary potential under many different scenarios.

  9. Adaptive Stabilization for a Class of Dynamical Systems with Nonlinear Delayed State Perturbations

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    The problem of adaptive stabilization for a class of systems with nonlinear delayed state perturbations is considered. The bound of the perturbations is assumed to be unknown, by using the adaptive control method, an adaptive controller is designed. Based on the Lyapunov- Karasovskii functional, it is shown that the dynamical system can be stabilized by the adaptive controller. The effectiveness of the proposed controller is demonstrated by some simulations.

  10. Dynamic range adaptation to sound level statistics in the auditory nerve.

    Science.gov (United States)

    Wen, Bo; Wang, Grace I; Dean, Isabel; Delgutte, Bertrand

    2009-11-04

    The auditory system operates over a vast range of sound pressure levels (100-120 dB) with nearly constant discrimination ability across most of the range, well exceeding the dynamic range of most auditory neurons (20-40 dB). Dean et al. (2005) have reported that the dynamic range of midbrain auditory neurons adapts to the distribution of sound levels in a continuous, dynamic stimulus by shifting toward the most frequently occurring level. Here, we show that dynamic range adaptation, distinct from classic firing rate adaptation, also occurs in primary auditory neurons in anesthetized cats for tone and noise stimuli. Specifically, the range of sound levels over which firing rates of auditory nerve (AN) fibers grows rapidly with level shifts nearly linearly with the most probable levels in a dynamic sound stimulus. This dynamic range adaptation was observed for fibers with all characteristic frequencies and spontaneous discharge rates. As in the midbrain, dynamic range adaptation improved the precision of level coding by the AN fiber population for the prevailing sound levels in the stimulus. However, dynamic range adaptation in the AN was weaker than in the midbrain and not sufficient (0.25 dB/dB, on average, for broadband noise) to prevent a significant degradation of the precision of level coding by the AN population above 60 dB SPL. These findings suggest that adaptive processing of sound levels first occurs in the auditory periphery and is enhanced along the auditory pathway.

  11. Hamiltonian-Driven Adaptive Dynamic Programming for Continuous Nonlinear Dynamical Systems.

    Science.gov (United States)

    Yang, Yongliang; Wunsch, Donald; Yin, Yixin

    2017-02-01

    This paper presents a Hamiltonian-driven framework of adaptive dynamic programming (ADP) for continuous time nonlinear systems, which consists of evaluation of an admissible control, comparison between two different admissible policies with respect to the corresponding the performance function, and the performance improvement of an admissible control. It is showed that the Hamiltonian can serve as the temporal difference for continuous-time systems. In the Hamiltonian-driven ADP, the critic network is trained to output the value gradient. Then, the inner product between the critic and the system dynamics produces the value derivative. Under some conditions, the minimization of the Hamiltonian functional is equivalent to the value function approximation. An iterative algorithm starting from an arbitrary admissible control is presented for the optimal control approximation with its convergence proof. The implementation is accomplished by a neural network approximation. Two simulation studies demonstrate the effectiveness of Hamiltonian-driven ADP.

  12. Orchestrating the Dynamic Adaptation of Distributed Software With Process Technology

    Science.gov (United States)

    2004-01-01

    Scanning and Software Distribution After Auto Discovery, IBM Red Book, May 9, 2003. [35] Marimba Inc., Marimba Embedded Management - Creating Self...Updating Appliances and Devices, Marimba White Paper, Mountain View, Ca., USA, 2001, http://www.marimba.com/products/datasheets/Embedded-wp-april

  13. Updating beliefs and combining evidence in adaptive forest management under climate change: a case study of Norway spruce (Picea abies L. Karst) in the Black Forest, Germany.

    Science.gov (United States)

    Yousefpour, Rasoul; Temperli, Christian; Bugmann, Harald; Elkin, Che; Hanewinkel, Marc; Meilby, Henrik; Jacobsen, Jette Bredahl; Thorsen, Bo Jellesmark

    2013-06-15

    We study climate uncertainty and how managers' beliefs about climate change develop and influence their decisions. We develop an approach for updating knowledge and beliefs based on the observation of forest and climate variables and illustrate its application for the adaptive management of an even-aged Norway spruce (Picea abies L. Karst) forest in the Black Forest, Germany. We simulated forest development under a range of climate change scenarios and forest management alternatives. Our analysis used Bayesian updating and Dempster's rule of combination to simulate how observations of climate and forest variables may influence a decision maker's beliefs about climate development and thereby management decisions. While forest managers may be inclined to rely on observed forest variables to infer climate change and impacts, we found that observation of climate state, e.g. temperature or precipitation is superior for updating beliefs and supporting decision-making. However, with little conflict among information sources, the strongest evidence would be offered by a combination of at least two informative variables, e.g., temperature and precipitation. The success of adaptive forest management depends on when managers switch to forward-looking management schemes. Thus, robust climate adaptation policies may depend crucially on a better understanding of what factors influence managers' belief in climate change.

  14. DMPD: Signalling adaptors used by Toll-like receptors: an update. [Dynamic Macrophage Pathway CSML Database

    Lifescience Database Archive (English)

    Full Text Available 18706831 Signalling adaptors used by Toll-like receptors: an update. Kenny EF, O'Ne...ill LA. Cytokine. 2008 Sep;43(3):342-9. Epub 2008 Aug 15. (.png) (.svg) (.html) (.csml) Show Signalling adap...tors used by Toll-like receptors: an update. PubmedID 18706831 Title Signalling adaptors used by Toll-like r

  15. Adaptive fusion of infrared and visible images in dynamic scene

    Science.gov (United States)

    Yang, Guang; Yin, Yafeng; Man, Hong; Desai, Sachi

    2011-11-01

    Multiple modalities sensor fusion has been widely employed in various surveillance and military applications. A variety of image fusion techniques including PCA, wavelet, curvelet and HSV has been proposed in recent years to improve human visual perception for object detection. One of the main challenges for visible and infrared image fusion is to automatically determine an optimal fusion strategy for different input scenes along with an acceptable computational cost. This paper, we propose a fast and adaptive feature selection based image fusion method to obtain high a contrast image from visible and infrared sensors for targets detection. At first, fuzzy c-means clustering is applied on the infrared image to highlight possible hotspot regions, which will be considered as potential targets' locations. After that, the region surrounding the target area is segmented as the background regions. Then image fusion is locally applied on the selected target and background regions by computing different linear combination of color components from registered visible and infrared images. After obtaining different fused images, histogram distributions are computed on these local fusion images as the fusion feature set. The variance ratio which is based on Linear Discriminative Analysis (LDA) measure is employed to sort the feature set and the most discriminative one is selected for the whole image fusion. As the feature selection is performed over time, the process will dynamically determine the most suitable feature for the image fusion in different scenes. Experiment is conducted on the OSU Color-Thermal database, and TNO Human Factor dataset. The fusion results indicate that our proposed method achieved a competitive performance compared with other fusion algorithms at a relatively low computational cost.

  16. An Analysis of Discourse Production and Cognitive Context Dynamism Based on Relevance-Adaptation Model

    Institute of Scientific and Technical Information of China (English)

    YANG Jing

    2014-01-01

    Taken discourse production as the research objective, it holds that discourse production is dynamic in human communi-cation. It attempts to analyze the dynamics on the basis of Relevance-adaption model from the perspective of cognitive pragmat-ics and explain the role of the context dynamics that plays in the discourse production.

  17. Body surface adaptations to boundary-layer dynamics

    NARCIS (Netherlands)

    Videler, J.J.

    1995-01-01

    Evolutionary processes have adapted nektonic animals to interact efficiently with the water that surrounds them. Not all these adaptations serve the same purpose. This paper concentrates on reduction of drag due to friction in the boundary layer close to the body surface. Mucus, compliant skins, sca

  18. Body surface adaptations to boundary-layer dynamics

    NARCIS (Netherlands)

    Videler, J.J.

    1995-01-01

    Evolutionary processes have adapted nektonic animals to interact efficiently with the water that surrounds them. Not all these adaptations serve the same purpose. This paper concentrates on reduction of drag due to friction in the boundary layer close to the body surface. Mucus, compliant skins,

  19. Dynamic Condition Response Graphs for Trustworthy Adaptive Case Management

    DEFF Research Database (Denmark)

    Mukkamala, Raghava Rao; Hildebrandt, Thomas; Slaats, Tijs

    2013-01-01

    By trustworthy adaptive case management we mean that it should be possible to adapt processes and goals at runtime while guaranteeing that no deadlocks and livelocks are introduced. We propose to support this by applying a formal declarative process model, DCR Graphs, and exemplify its operational...

  20. Evolution of taxis responses in virtual bacteria: non-adaptive dynamics.

    Directory of Open Access Journals (Sweden)

    Richard A Goldstein

    2008-05-01

    Full Text Available Bacteria are able to sense and respond to a variety of external stimuli, with responses that vary from stimuli to stimuli and from species to species. The best-understood is chemotaxis in the model organism Escherichia coli, where the dynamics and the structure of the underlying pathway are well characterised. It is not clear, however, how well this detailed knowledge applies to mechanisms mediating responses to other stimuli or to pathways in other species. Furthermore, there is increasing experimental evidence that bacteria integrate responses from different stimuli to generate a coherent taxis response. We currently lack a full understanding of the different pathway structures and dynamics and how this integration is achieved. In order to explore different pathway structures and dynamics that can underlie taxis responses in bacteria, we perform a computational simulation of the evolution of taxis. This approach starts with a population of virtual bacteria that move in a virtual environment based on the dynamics of the simple biochemical pathways they harbour. As mutations lead to changes in pathway structure and dynamics, bacteria better able to localise with favourable conditions gain a selective advantage. We find that a certain dynamics evolves consistently under different model assumptions and environments. These dynamics, which we call non-adaptive dynamics, directly couple tumbling probability of the cell to increasing stimuli. Dynamics that are adaptive under a wide range of conditions, as seen in the chemotaxis pathway of E. coli, do not evolve in these evolutionary simulations. However, we find that stimulus scarcity and fluctuations during evolution results in complex pathway dynamics that result both in adaptive and non-adaptive dynamics depending on basal stimuli levels. Further analyses of evolved pathway structures show that effective taxis dynamics can be mediated with as few as two components. The non-adaptive dynamics

  1. Efficient Large Scale Electromagnetics Simulations Using Dynamically Adapted Meshes with the Discontinuous Galerkin Method

    CERN Document Server

    Schnepp, Sascha M

    2011-01-01

    A framework for performing dynamic mesh adaptation with the discontinuous Galerkin method (DGM) is presented. Adaptations include modifications of the local mesh step size (h-adaptation) and the local degree of the approximating polynomials (p-adaptation) as well as their combination. The computation of the approximation within locally adapted elements is based on projections between finite element spaces (FES), which are shown to preserve the upper limit of the electromagnetic energy. The formulation supports high level hanging nodes and applies precomputation of surface integrals for increasing computational efficiency. A full wave simulation of electromagnetic scattering form a radar reflector demonstrates the applicability to large scale problems in three-dimensional space.

  2. Adapting the Medium: Dynamics of Intermedial Adaptation in Contemporary Japanese Popular Visual Culture

    Directory of Open Access Journals (Sweden)

    Pusztai Beáta

    2015-08-01

    Full Text Available With respect to adaptation studies, contemporary Japanese popular culture signifies a unique case, as different types of media (be those textual, auditive, visual or audio-visual are tightly intertwined through the “recycling” of successful characters and stories. As a result, a neatly woven net of intermedial adaptations has been formed - the core of this complex system being the manga-anime-live-action film “adaptational triangle.” On the one hand, the paper addresses the interplay of the various factors by which the very existence of this network is made possible, such as the distinctive cultural attitude to “originality,” the structure of the comics, animation and film industries, and finally, the role of fictitious genealogies of both traditional and contemporary media in the negotiation of national identity. On the other hand, the essay also considers some of the most significant thematic, narrative, and stylistic effects this close interconnectedness has on the individual medium. Special attention is being paid to the nascent trend of merging the adaptive medium with that of the original story (viewing adaptation as integration, apparent in contemporary manga-based live- action comedies, as the extreme case of intermedial adaptation. That is, when the aim of the adaptational process is no longer the transposition of the story but the adaptation (i.e. the incorporation of the medium itself- elevating certain medium-specific devices into transmedial phenomena.

  3. Adaptive financial networks with static and dynamic thresholds

    CERN Document Server

    Qiu, Tian; Chen, Guang

    2010-01-01

    Based on the daily data of American and Chinese stock markets, the dynamic behavior of a financial network with static and dynamic thresholds is investigated. Compared with the static threshold, the dynamic threshold suppresses the large fluctuation induced by the cross-correlation of individual stock prices, and leads to a stable topological structure in the dynamic evolution. Long-range time-correlations are revealed for the average clustering coefficient, average degree and cross-correlation of degrees. The dynamic network shows a two-peak behavior in the degree distribution.

  4. Adaptive Neural Network Dynamic Surface Control for a Class of Time-Delay Nonlinear Systems With Hysteresis Inputs and Dynamic Uncertainties.

    Science.gov (United States)

    Zhang, Xiuyu; Su, Chun-Yi; Lin, Yan; Ma, Lianwei; Wang, Jianguo

    2015-11-01

    In this paper, an adaptive neural network (NN) dynamic surface control is proposed for a class of time-delay nonlinear systems with dynamic uncertainties and unknown hysteresis. The main advantages of the developed scheme are: 1) NNs are utilized to approximately describe nonlinearities and unknown dynamics of the nonlinear time-delay systems, making it possible to deal with unknown nonlinear uncertain systems and pursue the L∞ performance of the tracking error; 2) using the finite covering lemma together with the NNs approximators, the Krasovskii function is abandoned, which paves the way for obtaining the L∞ performance of the tracking error; 3) by introducing an initializing technique, the L∞ performance of the tracking error can be achieved; 4) using a generalized Prandtl-Ishlinskii (PI) model, the limitation of the traditional PI hysteresis model is overcome; and 5) by applying the Young's inequalities to deal with the weight vector of the NNs, the updated laws are needed only at the last controller design step with only two parameters being estimated, which reduces the computational burden. It is proved that the proposed scheme can guarantee semiglobal stability of the closed-loop system and achieves the L∞ performance of the tracking error. Simulation results for general second-order time-delay nonlinear systems and the tuning metal cutting system are presented to demonstrate the efficiency of the proposed method.

  5. Dynamic Condition Response Graphs for Trustworthy Adaptive Case Management

    DEFF Research Database (Denmark)

    Mukkamala, Raghava Rao; Hildebrandt, Thomas; Slaats, Tijs

    2013-01-01

    By trustworthy adaptive case management we mean that it should be possible to adapt processes and goals at runtime while guaranteeing that no deadlocks and livelocks are introduced. We propose to support this by applying a formal declarative process model, DCR Graphs, and exemplify its operational...... specified either as linear time logic (LTL) or DCR Graphs, extend the language with time and data and offer extended support for cross-organizational case management systems....

  6. Adaptive methods in computational fluid dynamics of chemically reacting flows

    Science.gov (United States)

    Rogg, B.

    1991-09-01

    Possible approaches to fully implicit adaptive algorithms suitable for the numerical simulation of unsteady two-dimensional reactive flows are examined. Emphasis is placed on self-adaptive gridding procedures applicable to time-dependent two-dimensional reactive flows. Pulsating flame propagation, autoignition in a nonpremixed flow, flame propagation in a strained mixing layer, and hot-spot-like self-ignition are considered as examples.

  7. Common dynamical features of sensory adaptation in photoreceptors and olfactory sensory neurons

    OpenAIRE

    Giovanna De Palo; Giuseppe Facchetti; Monica Mazzolini; Anna Menini; Vincent Torre; Claudio Altafini

    2013-01-01

    Sensory systems adapt, i.e., they adjust their sensitivity to external stimuli according to the ambient level. In this paper we show that single cell electrophysiological responses of vertebrate olfactory receptors and of photoreceptors to different input protocols exhibit several common features related to adaptation, and that these features can be used to investigate the dynamical structure of the feedback regulation responsible for the adaptation. In particular, we point out that two diffe...

  8. Adaptive chaos control and synchronization for uncertain new chaotic dynamical system

    Energy Technology Data Exchange (ETDEWEB)

    Yassen, M.T. [Mathematics Department, Faculty of Science, Mansoura University, Mansoura 35516 (Egypt)]. E-mail: mtyassen@yahoo.com

    2006-01-30

    This Letter presents the adaptive control and synchronization problems for uncertain new chaotic dynamical system (Liu system). Based on Lyapunov stability theory, adaptive control law is derived such that the trajectory of Liu system with unknown parameters is globally stabilized to each unstable equilibrium point of the uncontrolled system. In addition, an adaptive control approach is proposed to make the states of two identical Liu systems with unknown parameters asymptotically synchronized. Numerical simulations are shown to verify the results.

  9. Dynamic adaptive policy pathways: a new method for crafting robust decisions for a deeply uncertain world

    OpenAIRE

    2013-01-01

    A new paradigm for planning under conditions of deep uncertainty has emerged in the literature. According to this paradigm, a planner should create a strategic vision of the future, commit to short-term actions, and establish a framework to guide future actions. A plan that embodies these ideas allows for its dynamic adaptation over time to meet changing circumstances. We propose a method for decisionmaking under uncertain global and regional changes called ‘Dynamic Adaptive Policy Pathways’....

  10. Catalysis of Protein Folding by Chaperones Accelerates Evolutionary Dynamics in Adapting Cell Populations

    OpenAIRE

    Murat Cetinbaş; Shakhnovich, Eugene I.

    2013-01-01

    Although molecular chaperones are essential components of protein homeostatic machinery, their mechanism of action and impact on adaptation and evolutionary dynamics remain controversial. Here we developed a physics-based ab initio multi-scale model of a living cell for population dynamics simulations to elucidate the effect of chaperones on adaptive evolution. The 6-loci genomes of model cells encode model proteins, whose folding and interactions in cellular milieu can be evaluated exactly f...

  11. Dynamic adaptation of tendon and muscle connective tissue to mechanical loading

    DEFF Research Database (Denmark)

    Mackey, Abigail; Heinemeier, Katja Maria; Koskinen, Satu Osmi Anneli

    2008-01-01

    The connective tissue of tendon and skeletal muscle is a crucial structure for force transmission. A dynamic adaptive capacity of these tissues in healthy individuals is evident from reports of altered gene expression and protein levels of the fibrillar and network-forming collagens, when subjected...... in this article provide strong evidence for the highly adaptable nature of connective tissue in muscle and tendon....

  12. Adaptation to fragmentation: evolutionary dynamics driven by human influences.

    Science.gov (United States)

    Cheptou, Pierre-Olivier; Hargreaves, Anna L; Bonte, Dries; Jacquemyn, Hans

    2017-01-19

    Fragmentation-the process by which habitats are transformed into smaller patches isolated from each other-has been identified as a major threat for biodiversity. Fragmentation has well-established demographic and population genetic consequences, eroding genetic diversity and hindering gene flow among patches. However, fragmentation should also select on life history, both predictably through increased isolation, demographic stochasticity and edge effects, and more idiosyncratically via altered biotic interactions. While species have adapted to natural fragmentation, adaptation to anthropogenic fragmentation has received little attention. In this review, we address how and whether organisms might adapt to anthropogenic fragmentation. Drawing on selected case studies and evolutionary ecology models, we show that anthropogenic fragmentation can generate selection on traits at both the patch and landscape scale, and affect the adaptive potential of populations. We suggest that dispersal traits are likely to experience especially strong selection, as dispersal both enables migration among patches and increases the risk of landing in the inhospitable matrix surrounding them. We highlight that suites of associated traits are likely to evolve together. Importantly, we show that adaptation will not necessarily rescue populations from the negative effects of fragmentation, and may even exacerbate them, endangering the entire metapopulation.This article is part of the themed issue 'Human influences on evolution, and the ecological and societal consequences'. © 2016 The Author(s).

  13. Adaptive-mesh algorithms for computational fluid dynamics

    Science.gov (United States)

    Powell, Kenneth G.; Roe, Philip L.; Quirk, James

    1993-01-01

    The basic goal of adaptive-mesh algorithms is to distribute computational resources wisely by increasing the resolution of 'important' regions of the flow and decreasing the resolution of regions that are less important. While this goal is one that is worthwhile, implementing schemes that have this degree of sophistication remains more of an art than a science. In this paper, the basic pieces of adaptive-mesh algorithms are described and some of the possible ways to implement them are discussed and compared. These basic pieces are the data structure to be used, the generation of an initial mesh, the criterion to be used to adapt the mesh to the solution, and the flow-solver algorithm on the resulting mesh. Each of these is discussed, with particular emphasis on methods suitable for the computation of compressible flows.

  14. Adapt or Die

    DEFF Research Database (Denmark)

    Brody, Joshua Eric; Larsen, Kasper Green

    2015-01-01

    In this paper, we study the role non-adaptivity plays in maintaining dynamic data structures. Roughly speaking, a data structure is non-adaptive if the memory locations it reads and/or writes when processing a query or update depend only on the query or update and not on the contents of previously...... read cells. We study such non-adaptive data structures in the cell probe model. This model is one of the least restrictive lower bound models and in particular, cell probe lower bounds apply to data structures developed in the popular word-RAM model. Unfortunately, this generality comes at a high cost......: the highest lower bound proved for any data structure problem is only polylogarithmic. Our main result is to demonstrate that one can in fact obtain polynomial cell probe lower bounds for non-adaptive data structures. To shed more light on the seemingly inherent polylogarithmic lower bound barrier, we study...

  15. Phase transition in a one-dimensional Ising ferromagnet at zero temperature using Glauber dynamics with a synchronous updating mode.

    Science.gov (United States)

    Sznajd-Weron, Katarzyna

    2010-09-01

    In the past decade low-temperature Glauber dynamics for the one-dimensional Ising system has been several times observed experimentally and occurred to be one of the most important theoretical approaches in a field of molecular nanomagnets. On the other hand, it has been shown recently that Glauber dynamics with the Metropolis flipping probability for the zero-temperature Ising ferromagnet under synchronous updating can lead surprisingly to the antiferromagnetic steady state. In this paper the generalized class of Glauber dynamics at zero temperature will be considered and the relaxation into the ground state, after a quench from high temperature, will be investigated. Using Monte Carlo simulations and a mean field approach, discontinuous phase transition between ferromagnetic and antiferromagnetic phases for a one-dimensional ferromagnet will be shown.

  16. Vertical Scan (V-SCAN) for 3-D Grid Adaptive Mesh Refinement for an atmospheric Model Dynamical Core

    Science.gov (United States)

    Andronova, N. G.; Vandenberg, D.; Oehmke, R.; Stout, Q. F.; Penner, J. E.

    2009-12-01

    One of the major building blocks of a rigorous representation of cloud evolution in global atmospheric models is a parallel adaptive grid MPI-based communication library (an Adaptive Blocks for Locally Cartesian Topologies library -- ABLCarT), which manages the block-structured data layout, handles ghost cell updates among neighboring blocks and splits a block as refinements occur. The library has several modules that provide a layer of abstraction for adaptive refinement: blocks, which contain individual cells of user data; shells - the global geometry for the problem, including a sphere, reduced sphere, and now a 3D sphere; a load balancer for placement of blocks onto processors; and a communication support layer which encapsulates all data movement. A major performance concern with adaptive mesh refinement is how to represent calculations that have need to be sequenced in a particular order in a direction, such as calculating integrals along a specific path (e.g. atmospheric pressure or geopotential in the vertical dimension). This concern is compounded if the blocks have varying levels of refinement, or are scattered across different processors, as can be the case in parallel computing. In this paper we describe an implementation in ABLCarT of a vertical scan operation, which allows computing along vertical paths in the correct order across blocks transparent to their resolution and processor location. We test this functionality on a 2D and a 3D advection problem, which tests the performance of the model’s dynamics (transport) and physics (sources and sinks) for different model resolutions needed for inclusion of cloud formation.

  17. Adaptive dynamic surface control of flexible-joint robots using self-recurrent wavelet neural networks.

    Science.gov (United States)

    Yoo, Sung Jin; Park, Jin Bae; Choi, Yoon Ho

    2006-12-01

    A new method for the robust control of flexible-joint (FJ) robots with model uncertainties in both robot dynamics and actuator dynamics is proposed. The proposed control system is a combination of the adaptive dynamic surface control (DSC) technique and the self-recurrent wavelet neural network (SRWNN). The adaptive DSC technique provides the ability to overcome the "explosion of complexity" problem in backstepping controllers. The SRWNNs are used to observe the arbitrary model uncertainties of FJ robots, and all their weights are trained online. From the Lyapunov stability analysis, their adaptation laws are induced, and the uniformly ultimately boundedness of all signals in a closed-loop adaptive system is proved. Finally, simulation results for a three-link FJ robot are utilized to validate the good position tracking performance and robustness against payload uncertainties and external disturbances of the proposed control system.

  18. An extension of the classification of evolutionary singular strategies in Adaptive Dynamics

    NARCIS (Netherlands)

    Boldin, Barbara; Diekmann, Odo

    2014-01-01

    The existing classification of evolutionarily singular strategies in Adaptive Dynamics (Geritz et al. in Evol Ecol 12:35–57, 1998; Metz et al. in Stochastic and spatial structures of dynamical systems, pp 183–231, 1996) assumes an invasion exponent that is differentiable twice as a function of both

  19. Chemical process dynamic optimization based on the differential evolution algorithm with an adaptive scheduling mutation strategy

    Science.gov (United States)

    Zhu, Jun; Yan, Xuefeng; Zhao, Weixiang

    2013-10-01

    To solve chemical process dynamic optimization problems, a differential evolution algorithm integrated with adaptive scheduling mutation strategy (ASDE) is proposed. According to the evolution feedback information, ASDE, with adaptive control parameters, adopts the round-robin scheduling algorithm to adaptively schedule different mutation strategies. By employing an adaptive mutation strategy and control parameters, the real-time optimal control parameters and mutation strategy are obtained to improve the optimization performance. The performance of ASDE is evaluated using a suite of 14 benchmark functions. The results demonstrate that ASDE performs better than four conventional differential evolution (DE) algorithm variants with different mutation strategies, and that the whole performance of ASDE is equivalent to a self-adaptive DE algorithm variant and better than five conventional DE algorithm variants. Furthermore, ASDE was applied to solve a typical dynamic optimization problem of a chemical process. The obtained results indicate that ASDE is a feasible and competitive optimizer for this kind of problem.

  20. Adaptation Algorithm of Geometric Graphs for Robot Motion Planning in Dynamic Environments

    Directory of Open Access Journals (Sweden)

    Jae-Han Park

    2016-01-01

    Full Text Available This study proposes an adaptive graph algorithm for collision-free motion planning of articulated robots in dynamic environments. For this purpose, deformations of the configuration space were analyzed according to the changes of the workspace using various simulations. Subsequently, we adopted the principles of gas motion dynamics in our adaptation algorithm to address the issue of the deformation of the configuration space. The proposed algorithm has an adaptation mechanism based on expansive repulsion and sensory repulsion, and it can be performed to provide the entire adaptation using distributed processing. The simulation results confirmed that the proposed method allows the adaptation of the roadmap graph to changes of the configuration space.

  1. Nonlinear System Design: Adaptive Feedback Linearization with Unmodeled Dynamics

    Science.gov (United States)

    1991-09-30

    First, we address severe restrictions of the two currently available types of the regulation problem . In Section 11 we characterize the schemes: the...existence of such a Lyapunov II. THE CLASS OF NONLINEAR SYSTEMS function cannot be aserned a priori. fa . The adaptive regulation problem will first be

  2. Advanced Dynamically Adaptive Algorithms for Stochastic Simulations on Extreme Scales

    Energy Technology Data Exchange (ETDEWEB)

    Xiu, Dongbin [Univ. of Utah, Salt Lake City, UT (United States)

    2017-03-03

    The focus of the project is the development of mathematical methods and high-performance computational tools for stochastic simulations, with a particular emphasis on computations on extreme scales. The core of the project revolves around the design of highly efficient and scalable numerical algorithms that can adaptively and accurately, in high dimensional spaces, resolve stochastic problems with limited smoothness, even containing discontinuities.

  3. Dynamics of dual prism adaptation: relating novel experimental results to a minimalistic neural model.

    Directory of Open Access Journals (Sweden)

    Orlando Arévalo

    Full Text Available In everyday life, humans interact with a dynamic environment often requiring rapid adaptation of visual perception and motor control. In particular, new visuo-motor mappings must be learned while old skills have to be kept, such that after adaptation, subjects may be able to quickly change between two different modes of generating movements ('dual-adaptation'. A fundamental question is how the adaptation schedule determines the acquisition speed of new skills. Given a fixed number of movements in two different environments, will dual-adaptation be faster if switches ('phase changes' between the environments occur more frequently? We investigated the dynamics of dual-adaptation under different training schedules in a virtual pointing experiment. Surprisingly, we found that acquisition speed of dual visuo-motor mappings in a pointing task is largely independent of the number of phase changes. Next, we studied the neuronal mechanisms underlying this result and other key phenomena of dual-adaptation by relating model simulations to experimental data. We propose a simple and yet biologically plausible neural model consisting of a spatial mapping from an input layer to a pointing angle which is subjected to a global gain modulation. Adaptation is performed by reinforcement learning on the model parameters. Despite its simplicity, the model provides a unifying account for a broad range of experimental data: It quantitatively reproduced the learning rates in dual-adaptation experiments for both direct effect, i.e. adaptation to prisms, and aftereffect, i.e. behavior after removal of prisms, and their independence on the number of phase changes. Several other phenomena, e.g. initial pointing errors that are far smaller than the induced optical shift, were also captured. Moreover, the underlying mechanisms, a local adaptation of a spatial mapping and a global adaptation of a gain factor, explained asymmetric spatial transfer and generalization of prism

  4. Adaptive global synchronization of a general complex dynamical network with non-delayed and delayed coupling

    Science.gov (United States)

    Wen, Sun; Chen, Shihua; Guo, Wanli

    2008-10-01

    This Letter investigates the global synchronization of a general complex dynamical network with non-delayed and delayed coupling. Based on Lasalle's invariance principle, adaptive global synchronization criteria is obtained. Analytical result shows that under the designed adaptive controllers, a general complex dynamical network with non-delayed and delayed coupling can globally asymptotically synchronize to a given trajectory. What is more, the node dynamic need not satisfy the very strong and conservative uniformly Lipschitz condition and the coupling matrix is not assumed to be symmetric or irreducible. Finally, numerical simulations are presented to verify the effectiveness of the proposed synchronization criteria.

  5. Adaptive global synchronization of a general complex dynamical network with non-delayed and delayed coupling

    Energy Technology Data Exchange (ETDEWEB)

    Wen Sun [College of Mathematics and Statistics, Wuhan University, Wuhan 430072 (China)], E-mail: sunwen_2201@163.com; Chen Shihua; Guo Wanli [College of Mathematics and Statistics, Wuhan University, Wuhan 430072 (China)

    2008-10-13

    This Letter investigates the global synchronization of a general complex dynamical network with non-delayed and delayed coupling. Based on Lasalle's invariance principle, adaptive global synchronization criteria is obtained. Analytical result shows that under the designed adaptive controllers, a general complex dynamical network with non-delayed and delayed coupling can globally asymptotically synchronize to a given trajectory. What is more, the node dynamic need not satisfy the very strong and conservative uniformly Lipschitz condition and the coupling matrix is not assumed to be symmetric or irreducible. Finally, numerical simulations are presented to verify the effectiveness of the proposed synchronization criteria.

  6. Quantitative adaptation analytics for assessing dynamic systems of systems: LDRD Final Report

    Energy Technology Data Exchange (ETDEWEB)

    Gauthier, John H. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). System Readiness & Sustainment Technologies (6133, M/S 1188); Miner, Nadine E. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Military & Energy Systems Analysis (6114, M/S 1188); Wilson, Michael L. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Resilience and Regulatory Effects (6921, M/S 1138); Le, Hai D. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). System Readiness & Sustainment Technologies (6133, M/S 1188); Kao, Gio K. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Networked System Survivability & Assurance (5629, M/S 0671); Melander, Darryl J. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Software Systems R& D (9525, M/S 1188); Longsine, Dennis Earl [Sandia National Laboratories, Unknown, Unknown; Vander Meer, Jr., Robert C. [SAIC, Inc., Albuquerque, NM (United States)

    2015-01-01

    Our society is increasingly reliant on systems and interoperating collections of systems, known as systems of systems (SoS). These SoS are often subject to changing missions (e.g., nation- building, arms-control treaties), threats (e.g., asymmetric warfare, terrorism), natural environments (e.g., climate, weather, natural disasters) and budgets. How well can SoS adapt to these types of dynamic conditions? This report details the results of a three year Laboratory Directed Research and Development (LDRD) project aimed at developing metrics and methodologies for quantifying the adaptability of systems and SoS. Work products include: derivation of a set of adaptability metrics, a method for combining the metrics into a system of systems adaptability index (SoSAI) used to compare adaptability of SoS designs, development of a prototype dynamic SoS (proto-dSoS) simulation environment which provides the ability to investigate the validity of the adaptability metric set, and two test cases that evaluate the usefulness of a subset of the adaptability metrics and SoSAI for distinguishing good from poor adaptability in a SoS. Intellectual property results include three patents pending: A Method For Quantifying Relative System Adaptability, Method for Evaluating System Performance, and A Method for Determining Systems Re-Tasking.

  7. Global Network Reorganization During Dynamic Adaptations of Bacillus subtilis Metabolism

    National Research Council Canada - National Science Library

    Buescher, Joerg Martin; Liebermeister, Wolfram; Jules, Matthieu; Uhr, Markus; Muntel, Jan; Botella, Eric; Hessling, Bernd; Kleijn, Roelco Jacobus; Le Chat, Ludovic; Lecointe, Francois; Maeder, Ulrike; Nicolas, Pierre; Piersma, Sjouke; Ruegheimer, Frank; Becher, Doerte; Bessieres, Philippe; Bidnenko, Elena; Denham, Emma L; Dervyn, Etienne; Devine, Kevin M; Doherty, Geoff; lhe, Samuel; Felicori, Liza; Fogg, Mark J; Goelzer, Anne; Hansen, Annette; Harwood, Colin R; Hecker, Michael; Hubner, Sebastian; Hultschig, Claus; Jarmer, Hanne; Klipp, Edda; Leduc, Aurelie; Lewis, Peter; Molina, Frank; Noirot, Philippe; Peres, Sabine; Pigeonneau, Nathalie; Pohl, Susanne; Rasmussen, Simon; Rinn, Bernd; Schaffer, Marc; Schnidder, Julian; Schwikowski, Benno; Van Dijl, Jan Maarten; Veiga, Patrick; Walsh, Sean; Wilkinson, Anthony J; Stelling, Joerg; Aymerich, Stephane; Sauer, Uwe

    2012-01-01

    .... For nutritional shifts between two preferred carbon sources of Bacillus subtilis, we combined statistical and model-based data analyses of dynamic transcript, protein, and metabolite abundances and promoter activities...

  8. Macroscopic description of complex adaptive networks co-evolving with dynamic node states

    CERN Document Server

    Wiedermann, Marc; Heitzig, Jobst; Lucht, Wolfgang; Kurths, Jürgen

    2015-01-01

    In many real-world complex systems, the time-evolution of the network's structure and the dynamic state of its nodes are closely entangled. Here, we study opinion formation and imitation on an adaptive complex network which is dependent on the individual dynamic state of each node and vice versa to model the co-evolution of renewable resources with the dynamics of harvesting agents on a social network. The adaptive voter model is coupled to a set of identical logistic growth models and we show that in such systems, the rate of interactions between nodes as well as the adaptive rewiring probability play a crucial role for the sustainability of the system's equilibrium state. We derive a macroscopic description of the system which provides a general framework to model and quantify the influence of single node dynamics on the macroscopic state of the network and is applicable to many fields of study, such as epidemic spreading or social modeling.

  9. Thermal adaptation of conformational dynamics in ribonuclease H.

    Directory of Open Access Journals (Sweden)

    Kate A Stafford

    Full Text Available The relationship between inherent internal conformational processes and enzymatic activity or thermodynamic stability of proteins has proven difficult to characterize. The study of homologous proteins with differing thermostabilities offers an especially useful approach for understanding the functional aspects of conformational dynamics. In particular, ribonuclease HI (RNase H, an 18 kD globular protein that hydrolyzes the RNA strand of RNA:DNA hybrid substrates, has been extensively studied by NMR spectroscopy to characterize the differences in dynamics between homologs from the mesophilic organism E. coli and the thermophilic organism T. thermophilus. Herein, molecular dynamics simulations are reported for five homologous RNase H proteins of varying thermostabilities and enzymatic activities from organisms of markedly different preferred growth temperatures. For the E. coli and T. thermophilus proteins, strong agreement is obtained between simulated and experimental values for NMR order parameters and for dynamically averaged chemical shifts, suggesting that these simulations can be a productive platform for predicting the effects of individual amino acid residues on dynamic behavior. Analyses of the simulations reveal that a single residue differentiates between two different and otherwise conserved dynamic processes in a region of the protein known to form part of the substrate-binding interface. Additional key residues within these two categories are identified through the temperature-dependence of these conformational processes.

  10. Finite element model updating of natural fibre reinforced composite structure in structural dynamics

    Directory of Open Access Journals (Sweden)

    Sani M.S.M.

    2016-01-01

    Full Text Available Model updating is a process of making adjustment of certain parameters of finite element model in order to reduce discrepancy between analytical predictions of finite element (FE and experimental results. Finite element model updating is considered as an important field of study as practical application of finite element method often shows discrepancy to the test result. The aim of this research is to perform model updating procedure on a composite structure as well as trying improving the presumed geometrical and material properties of tested composite structure in finite element prediction. The composite structure concerned in this study is a plate of reinforced kenaf fiber with epoxy. Modal properties (natural frequency, mode shapes, and damping ratio of the kenaf fiber structure will be determined using both experimental modal analysis (EMA and finite element analysis (FEA. In EMA, modal testing will be carried out using impact hammer test while normal mode analysis using FEA will be carried out using MSC. Nastran/Patran software. Correlation of the data will be carried out before optimizing the data from FEA. Several parameters will be considered and selected for the model updating procedure.

  11. Advanced Dynamically Adaptive Algorithms for Stochastic Simulations on Extreme Scales

    Energy Technology Data Exchange (ETDEWEB)

    Xiu, Dongbin [Purdue Univ., West Lafayette, IN (United States)

    2016-06-21

    The focus of the project is the development of mathematical methods and high-performance com- putational tools for stochastic simulations, with a particular emphasis on computations on extreme scales. The core of the project revolves around the design of highly e cient and scalable numer- ical algorithms that can adaptively and accurately, in high dimensional spaces, resolve stochastic problems with limited smoothness, even containing discontinuities.

  12. A Dynamically Adaptive Arbitrary Lagrangian-Eulerian Method for Hydrodynamics

    Energy Technology Data Exchange (ETDEWEB)

    Anderson, R W; Pember, R B; Elliott, N S

    2002-10-19

    A new method that combines staggered grid Arbitrary Lagrangian-Eulerian (ALE) techniques with structured local adaptive mesh refinement (AMR) has been developed for solution of the Euler equations. The novel components of the combined ALE-AMR method hinge upon the integration of traditional AMR techniques with both staggered grid Lagrangian operators as well as elliptic relaxation operators on moving, deforming mesh hierarchies. Numerical examples demonstrate the utility of the method in performing detailed three-dimensional shock-driven instability calculations.

  13. A Dynamically Adaptive Arbitrary Lagrangian-Eulerian Method for Hydrodynamics

    Energy Technology Data Exchange (ETDEWEB)

    Anderson, R W; Pember, R B; Elliott, N S

    2004-01-28

    A new method that combines staggered grid Arbitrary Lagrangian-Eulerian (ALE) techniques with structured local adaptive mesh refinement (AMR) has been developed for solution of the Euler equations. The novel components of the combined ALE-AMR method hinge upon the integration of traditional AMR techniques with both staggered grid Lagrangian operators as well as elliptic relaxation operators on moving, deforming mesh hierarchies. Numerical examples demonstrate the utility of the method in performing detailed three-dimensional shock-driven instability calculations.

  14. What to change and what to keep? Values and dynamics of adaptation to climate change

    Directory of Open Access Journals (Sweden)

    Sebastian Wessels

    2015-04-01

    Full Text Available This paper uses a complex systems theory framework to clarify what adaptation to climate change means in practice, which is to make targeted changes to a society's functioning in order to avoid changes happening to that which is of value to the members of that society. It is shown that the question what is to be changed and what to be preserved is not prescribed by the facts of climate change and technology, but a contingent one to be made by society. Discussing four important domains of adaptation and the respective narratives found in academia and politics, it is investigated how these decisions are formed, giving special consideration to the case of Germany. This leads to the finding that the generally defensive framings that characterizes common notions of adaptation reinforce predominant cultural paradigms and social dynamics that arguably have contributed considerably to the need for adaptation to climate change in the first place and will most likely create further need for adaptation in the future. A paradoxical tendency to accelerate predominant social dynamics in attempts to keep current states of affairs unchanged is identified. It is concluded that the concept of adaptation is a regression behind the concept of sustainability which can easily accommodate adaptation needs but avoids the identified pitfalls of adaptation by its future orientation and oft-criticized openness.

  15. DYNAMIC PROGRAMMING AND ADAPTIVE PROCESSES--1: MATHEMATICAL FOUNDATION

    Science.gov (United States)

    engulf the field of operations research, and play a paramount role in the current theory of stochastic control processes of ejectronic and mechanical ...origin. All three of these domains merge in the consideration of the problems of communication theory. The functional equation approach of dynamic

  16. Adaptive optimal spectral range for dynamically changing scene

    Science.gov (United States)

    Pinsky, Ephi; Siman-tov, Avihay; Peles, David

    2012-06-01

    A novel multispectral video system that continuously optimizes both its spectral range channels and the exposure time of each channel autonomously, under dynamic scenes, varying from short range-clear scene to long range-poor visibility, is currently being developed. Transparency and contrast of high scattering medium of channels with spectral ranges in the near infrared is superior to the visible channels, particularly to the blue range. Longer wavelength spectral ranges that induce higher contrast are therefore favored. Images of 3 spectral channels are fused and displayed for (pseudo) color visualization, as an integrated high contrast video stream. In addition to the dynamic optimization of the spectral channels, optimal real-time exposure time is adjusted simultaneously and autonomously for each channel. A criterion of maximum average signal, derived dynamically from previous frames of the video stream is used (Patent Application - International Publication Number: WO2009/093110 A2, 30.07.2009). This configuration enables dynamic compatibility with the optimal exposure time of a dynamically changing scene. It also maximizes the signal to noise ratio and compensates each channel for the specified value of daylight reflections and sensors response for each spectral range. A possible implementation is a color video camera based on 4 synchronized, highly responsive, CCD imaging detectors, attached to a 4CCD dichroic prism and combined with a common, color corrected, lens. Principal Components Analysis (PCA) technique is then applied for real time "dimensional collapse" in color space, in order to select and fuse, for clear color visualization, the 3 most significant principal channels out of at least 4 characterized by high contrast and rich details in the image data.

  17. Context-aware adaptation for group communication support applications with dynamic architecture

    CERN Document Server

    Rodriguez, Ismael Bouassida; Chassot, Christophe; Jmaiel, Mohamed

    2008-01-01

    In this paper, we propose a refinement-based adaptation approach for the architecture of distributed group communication support applications. Unlike most of previous works, our approach reaches implementable, context-aware and dynamically adaptable architectures. To model the context, we manage simultaneously four parameters that influence Qos provided by the application. These parameters are: the available bandwidth, the exchanged data communication priority, the energy level and the available memory for processing. These parameters make it possible to refine the choice between the various architectural configurations when passing from a given abstraction level to the lower level which implements it. Our approach allows the importance degree associated with each parameter to be adapted dynamically. To implement adaptation, we switch between the various configurations of the same level, and we modify the state of the entities of a given configuration when necessary. We adopt the direct and mediated Producer-...

  18. Investigation of passive and adaptive passive dynamic absorbers applied to an automatic washer suspension design

    Science.gov (United States)

    Aldrin, John C.; Conrad, Daniel C.; Soedel, Werner

    1996-05-01

    Alternative vibration control systems are of interest to the appliance industry to improve the performance of the automatic washer suspension. Consumer benefits from improved suspension performance include noise and vibration reduction, lighter machines and larger baskets for increased clothes load capacity. Passive dynamic absorbers are investigated because of their ability to control system resonances and absorb energy from vibrating components. Since the suspended mass is variable due to different clothes loads and the amount of water in the clothes, performance limitations exist for the passive vibration absorber. Adaptive passive dynamic absorbers are investigated as an alternative vibration control system. A set of design variables and constraints for a fundamental model of an automatic washer suspension incorporating both passive and adaptive passive dynamic absorbers is presented. Numerical integration is used to obtain each system response. Optimization of the fundamental automatic washer model incorporating a passive dynamic absorber is performed. Design of experiment techniques and general design studies are used to gain information concerning the importance of the design variables on the performance of the adaptive passive dynamic absorber. Both ideal and real absorber stiffness controller schemes are investigated. The results suggest some benefit of applying adaptive passive dynamic absorbers. Design constraints are found to play a major role in the feasibility of application of this technology to the appliance industry. When considering design cost and performance, the optimum passive dynamic absorber is shown to be the better choice. Examples of various methods of implementation of both passive and adaptive passive dynamic absorbers to an automatic washer are presented.

  19. KEY UPDATION FOR THE DYNAMIC ATTRIBUTES IN CLOUD COMPUTING FOR COMPETENT USER RETRACTION

    Directory of Open Access Journals (Sweden)

    ELAVARASI.P

    2013-06-01

    Full Text Available Companies are into the cloud and provide services on it. The increasing popularity of cloud computing draws attention to its security challenges, which are particularly worsen due to resource sharing. This technology is prone to security threats because of which the users want to trust their precious data. Several schemes are employed for access control of outsourced data. So, Hierarchical Attribute Set Based Encryption, an extension of Ciphertext policy attribute set- based encryption, has been proposed for its fine grained access control with hierarchical structure of users. The user’s secret key is determined by the attributes. The attributes will often be updated in the real world scenario. So, efficient method for updating the key for the changing attributes with user revocation is proposed in this paper.

  20. Robust adaptive synchronization of general dynamical networks with multiple delays and uncertainties

    Indian Academy of Sciences (India)

    LU YIMING; HE PING; MA SHU-HUA; LI GUO-ZHI; MOBAYBEN SALEH

    2016-06-01

    In this article, a general complex dynamical network which contains multiple delays and uncertainties is introduced, which contains time-varying coupling delays, time-varying node delay, and uncertainties of both the inner- and outer-coupling matrices. A robust adaptive synchronization scheme for these general complex networks with multiple delays and uncertainties is established and raised by employing the robust adaptive control principle and the Lyapunov stability theory. We choose some suitable adaptive synchronization controllers to ensure the robust synchronization of this dynamical network. The numerical simulations of the time-delay Lorenz chaotic system as local dynamical node are provided to observe and verify the viability and productivity of the theoretical research in this paper. Compared to the achievement of previous research, theresearch in this paper seems quite comprehensive and universal.

  1. Sliding Mode Control of Dynamic Voltage Restorer by Using a New Adaptive Reaching Law

    Science.gov (United States)

    Pandey, Achala; Agrawal, Rekha; Mandloi, Ravindra S.; Sarkar, Biswaroop

    2017-08-01

    This paper presents a new kind of adaptive reaching law for sliding mode control of Dynamic Voltage Restorer (DVR). Such an adaptive reaching law follows under-damped sinusoidal nature that causes the initial state to reach the sliding regime in extremely less time with negligible chattering. Moreover, it is robust in the sense the trajectory does not deviate from the sliding surface. This new approach is developed and successfully applied to DVR. The simulation results are presented that show its robustness.

  2. A Novel Fuzzy Logic Based Adaptive Supertwisting Sliding Mode Control Algorithm for Dynamic Uncertain Systems

    OpenAIRE

    Abdul Kareem; Mohammad Fazle Azeem

    2012-01-01

    This paper presents a novel fuzzy logic based Adaptive Super-twisting Sliding Mode Controller for the control of dynamic uncertain systems. The proposed controller combines the advantages of Second order Sliding Mode Control, Fuzzy Logic Control and Adaptive Control. The reaching conditions, stability and robustness of the system with the proposed controller are guaranteed. In addition, the proposed controller is well suited for simple design and implementation. The effectiveness ...

  3. Adaptive lag synchronization based topology identification scheme of uncertain general complex dynamical networks

    Science.gov (United States)

    Che, Y.; Li, R. X.; Han, C. X.; Wang, J.; Cui, S. G.; Deng, B.; Wei, X.

    2012-08-01

    This paper presents an adaptive lag synchronization based method for simultaneous identification of topology and parameters of uncertain general complex dynamical networks with and without time delays. Based on Lyapunov stability theorem and LaSalle's invariance principle, an adaptive controller is designed to realize lag synchronization between drive and response systems, meanwhile, identification criteria of network topology and system parameters are obtained. Numerical simulations illustrate the effectiveness of the proposed method.

  4. Adaptive Neural Network Dynamic Inversion with Prescribed Performance for Aircraft Flight Control

    OpenAIRE

    Wendong Gai; Honglun Wang; Jing Zhang; Yuxia Li

    2013-01-01

    An adaptive neural network dynamic inversion with prescribed performance method is proposed for aircraft flight control. The aircraft nonlinear attitude angle model is analyzed. And we propose a new attitude angle controller design method based on prescribed performance which describes the convergence rate and overshoot of the tracking error. Then the model error is compensated by the adaptive neural network. Subsequently, the system stability is analyzed in detail. Finally, the proposed meth...

  5. Policy Gradient Adaptive Dynamic Programming for Data-Based Optimal Control.

    Science.gov (United States)

    Luo, Biao; Liu, Derong; Wu, Huai-Ning; Wang, Ding; Lewis, Frank L

    2016-11-22

    The model-free optimal control problem of general discrete-time nonlinear systems is considered in this paper, and a data-based policy gradient adaptive dynamic programming (PGADP) algorithm is developed to design an adaptive optimal controller method. By using offline and online data rather than the mathematical system model, the PGADP algorithm improves control policy with a gradient descent scheme. The convergence of the PGADP algorithm is proved by demonstrating that the constructed.

  6. Adaptive Synchronization of Complex Dynamical Networks Governed by Local Lipschitz Nonlinearlity on Switching Topology

    Directory of Open Access Journals (Sweden)

    Bo Liu

    2013-01-01

    Full Text Available This paper investigates the adaptive synchronization of complex dynamical networks satisfying the local Lipschitz condition with switching topology. Based on differential inclusion and nonsmooth analysis, it is proved that all nodes can converge to the synchronous state, even though only one node is informed by the synchronous state via introducing decentralized adaptive strategies to the coupling strengths and feedback gains. Finally, some numerical simulations are worked out to illustrate the analytical results.

  7. Dynamic Modelling and Adaptive Traction Control for Mobile Robots

    Directory of Open Access Journals (Sweden)

    A. Albagul

    2008-11-01

    Full Text Available Mobile robots have received a great deal of research in recent years. A significant amount of research has been published in many aspects related to mobile robots. Most of the research is devoted to design and develop some control techniques for robot motion and path planning. A large number of researchers have used kinematic models to develop motion control strategy for mobile robots. Their argument and assumption that these models are valid if the robot has low speed, low acceleration and light load. However, dynamic modelling of mobile robots is very important as they are designed to travel at higher speed and perform heavy duty work. This paper presents and discusses a new approach to develop a dynamic model and control strategy for wheeled mobile robot which I modelled as a rigid body that roles on two wheels and a castor. The motion control strategy consists of two levels. The first level is dealing with the dynamic of the system and denoted as `Low' level controller. The second level is developed to take care of path planning and trajectory generation.

  8. Dynamic stability of sequential stimulus representations in adapting neuronal networks

    Directory of Open Access Journals (Sweden)

    Renato Carlos Farinha Duarte

    2014-10-01

    Full Text Available The ability to acquire and maintain appropriate representations of time-varying, sequentialstimulus events is a fundamental feature of neocortical circuits and a necessary first step towardsmore specialized information processing. The dynamical properties of such representationsdepend on the current state of the circuit, which is determined primarily by the ongoing, internallygenerated activity, setting the ground state from which input-specific transformations emerge.Here, we begin by demonstrating that timing-dependent synaptic plasticity mechanisms havean important role to play in the active maintenance of an ongoing dynamics characterized byasynchronous and irregular firing, closely resembling cortical activity in vivo. Incoming stimuli,acting as perturbations of the local balance of excitation and inhibition, require fast adaptiveresponses to prevent the development of unstable activity regimes, such as those characterizedby a high degree of population-wide synchrony. We establish a link between such pathologicalnetwork activity, which is circumvented by the action of plasticity, and a reduced computationalcapacity. Additionally, we demonstrate that the action of plasticity shapes and stabilizes thetransient network states exhibited in the presence of sequentially presented stimulus events,allowing the development of adequate and discernible stimulus representations. The mainfeature responsible for the increased discriminability of stimulus-driven population responsesin plastic networks is shown to be the decorrelating action of inhibitory plasticity and theconsequent maintenance of the asynchronous irregular dynamic regime both for ongoing activityand stimulus-driven responses, whereas excitatory plasticity is shown to play only a marginalrole.

  9. Dynamic Modelling and Adaptive Traction Control for Mobile Robots

    Directory of Open Access Journals (Sweden)

    A. Albagul

    2004-09-01

    Full Text Available Mobile robots have received a great deal of research in recent years. A significant amount of research has been published in many aspects related to mobile robots. Most of the research is devoted to design and develop some control techniques for robot motion and path planning. A large number of researchers have used kinematic models to develop motion control strategy for mobile robots. Their argument and assumption that these models are valid if the robot has low speed, low acceleration and light load. However, dynamic modelling of mobile robots is very important as they are designed to travel at higher speed and perform heavy duty work. This paper presents and discusses a new approach to develop a dynamic model and control strategy for wheeled mobile robot which I modelled as a rigid body that roles on two wheels and a castor. The motion control strategy consists of two levels. The first level is dealing with the dynamic of the system and denoted as ‘Low’ level controller. The second level is developed to take care of path planning and trajectory generation.

  10. Cortical microcircuit dynamics mediating Binocular Rivalry: The role of adaptation in inhibition

    Directory of Open Access Journals (Sweden)

    Panagiota eTheodoni

    2011-11-01

    Full Text Available Perceptual bistability arises when two conflicting interpretations of an ambiguous stimulus or images in binocular rivalry (BR compete for perceptual dominance. From a computational point of view competition models based on cross-inhibition and adaptation have shown that noise is a crucial force for rivalry and operates in balance with adaptation in order to explain the observed alternations in perception. In particular, noise-driven transitions and adaptation-driven oscillations define two dynamical regimes and the system operates near its boundary. In order to gain insights into the microcircuit dynamics mediating spontaneous perceptual alternations we used a reduced recurrent attractor-based biophysically realistic spiking network well known for working memory, attention and decision-making, where a spike-frequency adaptation mechanism is implemented to account for perceptual bistability. We, thus, derived a consistently reduced four-variable population rate model using mean-field techniques and tested it on BR data collected from human subjects. Our model accounts for experimental data parameters such as time dominance, coefficient of variation and gamma distribution. In addition, we show that our model also operates on the boundary between noise and adaptation and agrees with Levelt’s second revised and fourth propositions. These results show for the first time that a consistent reduction of a biophysically realistic spiking network of integrate and fire neurons with spike frequency adaptation could account for BR. Moreover, we demonstrate that BR can be explained only through the dynamics of the competing neuronal pools, without taking into account the adaptation of inhibitory interneurons..However, adaptation of interneurons affects the optimal parametric space of the system, by decreasing the overall adaptation necessary for the bifurcation to occur.

  11. An integrated architecture of adaptive neural network control for dynamic systems

    Energy Technology Data Exchange (ETDEWEB)

    Ke, Liu; Tokar, R.; Mcvey, B.

    1994-07-01

    In this study, an integrated neural network control architecture for nonlinear dynamic systems is presented. Most of the recent emphasis in the neural network control field has no error feedback as the control input which rises the adaptation problem. The integrated architecture in this paper combines feed forward control and error feedback adaptive control using neural networks. The paper reveals the different internal functionality of these two kinds of neural network controllers for certain input styles, e.g., state feedback and error feedback. Feed forward neural network controllers with state feedback establish fixed control mappings which can not adapt when model uncertainties present. With error feedbacks, neural network controllers learn the slopes or the gains respecting to the error feedbacks, which are error driven adaptive control systems. The results demonstrate that the two kinds of control scheme can be combined to realize their individual advantages. Testing with disturbances added to the plant shows good tracking and adaptation.

  12. Adaptive Feedback Control for Chaos Control and Synchronization for New Chaotic Dynamical System

    Directory of Open Access Journals (Sweden)

    M. M. El-Dessoky

    2012-01-01

    Full Text Available This paper investigates the problem of chaos control and synchronization for new chaotic dynamical system and proposes a simple adaptive feedback control method for chaos control and synchronization under a reasonable assumption. In comparison with previous methods, the present control technique is simple both in the form of the controller and its application. Based on Lyapunov's stability theory, adaptive control law is derived such that the trajectory of the new system with unknown parameters is globally stabilized to the origin. In addition, an adaptive control approach is proposed to make the states of two identical systems with unknown parameters asymptotically synchronized. Numerical simulations are shown to verify the analytical results.

  13. Nanostructural self-organization and dynamic adaptation of metal-polymer tribosystems

    Science.gov (United States)

    Mashkov, Yu. K.

    2017-02-01

    The results of investigating the effect of nanosize modifiers of a polymer matrix on the nanostructural self-organization of polymer composites and dynamic adaptation of metal-polymer tribosystems, which considerably affect the wear resistance of polymer composite materials, have been analyzed. It has been shown that the physicochemical nanostructural self-organization processes are developed in metal-polymer tribosystems with the formation of thermotropic liquid-crystal structures of the polymer matrix, followed by the transition of the system to the stationary state with a negative feedback that ensures dynamic adaptation of the tribosystem to given operating conditions.

  14. Adaptive Feedback Linearization Control for Asynchronous Machine with Nonlinear for Natural Dynamic Complete Observer

    Science.gov (United States)

    Bentaallah, Abderrahim; Massoum, Ahmed; Benhamida, Farid; Meroufel, Abdelkader

    2012-03-01

    This paper studies the nonlinear adaptive control of an induction motor with natural dynamic complete nonlinear observer. The aim of this work is to develop a nonlinear control law and adaptive performance for an asynchronous motor with two main objectives: to improve the continuation of trajectories and the stability, robustness to parametric variations and disturbances rejection. This control law will independently control the speed and flux into the machine by restricting supply. A complete nonlinear observer for dynamic nature ensuring closed loop stability of the entire control and observer has been developed. Several simulations have also been carried out to demonstrate system performance.

  15. Adaptive synchronization of the complex dynamical network with non-derivative and derivative coupling

    Science.gov (United States)

    Xu, Yuhua; Zhou, Wuneng; Fang, Jian'an; Sun, Wen

    2010-04-01

    This Letter investigates the synchronization of a general complex dynamical network with non-derivative and derivative coupling. Based on LaSalle's invariance principle, adaptive synchronization criteria are obtained. Analytical result shows that under the designed adaptive controllers, a general complex dynamical network with non-derivative and derivative coupling can asymptotically synchronize to a given trajectory, and several useful criteria for synchronization are given. What is more, the coupling matrix is not assumed to be symmetric or irreducible. Finally, simulations results show the method is effective.

  16. Adaptive synchronization of the complex dynamical network with non-derivative and derivative coupling

    Energy Technology Data Exchange (ETDEWEB)

    Xu Yuhua, E-mail: yuhuaxu2004@163.co [College of Information Science and Technology, Donghua University, Shanghai 201620 (China) and Department of Maths, Yunyang Teachers' College, Hubei 442000 (China); Zhou Wuneng, E-mail: wnzhou@163.co [College of Information Science and Technology, Donghua University, Shanghai 201620 (China); Fang Jian' an [College of Information Science and Technology, Donghua University, Shanghai 201620 (China); Sun Wen [School of Mathematics and Information, Yangtze University, Hubei Jingzhou 434023 (China)

    2010-04-05

    This Letter investigates the synchronization of a general complex dynamical network with non-derivative and derivative coupling. Based on LaSalle's invariance principle, adaptive synchronization criteria are obtained. Analytical result shows that under the designed adaptive controllers, a general complex dynamical network with non-derivative and derivative coupling can asymptotically synchronize to a given trajectory, and several useful criteria for synchronization are given. What is more, the coupling matrix is not assumed to be symmetric or irreducible. Finally, simulations results show the method is effective.

  17. Structural self-assembly and avalanchelike dynamics in locally adaptive networks

    Science.gov (United States)

    Gräwer, Johannes; Modes, Carl D.; Magnasco, Marcelo O.; Katifori, Eleni

    2015-07-01

    Transport networks play a key role across four realms of eukaryotic life: slime molds, fungi, plants, and animals. In addition to the developmental algorithms that build them, many also employ adaptive strategies to respond to stimuli, damage, and other environmental changes. We model these adapting network architectures using a generic dynamical system on weighted graphs and find in simulation that these networks ultimately develop a hierarchical organization of the final weighted architecture accompanied by the formation of a system-spanning backbone. In addition, we find that the long term equilibration dynamics exhibit behavior reminiscent of glassy systems characterized by long periods of slow changes punctuated by bursts of reorganization events.

  18. Adaptive Finite-Time Stabilization of High-Order Nonlinear Systems with Dynamic and Parametric Uncertainties

    Directory of Open Access Journals (Sweden)

    Meng-Meng Jiang

    2016-01-01

    Full Text Available Under the weaker assumption on nonlinear functions, the adaptive finite-time stabilization of more general high-order nonlinear systems with dynamic and parametric uncertainties is solved in this paper. To solve this problem, finite-time input-to-state stability (FTISS is used to characterize the unmeasured dynamic uncertainty. By skillfully combining Lyapunov function, sign function, backstepping, and finite-time input-to-state stability approaches, an adaptive state feedback controller is designed to guarantee high-order nonlinear systems are globally finite-time stable.

  19. Methodology for Simulation and Analysis of Complex Adaptive Supply Network Structure and Dynamics Using Information Theory

    Directory of Open Access Journals (Sweden)

    Joshua Rodewald

    2016-10-01

    Full Text Available Supply networks existing today in many industries can behave as complex adaptive systems making them more difficult to analyze and assess. Being able to fully understand both the complex static and dynamic structures of a complex adaptive supply network (CASN are key to being able to make more informed management decisions and prioritize resources and production throughout the network. Previous efforts to model and analyze CASN have been impeded by the complex, dynamic nature of the systems. However, drawing from other complex adaptive systems sciences, information theory provides a model-free methodology removing many of those barriers, especially concerning complex network structure and dynamics. With minimal information about the network nodes, transfer entropy can be used to reverse engineer the network structure while local transfer entropy can be used to analyze the network structure’s dynamics. Both simulated and real-world networks were analyzed using this methodology. Applying the methodology to CASNs allows the practitioner to capitalize on observations from the highly multidisciplinary field of information theory which provides insights into CASN’s self-organization, emergence, stability/instability, and distributed computation. This not only provides managers with a more thorough understanding of a system’s structure and dynamics for management purposes, but also opens up research opportunities into eventual strategies to monitor and manage emergence and adaption within the environment.

  20. Adaptive Process Management in Highly Dynamic and Pervasive Scenarios

    CERN Document Server

    de Leoni, Massimiliano

    2009-01-01

    Process Management Systems (PMSs) are currently more and more used as a supporting tool for cooperative processes in pervasive and highly dynamic situations, such as emergency situations, pervasive healthcare or domotics/home automation. But in all such situations, designed processes can be easily invalidated since the execution environment may change continuously due to frequent unforeseeable events. This paper aims at illustrating the theoretical framework and the concrete implementation of SmartPM, a PMS that features a set of sound and complete techniques to automatically cope with unplanned exceptions. PMS SmartPM is based on a general framework which adopts the Situation Calculus and Indigolog.

  1. Adaptive Process Management in Highly Dynamic and Pervasive Scenarios

    Directory of Open Access Journals (Sweden)

    Massimiliano de Leoni

    2009-06-01

    Full Text Available Process Management Systems (PMSs are currently more and more used as a supporting tool for cooperative processes in pervasive and highly dynamic situations, such as emergency situations, pervasive healthcare or domotics/home automation. But in all such situations, designed processes can be easily invalidated since the execution environment may change continuously due to frequent unforeseeable events. This paper aims at illustrating the theoretical framework and the concrete implementation of SmartPM, a PMS that features a set of sound and complete techniques to automatically cope with unplanned exceptions. PMS SmartPM is based on a general framework which adopts the Situation Calculus and Indigolog.

  2. A rigorous model study of the adaptative dynamics of Mendelian diploids

    CERN Document Server

    Collet, Pierre; Metz, J A J

    2011-01-01

    Adaptive dynamics so far has been put on a rigorous footing only for clonal inheritance. We extend this to sexually reproducing diploids, although admittedly still under the restriction of an unstructured population with Lotka-Volterra-like dynamics and single locus genetics (as in Kimura's 1965 infinite allele model). We prove under the usual smoothness assumptions, starting from a stochastic birth and death process model, that, when advantageous mutations are rare and mutational steps are not too large, the population behaves on the mutational time scale (the 'long' time scale of the literature on the genetical foundations of ESS theory) as a jump process moving between homozygous states (the trait substitution sequence of the adaptive dynamics literature). Essential technical ingredients are a rigorous estimate for the probability of invasion in a dynamic diploid population, a rigorous, geometric singular perturbation theory based, invasion implies substitution theorem, and the use of the Skorohod $M_1$ to...

  3. Adaptive rational block Arnoldi methods for model reductions in large-scale MIMO dynamical systems

    Directory of Open Access Journals (Sweden)

    Khalide Jbilou

    2016-04-01

    Full Text Available In recent years, a great interest has been shown towards Krylov subspace techniques applied to model order reduction of large-scale dynamical systems. A special interest has been devoted to single-input single-output (SISO systems by using moment matching techniques based on Arnoldi or Lanczos algorithms. In this paper, we consider multiple-input multiple-output (MIMO dynamical systems and introduce the rational block Arnoldi process to design low order dynamical systems that are close in some sense to the original MIMO dynamical system. Rational Krylov subspace methods are based on the choice of suitable shifts that are selected a priori or adaptively. In this paper, we propose an adaptive selection of those shifts and show the efficiency of this approach in our numerical tests. We also give some new block Arnoldi-like relations that are used to propose an upper bound for the norm of the error on the transfer function.

  4. Dynamic and adaptive policy models for coalition operations

    Science.gov (United States)

    Verma, Dinesh; Calo, Seraphin; Chakraborty, Supriyo; Bertino, Elisa; Williams, Chris; Tucker, Jeremy; Rivera, Brian; de Mel, Geeth R.

    2017-05-01

    It is envisioned that the success of future military operations depends on the better integration, organizationally and operationally, among allies, coalition members, inter-agency partners, and so forth. However, this leads to a challenging and complex environment where the heterogeneity and dynamism in the operating environment intertwines with the evolving situational factors that affect the decision-making life cycle of the war fighter. Therefore, the users in such environments need secure, accessible, and resilient information infrastructures where policy-based mechanisms adopt the behaviours of the systems to meet end user goals. By specifying and enforcing a policy based model and framework for operations and security which accommodates heterogeneous coalitions, high levels of agility can be enabled to allow rapid assembly and restructuring of system and information resources. However, current prevalent policy models (e.g., rule based event-condition-action model and its variants) are not sufficient to deal with the highly dynamic and plausibly non-deterministic nature of these environments. Therefore, to address the above challenges, in this paper, we present a new approach for policies which enables managed systems to take more autonomic decisions regarding their operations.

  5. Body surface adaptations to boundary-layer dynamics.

    Science.gov (United States)

    Videler, J J

    1995-01-01

    Evolutionary processes have adapted nektonic animals to interact efficiently with the water that surrounds them. Not all these adaptations serve the same purpose. This paper concentrates on reduction of drag due to friction in the boundary layer close to the body surface. Mucus, compliant skins, scales, riblets and roughness may influence the flow velocity gradient, the type of flow and the thickness of the boundary layer around animals, and may seriously affect their drag in a positive or negative way. The long-chain polymers found in mucus decrease the pressure gradient and considerably reduced drag due to friction. The effect is probably due to channelling of the flow particles in the direction of the main flow, resulting in a reduction of turbulence. Compliant surfaces could probably reduce drag by equalising and distributing pressure pulses. However, the existing evidence that drag reduction actually occurs is not convincing. There is no indication that instantaneous heating, reducing the viscosity in the boundary layer, is used by animals as a drag-reducing technique. Small longitudinal ridges on rows of scales on fish can reduce shear stress in the boundary by a maximum of 10% compared with the shear stress of a smooth surface. The mechanism is based on the impedance of cross flow under well-defined conditions. The effect has been visualized with the use of particle image velocimetry techniques. The function of the swords and spears of several fast, pelagic, predatory fish species is still enigmatic. The surface structure of the sword of a swordfish is shown to be both rough and porous. The height of the roughness elements on the tip of the sword is close to the critical value for the induction of a laminar-to-turbulent flow transition at moderate cruising speeds. A flow tank is described that is designed to visualize the effects of surface imperfections on flow in the boundary layer in direct comparison with a smooth flat wall. The flow in a 1 m long, 10 cm

  6. Workload Model Based Dynamic Adaptation of Social Internet of Vehicles

    Directory of Open Access Journals (Sweden)

    Kazi Masudul Alam

    2015-09-01

    Full Text Available Social Internet of Things (SIoT has gained much interest among different research groups in recent times. As a key member of a smart city, the vehicular domain of SIoT (SIoV is also undergoing steep development. In the SIoV, vehicles work as sensor-hub to capture surrounding information using the in-vehicle and Smartphone sensors and later publish them for the consumers. A cloud centric cyber-physical system better describes the SIoV model where physical sensing-actuation process affects the cloud based service sharing or computation in a feedback loop or vice versa. The cyber based social relationship abstraction enables distributed, easily navigable and scalable peer-to-peer communication among the SIoV subsystems. These cyber-physical interactions involve a huge amount of data and it is difficult to form a real instance of the system to test the feasibility of SIoV applications. In this paper, we propose an analytical model to measure the workloads of various subsystems involved in the SIoV process. We present the basic model which is further extended to incorporate complex scenarios. We provide extensive simulation results for different parameter settings of the SIoV system. The findings of the analyses are further used to design example adaptation strategies for the SIoV subsystems which would foster deployment of intelligent transport systems.

  7. Workload Model Based Dynamic Adaptation of Social Internet of Vehicles.

    Science.gov (United States)

    Alam, Kazi Masudul; Saini, Mukesh; El Saddik, Abdulmotaleb

    2015-09-15

    Social Internet of Things (SIoT) has gained much interest among different research groups in recent times. As a key member of a smart city, the vehicular domain of SIoT (SIoV) is also undergoing steep development. In the SIoV, vehicles work as sensor-hub to capture surrounding information using the in-vehicle and Smartphone sensors and later publish them for the consumers. A cloud centric cyber-physical system better describes the SIoV model where physical sensing-actuation process affects the cloud based service sharing or computation in a feedback loop or vice versa. The cyber based social relationship abstraction enables distributed, easily navigable and scalable peer-to-peer communication among the SIoV subsystems. These cyber-physical interactions involve a huge amount of data and it is difficult to form a real instance of the system to test the feasibility of SIoV applications. In this paper, we propose an analytical model to measure the workloads of various subsystems involved in the SIoV process. We present the basic model which is further extended to incorporate complex scenarios. We provide extensive simulation results for different parameter settings of the SIoV system. The findings of the analyses are further used to design example adaptation strategies for the SIoV subsystems which would foster deployment of intelligent transport systems.

  8. Dynamic Structure Neural Networks for Stable Adaptive Control of Nonlinear Systems

    OpenAIRE

    Fabri, S.; Kadirkamanathan, V.

    1994-01-01

    An adaptive control technique, using dynamic structure Gaussian radical basis function neural networks, that grow in time according to the location of the system's state in space is presented for the affine class of nonlinear systems having unknown or partially known dynamics. The method results in a network that is economic in terms of network size, for cases where the state spans only a small subset of state space, by utilising less basis functions than would have been the case if basis fun...

  9. Update: Advancement of Contact Dynamics Modeling for Human Spaceflight Simulation Applications

    Science.gov (United States)

    Brain, Thomas A.; Kovel, Erik B.; MacLean, John R.; Quiocho, Leslie J.

    2017-01-01

    Pong is a new software tool developed at the NASA Johnson Space Center that advances interference-based geometric contact dynamics based on 3D graphics models. The Pong software consists of three parts: a set of scripts to extract geometric data from 3D graphics models, a contact dynamics engine that provides collision detection and force calculations based on the extracted geometric data, and a set of scripts for visualizing the dynamics response with the 3D graphics models. The contact dynamics engine can be linked with an external multibody dynamics engine to provide an integrated multibody contact dynamics simulation. This paper provides a detailed overview of Pong including the overall approach and modeling capabilities, which encompasses force generation from contact primitives and friction to computational performance. Two specific Pong-based examples of International Space Station applications are discussed, and the related verification and validation using this new tool are also addressed.

  10. A MATLAB toolbox for the efficient estimation of the psychometric function using the updated maximum-likelihood adaptive procedure

    Science.gov (United States)

    Richards, V. M.; Dai, W.

    2014-01-01

    A MATLAB toolbox for the efficient estimation of the threshold, slope, and lapse rate of the psychometric function is described. The toolbox enables the efficient implementation of the updated maximum-likelihood (UML) procedure. The toolbox uses an object-oriented architecture for organizing the experimental variables and computational algorithms, which provides experimenters with flexibility in experimental design and data management. Descriptions of the UML procedure and the UML Toolbox are provided, followed by toolbox use examples. Finally, guidelines and recommendations of parameter configurations are given. PMID:24671826

  11. A MATLAB toolbox for the efficient estimation of the psychometric function using the updated maximum-likelihood adaptive procedure.

    Science.gov (United States)

    Shen, Yi; Dai, Wei; Richards, Virginia M

    2015-03-01

    A MATLAB toolbox for the efficient estimation of the threshold, slope, and lapse rate of the psychometric function is described. The toolbox enables the efficient implementation of the updated maximum-likelihood (UML) procedure. The toolbox uses an object-oriented architecture for organizing the experimental variables and computational algorithms, which provides experimenters with flexibility in experimental design and data management. Descriptions of the UML procedure and the UML Toolbox are provided, followed by toolbox use examples. Finally, guidelines and recommendations of parameter configurations are given.

  12. Adaptive control for space debris removal with uncertain kinematics, dynamics and states

    Science.gov (United States)

    Huang, Panfeng; Zhang, Fan; Meng, Zhongjie; Liu, Zhengxiong

    2016-11-01

    As the Tethered Space Robot is considered to be a promising solution for the Active Debris Removal, a lot of problems arise in the approaching, capturing and removing phases. Particularly, kinematics and dynamics parameters of the debris are unknown, and parts of the states are unmeasurable according to the specifics of tether, which is a tough problem for the target retrieval/de-orbiting. This work proposes a full adaptive control strategy for the space debris removal via a Tethered Space Robot with unknown kinematics, dynamics and part of the states. First we derive a dynamics model for the retrieval by treating the base satellite (chaser) and the unknown space debris (target) as rigid bodies in the presence of offsets, and involving the flexibility and elasticity of tether. Then, a full adaptive controller is presented including a control law, a dynamic adaption law, and a kinematic adaption law. A modified controller is also presented according to the peculiarities of this system. Finally, simulation results are presented to illustrate the performance of two proposed controllers.

  13. A Self-adaptive Scope Allocation Scheme for Labeling Dynamic XML Documents

    NARCIS (Netherlands)

    Shen, Y.; Feng, L.; Shen, T.; Wang, B.

    2004-01-01

    This paper proposes a self-adaptive scope allocation scheme for labeling dynamic XML documents. It is general, light-weight and can be built upon existing data retrieval mechanisms. Bayesian inference is used to compute the actual scope allocated for labeling a certain node based on both the prior i

  14. Supporting Dynamic Adaptive Streaming over HTTP in Wireless Meshed Networks using Random Linear Network Coding

    DEFF Research Database (Denmark)

    Hundebøll, Martin; Pedersen, Morten Videbæk; Roetter, Daniel Enrique Lucani

    2014-01-01

    This work studies the potential and impact of the FRANC network coding protocol for delivering high quality Dynamic Adaptive Streaming over HTTP (DASH) in wireless networks. Although DASH aims to tailor the video quality rate based on the available throughput to the destination, it relies...

  15. Adaptive Fuzzy Control of Strict-Feedback Nonlinear Time-Delay Systems With Unmodeled Dynamics.

    Science.gov (United States)

    Yin, Shen; Shi, Peng; Yang, Hongyan

    2016-08-01

    In this paper, an approximated-based adaptive fuzzy control approach with only one adaptive parameter is presented for a class of single input single output strict-feedback nonlinear systems in order to deal with phenomena like nonlinear uncertainties, unmodeled dynamics, dynamic disturbances, and unknown time delays. Lyapunov-Krasovskii function approach is employed to compensate the unknown time delays in the design procedure. By combining the advances of the hyperbolic tangent function with adaptive fuzzy backstepping technique, the proposed controller guarantees the semi-globally uniformly ultimately boundedness of all the signals in the closed-loop system from the mean square point of view. Two simulation examples are finally provided to show the superior effectiveness of the proposed scheme.

  16. HOLD MODE BASED DYNAMIC PRIORITY LOAD ADAPTIVE INTERPICONET SCHEDULING FOR BLUETOOTH SCATTERNETS

    Directory of Open Access Journals (Sweden)

    G.S. Mahalakshmi

    2011-09-01

    Full Text Available Scheduling in piconets has emerged as a challenging research area. Interpiconet scheduling focuses on when a bridge is switched among various piconets and how a bridge node communicates with the masters in different piconets. This paper proposes an interpiconet scheduling algorithm named, hold mode based dynamic traffic priority load adaptive scheduling. The bridges are adaptively switched between the piconets according to various traffic loads. The main goal is to maximize the utilization of the bridge by reducing the bridge switch wastes, utilize intelligent decision making algorithm, resolve conflict between the masters, and allow negotiation for bridge utilization in HDPLIS using bridge failure-bridge repair procedure . The Hold mode - dynamic traffic - priority based - load adaptive scheduling reduces the number of bridge switch wastes and hence increases the efficiency of the bridge which results in increased performance of the system.

  17. We be jammin’: an update on pectin biosynthesis, trafficking and dynamics

    Energy Technology Data Exchange (ETDEWEB)

    Anderson, Charles T.

    2015-11-20

    Pectins are complex polysaccharides that contain acidic sugars and are major determinants of the cohesion, adhesion, extensibility, porosity and electrostatic potential of plant cell walls. Recent evidence has solidified their positions as key regulators of cellular growth and tissue morphogenesis, although important details of how they achieve this regulation are still missing. Pectins are also hypothesized to function as ligands for wall integrity sensors that enable plant cells to respond to intrinsic defects in wall biomechanics and to wall degradation by attacking pathogens. This update highlights recent advances in our understanding of the biosynthesis of pectins, how they are delivered to the cell surface and become incorporated into the cell wall matrix and how pectins are modified over time in the apoplast. It also poses unanswered questions for further research into this enigmatic but essential class of carbohydrate polymers.

  18. Update on Small Modular Reactors Dynamic System Modeling Tool: Web Application

    Energy Technology Data Exchange (ETDEWEB)

    Hale, Richard Edward [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Cetiner, Sacit M. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Fugate, David L. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Batteh, John J [Modelon Corporation (Sweden); Tiller, Michael M. [Xogeny Corporation (United States)

    2015-01-01

    Previous reports focused on the development of component and system models as well as end-to-end system models using Modelica and Dymola for two advanced reactor architectures: (1) Advanced Liquid Metal Reactor and (2) fluoride high-temperature reactor (FHR). The focus of this report is the release of the first beta version of the web-based application for model use and collaboration, as well as an update on the FHR model. The web-based application allows novice users to configure end-to-end system models from preconfigured choices to investigate the instrumentation and controls implications of these designs and allows for the collaborative development of individual component models that can be benchmarked against test systems for potential inclusion in the model library. A description of this application is provided along with examples of its use and a listing and discussion of all the models that currently exist in the library.

  19. A robust adaptive control with unmodeled dynamic for HVDC transmission systems

    Institute of Scientific and Technical Information of China (English)

    YAN Quan; LI Xing-yuan; WANG Lu; LIU Hong-chao; CHEN Shu-beng

    2006-01-01

    Utilizing the feature of quick response of HVDC to improve the performance of AC/DC system has become the emphasis to be researched.This paper introduces firstly the principle of the robust adaptive control of nonlinear systems with unmodeled dynamics,then developed the robust adaptive additional control of HVDC with unmodeled dynamics of generator in order to improve stability of power system.The additional control of HVDC with unmodeled dynamics only uses the local signals and its design is simple,furthermore it can obviously improve the stability of power system in different operational conditions.Experimental results using the presented concepts obtained on single machine infinite bus model are also included.These results prove the efficiency of the control scheme.The design process of controller provided a new idea to design controller by use of simplified model.

  20. Nonlinear Adaptive Control Using Gaussian Networks with Composite Adaptation for Improved Convergence

    OpenAIRE

    Fabri, S.; Kadirkamanathan, V.

    1996-01-01

    The use of composite adaptive laws for control of the affine class of nonlinear systems having unknown dynamics is proposed. These dynamics are approximated by Gaussian radial basis function neural networks whose parameters are updated by a composite law that is driven by both tracking and estimation errors, combining techniques used in direct and indirect adaptive control. This is motivated by the need to improve the speed of convergence of the unknown parameters, hence resulting in a better...

  1. Adaptive Neural Tracking Control for a Class of Nonlinear Systems With Dynamic Uncertainties.

    Science.gov (United States)

    Wang, Huanqing; Shi, Peng; Li, Hongyi; Zhou, Qi

    2016-09-22

    This paper considers the problem of adaptive neural control of nonlower triangular nonlinear systems with unmodeled dynamics and dynamic disturbances. The design difficulties appeared in the unmodeled dynamics and nonlower triangular form are handled with a dynamic signal and a variable partition technique for the nonlinear functions of all state variables, respectively. It is shown that the proposed controller is able to ensure the semi-global boundedness of all signals of the resulting closed-loop system. Furthermore, the system output is ensured to converge to a small domain of the given trajectories. The main advantage about this research is that a neural networks-based tracking control method is developed for uncertain nonlinear systems with unmodeled dynamics and nonlower triangular form. Simulation results demonstrate the feasibility of the newly presented design techniques.

  2. Adaptive Neural Network Dynamic Inversion with Prescribed Performance for Aircraft Flight Control

    Directory of Open Access Journals (Sweden)

    Wendong Gai

    2013-01-01

    Full Text Available An adaptive neural network dynamic inversion with prescribed performance method is proposed for aircraft flight control. The aircraft nonlinear attitude angle model is analyzed. And we propose a new attitude angle controller design method based on prescribed performance which describes the convergence rate and overshoot of the tracking error. Then the model error is compensated by the adaptive neural network. Subsequently, the system stability is analyzed in detail. Finally, the proposed method is applied to the aircraft attitude tracking control system. The nonlinear simulation demonstrates that this method can guarantee the stability and tracking performance in the transient and steady behavior.

  3. A mobile communication device adapted to provide a dynamic display arrangement

    DEFF Research Database (Denmark)

    2011-01-01

    The invention relates to a mobile communication device comprising a light projector adapted to project a multi-coloured image onto a surface; a hinged mirror comprising a first mirror part adapted to be tilted around the hinge into the light path of the light projector; wherein the first mirror...... part comprises means for correcting a skew angle in the multi-coloured image projected onto a surface. Thereby is achieved that the mobile communication device is able to provide RGB full colour dynamic image projection which is preferred over monochromatic laser projection because it is a speckle free...

  4. Hierarchical Direct Time Integration Method and Adaptive Procedure for Dynamic Analysis

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

    New hierarchical direct time integration method for structural dynamic analysis is developed by using Taylor series expansions in each time step. Very accurate results can be obtained by increasing the order of the Taylor series. Furthermore, the local error can be estimated by simply comparing the solutions obtained by the proposed method with the higher order solutions. This local estimate is then used to develop an adaptive order-control technique. Numerical examples are given to illustrate the performance of the present method and its adaptive procedure.

  5. Distributed Consensus-Based Robust Adaptive Formation Control for Nonholonomic Mobile Robots with Partial Known Dynamics

    Directory of Open Access Journals (Sweden)

    Zhaoxia Peng

    2014-01-01

    Full Text Available This paper investigates the distributed consensus-based robust adaptive formation control for nonholonomic mobile robots with partially known dynamics. Firstly, multirobot formation control problem has been converted into a state consensus problem. Secondly, the practical control strategies, which incorporate the distributed kinematic controllers and the robust adaptive torque controllers, are designed for solving the formation control problem. Thirdly, the specified reference trajectory for the geometric centroid of the formation is assumed as the trajectory of a virtual leader, whose information is available to only a subset of the followers. Finally, numerical results are provided to illustrate the effectiveness of the proposed control approaches.

  6. An adaptive approach to the dynamic allocation of buffer storage. M.S. Thesis

    Science.gov (United States)

    Crooke, S. C.

    1970-01-01

    Several strategies for the dynamic allocation of buffer storage are simulated and compared. The basic algorithms investigated, using actual statistics observed in the Univac 1108 EXEC 8 System, include the buddy method and the first-fit method. Modifications are made to the basic methods in an effort to improve and to measure allocation performance. A simulation model of an adaptive strategy is developed which permits interchanging the two different methods, the buddy and the first-fit methods with some modifications. Using an adaptive strategy, each method may be employed in the statistical environment in which its performance is superior to the other method.

  7. Study of Multimedia Streams Dynamic Rate Control Based on Fuzzy Adaptive PID

    Institute of Scientific and Technical Information of China (English)

    SUN Yan-fei; ZHANG Shun-yi; SHI Jin; WANG Jiang-tao

    2005-01-01

    A Multimedia streams dynamic rate control algorithm based on Fuzzy adaptive PID (MFPID) has been proposed to implement multimedia streams' end sending rate on-line self-regulating and smoothing, and to track system resources in time, so that it can avoid system's regulating oscillation and guarantee system's stability. And, some work has been done to analyze adaptive session model of multimedia streams, to implement future available bandwidth estimation of IP network, to achieve PID parameters' on-line self-tuning by fuzzy controlling. Simulation validated the theoretical results of MFPID.

  8. The adaptive dynamic community detection algorithm based on the non-homogeneous random walking

    Science.gov (United States)

    Xin, Yu; Xie, Zhi-Qiang; Yang, Jing

    2016-05-01

    With the changing of the habit and custom, people's social activity tends to be changeable. It is required to have a community evolution analyzing method to mine the dynamic information in social network. For that, we design the random walking possibility function and the topology gain function to calculate the global influence matrix of the nodes. By the analysis of the global influence matrix, the clustering directions of the nodes can be obtained, thus the NRW (Non-Homogeneous Random Walk) method for detecting the static overlapping communities can be established. We design the ANRW (Adaptive Non-Homogeneous Random Walk) method via adapting the nodes impacted by the dynamic events based on the NRW. The ANRW combines the local community detection with dynamic adaptive adjustment to decrease the computational cost for ANRW. Furthermore, the ANRW treats the node as the calculating unity, thus the running manner of the ANRW is suitable to the parallel computing, which could meet the requirement of large dataset mining. Finally, by the experiment analysis, the efficiency of ANRW on dynamic community detection is verified.

  9. Salinity fluctuation influencing biological adaptation: growth dynamics and Na(+) /K(+) -ATPase activity in a euryhaline bacterium.

    Science.gov (United States)

    Yang, Hao; Meng, Yang; Song, Youxin; Tan, Yalin; Warren, Alan; Li, Jiqiu; Lin, Xiaofeng

    2017-07-01

    Although salinity fluctuation is a prominent characteristic of many coastal ecosystems, its effects on biological adaptation have not yet been fully recognized. To test the salinity fluctuations on biological adaptation, population growth dynamics and Na(+) /K(+) -ATPase activity were investigated in the euryhaline bacterium Idiomarina sp. DYB, which was acclimated at different salinity exposure levels, exposure times, and shifts in direction of salinity. Results showed: (1) bacterial population growth dynamics and Na(+) /K(+) -ATPase activity changed significantly in response to salinity fluctuation; (2) patterns of variation in bacterial growth dynamics were related to exposure times, levels of salinity, and shifts in direction of salinity change; (3) significant tradeoffs were detected between growth rate (r) and carrying capacity (K) on the one hand, and Na(+) /K(+) -ATPase activity on the other; and (4) beneficial acclimation was confirmed in Idiomarina sp. DYB. In brief, this study demonstrated that salinity fluctuation can change the population growth dynamics, Na(+) /K(+) -ATPase activity, and tradeoffs between r, K, and Na(+) /K(+) -ATPase activity, thus facilitating bacterial adaption in a changing environment. These findings provide constructive information for determining biological response patterns to environmental change. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  10. Macroscopic description of complex adaptive networks coevolving with dynamic node states

    Science.gov (United States)

    Wiedermann, Marc; Donges, Jonathan F.; Heitzig, Jobst; Lucht, Wolfgang; Kurths, Jürgen

    2015-05-01

    In many real-world complex systems, the time evolution of the network's structure and the dynamic state of its nodes are closely entangled. Here we study opinion formation and imitation on an adaptive complex network which is dependent on the individual dynamic state of each node and vice versa to model the coevolution of renewable resources with the dynamics of harvesting agents on a social network. The adaptive voter model is coupled to a set of identical logistic growth models and we mainly find that, in such systems, the rate of interactions between nodes as well as the adaptive rewiring probability are crucial parameters for controlling the sustainability of the system's equilibrium state. We derive a macroscopic description of the system in terms of ordinary differential equations which provides a general framework to model and quantify the influence of single node dynamics on the macroscopic state of the network. The thus obtained framework is applicable to many fields of study, such as epidemic spreading, opinion formation, or socioecological modeling.

  11. Catalysis of protein folding by chaperones accelerates evolutionary dynamics in adapting cell populations.

    Science.gov (United States)

    Cetinbaş, Murat; Shakhnovich, Eugene I

    2013-01-01

    Although molecular chaperones are essential components of protein homeostatic machinery, their mechanism of action and impact on adaptation and evolutionary dynamics remain controversial. Here we developed a physics-based ab initio multi-scale model of a living cell for population dynamics simulations to elucidate the effect of chaperones on adaptive evolution. The 6-loci genomes of model cells encode model proteins, whose folding and interactions in cellular milieu can be evaluated exactly from their genome sequences. A genotype-phenotype relationship that is based on a simple yet non-trivially postulated protein-protein interaction (PPI) network determines the cell division rate. Model proteins can exist in native and molten globule states and participate in functional and all possible promiscuous non-functional PPIs. We find that an active chaperone mechanism, whereby chaperones directly catalyze protein folding, has a significant impact on the cellular fitness and the rate of evolutionary dynamics, while passive chaperones, which just maintain misfolded proteins in soluble complexes have a negligible effect on the fitness. We find that by partially releasing the constraint on protein stability, active chaperones promote a deeper exploration of sequence space to strengthen functional PPIs, and diminish the non-functional PPIs. A key experimentally testable prediction emerging from our analysis is that down-regulation of chaperones that catalyze protein folding significantly slows down the adaptation dynamics.

  12. Catalysis of protein folding by chaperones accelerates evolutionary dynamics in adapting cell populations.

    Directory of Open Access Journals (Sweden)

    Murat Cetinbaş

    Full Text Available Although molecular chaperones are essential components of protein homeostatic machinery, their mechanism of action and impact on adaptation and evolutionary dynamics remain controversial. Here we developed a physics-based ab initio multi-scale model of a living cell for population dynamics simulations to elucidate the effect of chaperones on adaptive evolution. The 6-loci genomes of model cells encode model proteins, whose folding and interactions in cellular milieu can be evaluated exactly from their genome sequences. A genotype-phenotype relationship that is based on a simple yet non-trivially postulated protein-protein interaction (PPI network determines the cell division rate. Model proteins can exist in native and molten globule states and participate in functional and all possible promiscuous non-functional PPIs. We find that an active chaperone mechanism, whereby chaperones directly catalyze protein folding, has a significant impact on the cellular fitness and the rate of evolutionary dynamics, while passive chaperones, which just maintain misfolded proteins in soluble complexes have a negligible effect on the fitness. We find that by partially releasing the constraint on protein stability, active chaperones promote a deeper exploration of sequence space to strengthen functional PPIs, and diminish the non-functional PPIs. A key experimentally testable prediction emerging from our analysis is that down-regulation of chaperones that catalyze protein folding significantly slows down the adaptation dynamics.

  13. Geophysical astrophysical spectral-element adaptive refinement (GASpAR): Object-oriented h-adaptive fluid dynamics simulation

    Science.gov (United States)

    Rosenberg, Duane; Fournier, Aimé; Fischer, Paul; Pouquet, Annick

    2006-06-01

    An object-oriented geophysical and astrophysical spectral-element adaptive refinement (GASpAR) code is introduced. Like most spectral-element codes, GASpAR combines finite-element efficiency with spectral-method accuracy. It is also designed to be flexible enough for a range of geophysics and astrophysics applications where turbulence or other complex multiscale problems arise. The formalism accommodates both conforming and non-conforming elements. Several aspects of this code derive from existing methods, but here are synthesized into a new formulation of dynamic adaptive refinement (DARe) of non-conforming h-type. As a demonstration of the code, several new 2D test cases are introduced that have time-dependent analytic solutions and exhibit localized flow features, including the 2D Burgers equation with straight, curved-radial and oblique-colliding fronts. These are proposed as standard test problems for comparable DARe codes. Quantitative errors are reported for 2D spatial and temporal convergence of DARe.

  14. Parallel Adaptive Mesh Refinement for High-Order Finite-Volume Schemes in Computational Fluid Dynamics

    Science.gov (United States)

    Schwing, Alan Michael

    For computational fluid dynamics, the governing equations are solved on a discretized domain of nodes, faces, and cells. The quality of the grid or mesh can be a driving source for error in the results. While refinement studies can help guide the creation of a mesh, grid quality is largely determined by user expertise and understanding of the flow physics. Adaptive mesh refinement is a technique for enriching the mesh during a simulation based on metrics for error, impact on important parameters, or location of important flow features. This can offload from the user some of the difficult and ambiguous decisions necessary when discretizing the domain. This work explores the implementation of adaptive mesh refinement in an implicit, unstructured, finite-volume solver. Consideration is made for applying modern computational techniques in the presence of hanging nodes and refined cells. The approach is developed to be independent of the flow solver in order to provide a path for augmenting existing codes. It is designed to be applicable for unsteady simulations and refinement and coarsening of the grid does not impact the conservatism of the underlying numerics. The effect on high-order numerical fluxes of fourth- and sixth-order are explored. Provided the criteria for refinement is appropriately selected, solutions obtained using adapted meshes have no additional error when compared to results obtained on traditional, unadapted meshes. In order to leverage large-scale computational resources common today, the methods are parallelized using MPI. Parallel performance is considered for several test problems in order to assess scalability of both adapted and unadapted grids. Dynamic repartitioning of the mesh during refinement is crucial for load balancing an evolving grid. Development of the methods outlined here depend on a dual-memory approach that is described in detail. Validation of the solver developed here against a number of motivating problems shows favorable

  15. Modularity, adaptability and evolution in the AUTOPIA architecture for control of autonomous vehicles. Updating Mechatronics of Automatic Cars

    OpenAIRE

    Pérez Rastelli, Joshué; González, Carlos; Milanés, Vicente; Onieva, Enrique; Godoy, Jorge; Pedro, Teresa De

    2009-01-01

    International audience; Computer systems to carry out control algorithms on autonomous vehicles have been developed in recent years. However, the advances in peripheral devices allow connecting the actuator controllers to the control system by means of standard communication links (USB, CAN, Ethernet ... ).The goal is to permit the use of standard computers. In this paper, we present the evolution of AUTOPIA architecture and its modularity and adaptability to move the old system based on ISA ...

  16. High protein flexibility and reduced hydration water dynamics are key pressure adaptive strategies in prokaryotes

    KAUST Repository

    Martinez, N.

    2016-09-06

    Water and protein dynamics on a nanometer scale were measured by quasi-elastic neutron scattering in the piezophile archaeon Thermococcus barophilus and the closely related pressure-sensitive Thermococcus kodakarensis, at 0.1 and 40 MPa. We show that cells of the pressure sensitive organism exhibit higher intrinsic stability. Both the hydration water dynamics and the fast protein and lipid dynamics are reduced under pressure. In contrast, the proteome of T. barophilus is more pressure sensitive than that of T. kodakarensis. The diffusion coefficient of hydration water is reduced, while the fast protein and lipid dynamics are slightly enhanced with increasing pressure. These findings show that the coupling between hydration water and cellular constituents might not be simply a master-slave relationship. We propose that the high flexibility of the T. barophilus proteome associated with reduced hydration water may be the keys to the molecular adaptation of the cells to high hydrostatic pressure.

  17. Fiber Bragg grating dynamic strain sensor using an adaptive reflective semiconductor optical amplifier source.

    Science.gov (United States)

    Wei, Heming; Tao, Chuanyi; Zhu, Yinian; Krishnaswamy, Sridhar

    2016-04-01

    In this paper, a reflective semiconductor optical amplifier (RSOA) is configured to demodulate dynamic spectral shifts of a fiber Bragg grating (FBG) dynamic strain sensor. The FBG sensor and the RSOA source form an adaptive fiber cavity laser. As the reflective spectrum of the FBG sensor changes due to dynamic strains, the wavelength of the laser output shifts accordingly, which is subsequently converted into a corresponding phase shift and demodulated by an unbalanced Michelson interferometer. Due to the short transition time of the RSOA, the RSOA-FBG cavity can respond to dynamic strains at high frequencies extending to megahertz. A demodulator using a PID controller is used to compensate for low-frequency drifts induced by temperature and large quasi-static strains. As the sensitivity of the demodulator is a function of the optical path difference and the FBG spectral width, optimal parameters to obtain high sensitivity are presented. Multiplexing to demodulate multiple FBG sensors is also discussed.

  18. High protein flexibility and reduced hydration water dynamics are key pressure adaptive strategies in prokaryotes

    Science.gov (United States)

    Martinez, N.; Michoud, G.; Cario, A.; Ollivier, J.; Franzetti, B.; Jebbar, M.; Oger, P.; Peters, J.

    2016-09-01

    Water and protein dynamics on a nanometer scale were measured by quasi-elastic neutron scattering in the piezophile archaeon Thermococcus barophilus and the closely related pressure-sensitive Thermococcus kodakarensis, at 0.1 and 40 MPa. We show that cells of the pressure sensitive organism exhibit higher intrinsic stability. Both the hydration water dynamics and the fast protein and lipid dynamics are reduced under pressure. In contrast, the proteome of T. barophilus is more pressure sensitive than that of T. kodakarensis. The diffusion coefficient of hydration water is reduced, while the fast protein and lipid dynamics are slightly enhanced with increasing pressure. These findings show that the coupling between hydration water and cellular constituents might not be simply a master-slave relationship. We propose that the high flexibility of the T. barophilus proteome associated with reduced hydration water may be the keys to the molecular adaptation of the cells to high hydrostatic pressure.

  19. Power and Mobility-Aware Adaptive Dynamic Source Routing in Mobile Ad Hoc Network

    Institute of Scientific and Technical Information of China (English)

    XULi; ZHENGBaoyu; YANGZhen

    2005-01-01

    MANET (Mobile ad hoc network) is characterized by a highly dynamic network topology. This makes routing discovery and maintenance challenging for routing protocol design. On the other hand, energy efficient routing may be another important design criterion for MANET since most of nodes are usually powered by battery with limited capacity. With optimization of DSR (Dynamic source routing) protocol, this paper proposes Power and mobility-aware adaptive dynamic source routing (PMADSR). The new routing protocol can be aware of the mobility and remaining battery capacity of nodes. Performance simulation results show that the proposed PMADSR protocol can dynamically balance the traffic load inside the whole network, so as to prolong the network lifetime, as well as achieve higher throughput.

  20. Laboratory comparison of coronagraphic concepts under dynamical seeing and high-order adaptive optics correction

    CERN Document Server

    Martinez, P; Kasper, M; Boccaletti, A; Dorrer, C; Baudrand, J

    2011-01-01

    The exoplanetary science through direct imaging and spectroscopy will largely expand with the forthcoming development of new instruments at the VLT (SPHERE), Gemini (GPI), Subaru (HiCIAO), and Palomar (Project 1640) observatories. All these ground-based adaptive optics instruments combine extremely high performance adaptive optics (XAO) systems correcting for the atmospheric turbulence with advanced starlight-cancellation techniques such as coronagraphy to deliver contrast ratios of about 10-6 to 10-7. While the past fifteen years have seen intensive research and the development of high-contrast coronagraph concepts, very few concepts have been tested under dynamical seeing conditions (either during sky observation or in a realistic laboratory environment). In this paper, we discuss the results obtained with four different coronagraphs -- phase and amplitude types -- on the High-Order Testbench (HOT), the adaptive optics facility developed at ESO. This facility emphasizes realistic conditions encountered at a...

  1. Quantum Information Biology: From Theory of Open Quantum Systems to Adaptive Dynamics

    Science.gov (United States)

    Asano, Masanari; Basieva, Irina; Khrennikov, Andrei; Ohya, Masanori; Tanaka, Yoshiharu; Yamato, Ichiro

    This chapter reviews quantum(-like) information biology (QIB). Here biology is treated widely as even covering cognition and its derivatives: psychology and decision making, sociology, and behavioral economics and finances. QIB provides an integrative description of information processing by bio-systems at all scales of life: from proteins and cells to cognition, ecological and social systems. Mathematically QIB is based on the theory of adaptive quantum systems (which covers also open quantum systems). Ideologically QIB is based on the quantum-like (QL) paradigm: complex bio-systems process information in accordance with the laws of quantum information and probability. This paradigm is supported by plenty of statistical bio-data collected at all bio-scales. QIB re ects the two fundamental principles: a) adaptivity; and, b) openness (bio-systems are fundamentally open). In addition, quantum adaptive dynamics provides the most generally possible mathematical representation of these principles.

  2. Adaptive Fuzzy Output Feedback Control for Switched Nonlinear Systems With Unmodeled Dynamics.

    Science.gov (United States)

    Tong, Shaocheng; Li, Yongming

    2017-02-01

    This paper investigates a robust adaptive fuzzy control stabilization problem for a class of uncertain nonlinear systems with arbitrary switching signals that use an observer-based output feedback scheme. The considered switched nonlinear systems possess the unstructured uncertainties, unmodeled dynamics, and without requiring the states being available for measurement. A state observer which is independent of switching signals is designed to solve the problem of unmeasured states. Fuzzy logic systems are used to identify unknown lumped nonlinear functions so that the problem of unstructured uncertainties can be solved. By combining adaptive backstepping design principle and small-gain approach, a novel robust adaptive fuzzy output feedback stabilization control approach is developed. The stability of the closed-loop system is proved via the common Lyapunov function theory and small-gain theorem. Finally, the simulation results are given to demonstrate the validity and performance of the proposed control strategy.

  3. What's in a Name? Interlocutors dynamically update expectations about shared names

    Directory of Open Access Journals (Sweden)

    Whitney Marie Gegg-Harrison

    2016-02-01

    Full Text Available In order to refer using a name, speakers must know that their addressee knows about the link between the name and the intended referent. In cases where speakers and addressees learned names together, speakers are adept at using names only when their addressee knows them. But speakers do not always share such learning experience with their conversational partners. In these situations, what information guides speakers’ choice of referring expression? A speaker who is uncertain about a names’ common ground (CG status often uses a name and description together. This N+D form allows speakers to demonstrate knowledge of a name, and could provide, even in the absence of miscommunication, useful evidence to the addressee regarding the speaker’s knowledge. In cases where knowledge of one name is associated with knowledge of other names, could provide indirect evidence regarding knowledge of other names that could support generalizations used to update beliefs about CG. Using data explanation approaches to language processing as a guiding framework, we predict that interlocutors can use their partner’s choice of referring expression, in particular their use of an N+D form, to generate more accurate beliefs regarding their partner’s knowledge of other names. In Experiment 1, we find that domain experts are able to use their partner’s referring expression choices to generate more accurate estimates of CG. In Experiment 2, we find that interlocutors are able to infer from a partner’s use of an N+D form which other names that partner is likely to know or not know. Our results suggest that interlocutors can use the information conveyed in their partner’s choice of referring expression to make generalizations that contribute to more accurate beliefs about what is shared with their partner, and further, that models of CG for reference need to account not just for the status of referents, but the status of means of referring to those referents.

  4. Disentangling density-dependent dynamics using full annual cycle models and Bayesian model weight updating

    Science.gov (United States)

    Robinson, Orin J.; McGowan, Conor; Devers, Patrick K.

    2017-01-01

    Density dependence regulates populations of many species across all taxonomic groups. Understanding density dependence is vital for predicting the effects of climate, habitat loss and/or management actions on wild populations. Migratory species likely experience seasonal changes in the relative influence of density dependence on population processes such as survival and recruitment throughout the annual cycle. These effects must be accounted for when characterizing migratory populations via population models.To evaluate effects of density on seasonal survival and recruitment of a migratory species, we used an existing full annual cycle model framework for American black ducks Anas rubripes, and tested different density effects (including no effects) on survival and recruitment. We then used a Bayesian model weight updating routine to determine which population model best fit observed breeding population survey data between 1990 and 2014.The models that best fit the survey data suggested that survival and recruitment were affected by density dependence and that density effects were stronger on adult survival during the breeding season than during the non-breeding season.Analysis also suggests that regulation of survival and recruitment by density varied over time. Our results showed that different characterizations of density regulations changed every 8–12 years (three times in the 25-year period) for our population.Synthesis and applications. Using a full annual cycle, modelling framework and model weighting routine will be helpful in evaluating density dependence for migratory species in both the short and long term. We used this method to disentangle the seasonal effects of density on the continental American black duck population which will allow managers to better evaluate the effects of habitat loss and potential habitat management actions throughout the annual cycle. The method here may allow researchers to hone in on the proper form and/or strength of

  5. Behavioral and neural Darwinism: selectionist function and mechanism in adaptive behavior dynamics.

    Science.gov (United States)

    McDowell, J J

    2010-05-01

    An evolutionary theory of behavior dynamics and a theory of neuronal group selection share a common selectionist framework. The theory of behavior dynamics instantiates abstractly the idea that behavior is selected by its consequences. It implements Darwinian principles of selection, reproduction, and mutation to generate adaptive behavior in virtual organisms. The behavior generated by the theory has been shown to be quantitatively indistinguishable from that of live organisms. The theory of neuronal group selection suggests a mechanism whereby the abstract principles of the evolutionary theory may be implemented in the nervous systems of biological organisms. According to this theory, groups of neurons subserving behavior may be selected by synaptic modifications that occur when the consequences of behavior activate value systems in the brain. Together, these theories constitute a framework for a comprehensive account of adaptive behavior that extends from brain function to the behavior of whole organisms in quantitative detail.

  6. Inversion for Refractivity Parameters Using a Dynamic Adaptive Cuckoo Search with Crossover Operator Algorithm.

    Science.gov (United States)

    Zhang, Zhihua; Sheng, Zheng; Shi, Hanqing; Fan, Zhiqiang

    2016-01-01

    Using the RFC technique to estimate refractivity parameters is a complex nonlinear optimization problem. In this paper, an improved cuckoo search (CS) algorithm is proposed to deal with this problem. To enhance the performance of the CS algorithm, a parameter dynamic adaptive operation and crossover operation were integrated into the standard CS (DACS-CO). Rechenberg's 1/5 criteria combined with learning factor were used to control the parameter dynamic adaptive adjusting process. The crossover operation of genetic algorithm was utilized to guarantee the population diversity. The new hybrid algorithm has better local search ability and contributes to superior performance. To verify the ability of the DACS-CO algorithm to estimate atmospheric refractivity parameters, the simulation data and real radar clutter data are both implemented. The numerical experiments demonstrate that the DACS-CO algorithm can provide an effective method for near-real-time estimation of the atmospheric refractivity profile from radar clutter.

  7. Inversion for Refractivity Parameters Using a Dynamic Adaptive Cuckoo Search with Crossover Operator Algorithm

    Directory of Open Access Journals (Sweden)

    Zhihua Zhang

    2016-01-01

    Full Text Available Using the RFC technique to estimate refractivity parameters is a complex nonlinear optimization problem. In this paper, an improved cuckoo search (CS algorithm is proposed to deal with this problem. To enhance the performance of the CS algorithm, a parameter dynamic adaptive operation and crossover operation were integrated into the standard CS (DACS-CO. Rechenberg’s 1/5 criteria combined with learning factor were used to control the parameter dynamic adaptive adjusting process. The crossover operation of genetic algorithm was utilized to guarantee the population diversity. The new hybrid algorithm has better local search ability and contributes to superior performance. To verify the ability of the DACS-CO algorithm to estimate atmospheric refractivity parameters, the simulation data and real radar clutter data are both implemented. The numerical experiments demonstrate that the DACS-CO algorithm can provide an effective method for near-real-time estimation of the atmospheric refractivity profile from radar clutter.

  8. HyFIS: adaptive neuro-fuzzy inference systems and their application to nonlinear dynamical systems.

    Science.gov (United States)

    Kim, J; Kasabov, N

    1999-11-01

    This paper proposes an adaptive neuro-fuzzy system, HyFIS (Hybrid neural Fuzzy Inference System), for building and optimising fuzzy models. The proposed model introduces the learning power of neural networks to fuzzy logic systems and provides linguistic meaning to the connectionist architectures. Heuristic fuzzy logic rules and input-output fuzzy membership functions can be optimally tuned from training examples by a hybrid learning scheme comprised of two phases: rule generation phase from data; and rule tuning phase using error backpropagation learning scheme for a neural fuzzy system. To illustrate the performance and applicability of the proposed neuro-fuzzy hybrid model, extensive simulation studies of nonlinear complex dynamic systems are carried out. The proposed method can be applied to an on-line incremental adaptive learning for the prediction and control of nonlinear dynamical systems. Two benchmark case studies are used to demonstrate that the proposed HyFIS system is a superior neuro-fuzzy modelling technique.

  9. Adaptive RBFNN Formation Control of Multi-mobile Robots with Actuator Dynamics

    Directory of Open Access Journals (Sweden)

    Li Yan-dong

    2013-04-01

    Full Text Available We study the problem of formation control and trajectory tracking for multiple nonholonomic mobile robots with actuator and formation dynamics. An adaptive neural-network (NN control strategy that integrated kinematic controller with input voltages controller of actuator was proposed. A control law was designed by backstepping technique based on separation-bearing formation control structure of leader-follower. The radial basis function neural network (RBFNN was adopted to achieve on-line estimation for the dynamics nonlinear uncertain part for follower and leader robots. The adaptive robust controller was adopted to compensate modeling errors of NN. This strategy not only overcomed all kinds of uncertainties of mobile robots, but also ensured the desired trajectory tracking of robot formation in the case of maintaining formation. The stability and convergence of the control system were proved by using the Lyapunov theory. The simulation results showed the effectiveness of this proposed method.

  10. Chaos Synchronization Using Adaptive Dynamic Neural Network Controller with Variable Learning Rates

    Directory of Open Access Journals (Sweden)

    Chih-Hong Kao

    2011-01-01

    Full Text Available This paper addresses the synchronization of chaotic gyros with unknown parameters and external disturbance via an adaptive dynamic neural network control (ADNNC system. The proposed ADNNC system is composed of a neural controller and a smooth compensator. The neural controller uses a dynamic RBF (DRBF network to online approximate an ideal controller. The DRBF network can create new hidden neurons online if the input data falls outside the hidden layer and prune the insignificant hidden neurons online if the hidden neuron is inappropriate. The smooth compensator is designed to compensate for the approximation error between the neural controller and the ideal controller. Moreover, the variable learning rates of the parameter adaptation laws are derived based on a discrete-type Lyapunov function to speed up the convergence rate of the tracking error. Finally, the simulation results which verified the chaotic behavior of two nonlinear identical chaotic gyros can be synchronized using the proposed ADNNC scheme.

  11. Dynamic Optimal CCI Weight Channel Pre-evaluative Assignment in Adaptive Array Antenna System

    Institute of Scientific and Technical Information of China (English)

    MENG Weixiao; ZHANG Naitong

    2001-01-01

    Dynamic Channel Assignment (DCA)together with Adaptive Array Antenna (AAA) takes an important part in cellular mobile communication system. In this paper, a conception of co-channel in terference (CCI) quantification is advanced in multicell 8-element circular adaptive array antenna system.Normalized CCI weight relational expression, which is concerned in distance and look angle difference is sublimed from experiential sampling, induction and non-linear fitting. Then an algorithm of optimal CCI weight channel pre-evaluation is proposed as a solution of dynamic channel assignment. The least sum of weight value before assignment is used to pre-evaluate the performance of all the channels. Based on an approached practical cellular model, a series of systemclassed simulations are accomplished. Simulation resuits show that this algorithm is quite effective: system capacity is increased greatly; traffic block probabilities are decreased remarkably; nice channel quality is maintained; the reliability of DCA is enhanced; the higher frequency utilization efficiency is also obtained.

  12. A Discontinuous Galerkin Time-Domain Method with Dynamically Adaptive Cartesian Meshes for Computational Electromagnetics

    CERN Document Server

    Yan, Su; Arslanbekov, Robert R; Kolobov, Vladimir I; Jin, Jian-Ming

    2016-01-01

    A discontinuous Galerkin time-domain (DGTD) method based on dynamically adaptive Cartesian meshes (ACM) is developed for a full-wave analysis of electromagnetic fields in dispersive media. Hierarchical Cartesian grids offer simplicity close to that of structured grids and the flexibility of unstructured grids while being highly suited for adaptive mesh refinement (AMR). The developed DGTD-ACM achieves a desired accuracy by refining non-conformal meshes near material interfaces to reduce stair-casing errors without sacrificing the high efficiency afforded with uniform Cartesian meshes. Moreover, DGTD-ACM can dynamically refine the mesh to resolve the local variation of the fields during propagation of electromagnetic pulses. A local time-stepping scheme is adopted to alleviate the constraint on the time-step size due to the stability condition of the explicit time integration. Simulations of electromagnetic wave diffraction over conducting and dielectric cylinders and spheres demonstrate that the proposed meth...

  13. Adaptive block dynamic surface control for integrated missile guidance and autopilot

    Institute of Scientific and Technical Information of China (English)

    Hou Mingzhe; Liang Xiaoling; Duan Guangren

    2013-01-01

    A novel integrated guidance and autopilot design method is proposed for homing missiles based on the adaptive block dynamic surface control approach.The fully integrated guidance and autopilot model is established by combining the nonlinear missile dynamics with the nonlinear dynamics describing the pursuit situation of a missile and a target in the three-dimensional space.The integrated guidance and autopilot design problem is further converted to a state regulation problem of a time-varying nonlinear system with matched and unmatched uncertainties.A new and simple adaptive block dynamic surface control algorithm is proposed to address such a state regulation problem.The stability of the closed-loop system is proven based on the Lyapunov theory.The six degrees of freedom (6DOF) nonlinear numerical simulation results show that the proposed integrated guidance and autopilot algorithm can ensure the accuracy of target interception and the robust stability of the closed-loop system with respect to the uncertainties in the missile dynamics

  14. Adaptive Leader-Following Consensus of Multi-Agent Systems with Unknown Nonlinear Dynamics

    Directory of Open Access Journals (Sweden)

    Junwei Wang

    2014-09-01

    Full Text Available This paper deals with the leader-following consensus of multi-agent systems with matched nonlinear dynamics. Compared with previous works, the major difficulty here is caused by the simultaneous existence of nonidentical agent dynamics and unknown system parameters, which are more practical in real-world applications. To tackle this difficulty, a distributed adaptive control law for each follower is proposed based on algebraic graph theory and algebraic Riccati equation. By a Lyapunov function method, we show that the designed control law guarantees that each follower asymptotically converges to the leader under connected communication graphs. A simulation example demonstrates the effectiveness of the proposed scheme.

  15. Dynamically adaptive Lattice Boltzmann simulation of shallow water flows with the Peano framework

    KAUST Repository

    Neumann, Philipp

    2015-09-01

    © 2014 Elsevier Inc. All rights reserved. We present a dynamically adaptive Lattice Boltzmann (LB) implementation for solving the shallow water equations (SWEs). Our implementation extends an existing LB component of the Peano framework. We revise the modular design with respect to the incorporation of new simulation aspects and LB models. The basic SWE-LB implementation is validated in different breaking dam scenarios. We further provide a numerical study on stability of the MRT collision operator used in our simulations.

  16. A dynamic Fourier series for the compression of ECG using FFT and adaptive coefficient estimation.

    Science.gov (United States)

    al-Nashash, H A

    1995-04-01

    In this article, a new ECG data compression technique is proposed. The method relies on modelling quasi-periodic ECG signals as a dynamic Fourier series. Fourier coefficients are continuously estimated using either an FFT algorithm or the adaptive least mean square algorithm. Results from simulated normal and pathological ECGs are presented and discussed. The merits of each of the above two methods are also illustrated. Furthermore, a comparison with other compression techniques is also discussed.

  17. Adaptive, High-Order, and Scalable Software Elements for Dynamic Rupture Simulations in Complex Geometries

    Science.gov (United States)

    Kozdon, J. E.; Wilcox, L.; Aranda, A. R.

    2014-12-01

    The goal of this work is to develop a new set of simulation tools for earthquake rupture dynamics based on state-of-the-art high-order, adaptive numerical methods capable of handling complex geometries. High-order methods are ideal for earthquake rupture simulations as the problems are wave-dominated and the waves excited in simulations propagate over distance much larger than their fundamental wavelength. When high-order methods are used for such problems significantly fewer degrees of freedom are required as compared with low-order methods. The base numerical method in our new software elements is a discontinuous Galerkin method based on curved, Kronecker product hexahedral elements. We currently use MPI for off-node parallelism and are in the process of exploring strategies for on-node parallelism. Spatial mesh adaptivity is handled using the p4est library and temporal adaptivity is achieved through an Adams-Bashforth based local time stepping method; we are presently in the process of including dynamic spatial adaptivity which we believe will be valuable for capturing the small-scale features around the propagating rupture front. One of the key features of our software elements is that the method is provably stable, even after the inclusion of the nonlinear frictions laws which govern rupture dynamics. In this presentation we will both outline the structure of the software elements as well as validate the rupture dynamics with SCEC benchmark test problems. We are also presently developing several realistic simulation geometries which may also be reported on. Finally, the software elements that we have designed are fully public domain and have been designed with tightly coupled, wave dominated multiphysics applications in mind. This latter design decisions means the software elements are applicable to many other geophysical and non-geophysical applications.

  18. Some fundamental problems for an energy conserving adaptive resolution molecular dynamics scheme

    OpenAIRE

    Site, L. Delle

    2007-01-01

    Adaptive resolution molecular dynamics (MD) schemes allow for changing the number of degrees of freedom on the fly and preserve the free exchange of particles between regions of different resolution. There are two main alternatives on how to design the algorithm to switch resolution using auxiliary ''switching'' functions; force based and potential energy based approach. In this work we show that, in the framework of classical MD, the latter presents fundamental conceptual problems which make...

  19. Structure identification and adaptive synchronization of uncertain general complex dynamical networks

    Energy Technology Data Exchange (ETDEWEB)

    Xu Yuhua, E-mail: yuhuaxu2004@163.co [College of Information Science and Technology, Donghua University, Shanghai 201620 (China) and Department of Maths, Yunyang Teacher' s College, Hubei 442000 (China); Zhou Wuneng, E-mail: wnzhou@163.co [College of Information Science and Technology, Donghua University, Shanghai 201620 (China); Fang Jian' an [College of Information Science and Technology, Donghua University, Shanghai 201620 (China); Lu Hongqian [Shandong Institute of Light Industry, Shandong Jinan 250353 (China)

    2009-12-28

    This Letter proposes an approach to identify the topological structure and unknown parameters for uncertain general complex networks simultaneously. By designing effective adaptive controllers, we achieve synchronization between two complex networks. The unknown network topological structure and system parameters of uncertain general complex dynamical networks are identified simultaneously in the process of synchronization. Several useful criteria for synchronization are given. Finally, an illustrative example is presented to demonstrate the application of the theoretical results.

  20. Dynamic learning from adaptive neural network control of a class of nonaffine nonlinear systems.

    Science.gov (United States)

    Dai, Shi-Lu; Wang, Cong; Wang, Min

    2014-01-01

    This paper studies the problem of learning from adaptive neural network (NN) control of a class of nonaffine nonlinear systems in uncertain dynamic environments. In the control design process, a stable adaptive NN tracking control design technique is proposed for the nonaffine nonlinear systems with a mild assumption by combining a filtered tracking error with the implicit function theorem, input-to-state stability, and the small-gain theorem. The proposed stable control design technique not only overcomes the difficulty in controlling nonaffine nonlinear systems but also relaxes constraint conditions of the considered systems. In the learning process, the partial persistent excitation (PE) condition of radial basis function NNs is satisfied during tracking control to a recurrent reference trajectory. Under the PE condition and an appropriate state transformation, the proposed adaptive NN control is shown to be capable of acquiring knowledge on the implicit desired control input dynamics in the stable control process and of storing the learned knowledge in memory. Subsequently, an NN learning control design technique that effectively exploits the learned knowledge without re-adapting to the controller parameters is proposed to achieve closed-loop stability and improved control performance. Simulation studies are performed to demonstrate the effectiveness of the proposed design techniques.

  1. Altered temporal dynamics of neural adaptation in the aging human auditory cortex.

    Science.gov (United States)

    Herrmann, Björn; Henry, Molly J; Johnsrude, Ingrid S; Obleser, Jonas

    2016-09-01

    Neural response adaptation plays an important role in perception and cognition. Here, we used electroencephalography to investigate how aging affects the temporal dynamics of neural adaptation in human auditory cortex. Younger (18-31 years) and older (51-70 years) normal hearing adults listened to tone sequences with varying onset-to-onset intervals. Our results show long-lasting neural adaptation such that the response to a particular tone is a nonlinear function of the extended temporal history of sound events. Most important, aging is associated with multiple changes in auditory cortex; older adults exhibit larger and less variable response magnitudes, a larger dynamic response range, and a reduced sensitivity to temporal context. Computational modeling suggests that reduced adaptation recovery times underlie these changes in the aging auditory cortex and that the extended temporal stimulation has less influence on the neural response to the current sound in older compared with younger individuals. Our human electroencephalography results critically narrow the gap to animal electrophysiology work suggesting a compensatory release from cortical inhibition accompanying hearing loss and aging.

  2. Block Fusion on Dynamically Adaptive Spacetree Grids for Shallow Water Waves

    KAUST Repository

    Weinzierl, Tobias

    2014-09-01

    © 2014 World Scientific Publishing Company. Spacetrees are a popular formalism to describe dynamically adaptive Cartesian grids. Even though they directly yield a mesh, it is often computationally reasonable to embed regular Cartesian blocks into their leaves. This promotes stencils working on homogeneous data chunks. The choice of a proper block size is sensitive. While large block sizes foster loop parallelism and vectorisation, they restrict the adaptivity\\'s granularity and hence increase the memory footprint and lower the numerical accuracy per byte. In the present paper, we therefore use a multiscale spacetree-block coupling admitting blocks on all spacetree nodes. We propose to find sets of blocks on the finest scale throughout the simulation and to replace them by fused big blocks. Such a replacement strategy can pick up hardware characteristics, i.e. which block size yields the highest throughput, while the dynamic adaptivity of the fine grid mesh is not constrained - applications can work with fine granular blocks. We study the fusion with a state-of-the-art shallow water solver at hands of an Intel Sandy Bridge and a Xeon Phi processor where we anticipate their reaction to selected block optimisation and vectorisation.

  3. Molecular Mechanisms That Underlie the Dynamic Adaptation of Innate Monocyte Memory to Varying Stimulant Strength of TLR Ligands.

    Science.gov (United States)

    Yuan, Ruoxi; Geng, Shuo; Li, Liwu

    2016-01-01

    In adaptation to rising stimulant strength, innate monocytes can be dynamically programed to preferentially express either pro- or anti-inflammatory mediators. Such dynamic innate adaptation or programing may bear profound relevance in host health and disease. However, molecular mechanisms that govern innate adaptation to varying strength of stimulants are not well understood. Using lipopolysaccharide (LPS), the model stimulant of toll-like-receptor 4 (TLR4), we reported that the expressions of pro-inflammatory mediators are preferentially sustained in monocytes adapted by lower doses of LPS, and suppressed/tolerized in monocytes adapted by higher doses of LPS. Mechanistically, monocytes adapted by super-low dose LPS exhibited higher levels of transcription factor, interferon regulatory factor 5 (IRF5), and reduced levels of transcriptional modulator B lymphocyte-induced maturation protein-1 (Blimp-1). Intriguingly, the inflammatory monocyte adaptation by super-low dose LPS is dependent upon TRAM/TRIF but not MyD88. Similar to LPS, we also observed biphasic inflammatory adaptation and tolerance in monocytes challenged with varying dosages of TLR7 agonist. In sharp contrast, rising doses of TLR3 agonist preferentially caused inflammatory adaptation without inducing tolerance. At the molecular level, the differential regulation of IRF5 and Blimp-1 coincides with unique monocyte adaptation dynamics by TLR4/7 and TLR3 agonists. Our study provides novel clue toward the understanding of monocyte adaptation and memory toward distinct TLR ligands.

  4. Update on Small Modular Reactors Dynamics System Modeling Tool -- Molten Salt Cooled Architecture

    Energy Technology Data Exchange (ETDEWEB)

    Hale, Richard Edward [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Cetiner, Sacit M. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Fugate, David L. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Qualls, A L. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Borum, Robert C. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Chaleff, Ethan S. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Rogerson, Doug W. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Batteh, John J. [Modelon Corporation (Sweden); Tiller, Michael M. [Xogeny Corporation, Canton, MI (United States)

    2014-08-01

    The Small Modular Reactor (SMR) Dynamic System Modeling Tool project is in the third year of development. The project is designed to support collaborative modeling and study of various advanced SMR (non-light water cooled) concepts, including the use of multiple coupled reactors at a single site. The objective of the project is to provide a common simulation environment and baseline modeling resources to facilitate rapid development of dynamic advanced reactor SMR models, ensure consistency among research products within the Instrumentation, Controls, and Human-Machine Interface (ICHMI) technical area, and leverage cross-cutting capabilities while minimizing duplication of effort. The combined simulation environment and suite of models are identified as the Modular Dynamic SIMulation (MoDSIM) tool. The critical elements of this effort include (1) defining a standardized, common simulation environment that can be applied throughout the program, (2) developing a library of baseline component modules that can be assembled into full plant models using existing geometry and thermal-hydraulic data, (3) defining modeling conventions for interconnecting component models, and (4) establishing user interfaces and support tools to facilitate simulation development (i.e., configuration and parameterization), execution, and results display and capture.

  5. Dynamic adaptation process to implement an evidence-based child maltreatment intervention

    Directory of Open Access Journals (Sweden)

    Aarons Gregory A

    2012-04-01

    Full Text Available Abstract Background Adaptations are often made to evidence-based practices (EBPs by systems, organizations, and/or service providers in the implementation process. The degree to which core elements of an EBP can be maintained while allowing for local adaptation is unclear. In addition, adaptations may also be needed at the system, policy, or organizational levels to facilitate EBP implementation and sustainment. This paper describes a study of the feasibility and acceptability of an implementation approach, the Dynamic Adaptation Process (DAP, designed to allow for EBP adaptation and system and organizational adaptations in a planned and considered, rather than ad hoc, way. The DAP involves identifying core elements and adaptable characteristics of an EBP, then supporting implementation with specific training on allowable adaptations to the model, fidelity monitoring and support, and identifying the need for and solutions to system and organizational adaptations. In addition, this study addresses a secondary concern, that of improving EBP model fidelity assessment and feedback in real-world settings. Methods This project examines the feasibility, acceptability, and utility of the DAP; tests the degree to which fidelity can be maintained using the DAP compared to implementation as usual (IAU; and examines the feasibility of using automated phone or internet-enabled, computer-based technology to assess intervention fidelity and client satisfaction. The study design incorporates mixed methods in order to describe processes and factors associated with variations in both how the DAP itself is implemented and how the DAP impacts fidelity, drift, and adaptation. The DAP model is to be examined by assigning six regions in California (USA to either the DAP (n = 3 or IAU (n = 3 to implement an EBP to prevent child neglect. Discussion The DAP represents a data-informed, collaborative, multiple stakeholder approach to maintain intervention fidelity

  6. Adaptive optimal control of highly dissipative nonlinear spatially distributed processes with neuro-dynamic programming.

    Science.gov (United States)

    Luo, Biao; Wu, Huai-Ning; Li, Han-Xiong

    2015-04-01

    Highly dissipative nonlinear partial differential equations (PDEs) are widely employed to describe the system dynamics of industrial spatially distributed processes (SDPs). In this paper, we consider the optimal control problem of the general highly dissipative SDPs, and propose an adaptive optimal control approach based on neuro-dynamic programming (NDP). Initially, Karhunen-Loève decomposition is employed to compute empirical eigenfunctions (EEFs) of the SDP based on the method of snapshots. These EEFs together with singular perturbation technique are then used to obtain a finite-dimensional slow subsystem of ordinary differential equations that accurately describes the dominant dynamics of the PDE system. Subsequently, the optimal control problem is reformulated on the basis of the slow subsystem, which is further converted to solve a Hamilton-Jacobi-Bellman (HJB) equation. HJB equation is a nonlinear PDE that has proven to be impossible to solve analytically. Thus, an adaptive optimal control method is developed via NDP that solves the HJB equation online using neural network (NN) for approximating the value function; and an online NN weight tuning law is proposed without requiring an initial stabilizing control policy. Moreover, by involving the NN estimation error, we prove that the original closed-loop PDE system with the adaptive optimal control policy is semiglobally uniformly ultimately bounded. Finally, the developed method is tested on a nonlinear diffusion-convection-reaction process and applied to a temperature cooling fin of high-speed aerospace vehicle, and the achieved results show its effectiveness.

  7. Evolution dynamics of a model for gene duplication under adaptive conflict

    Science.gov (United States)

    Ancliff, Mark; Park, Jeong-Man

    2014-06-01

    We present and solve the dynamics of a model for gene duplication showing escape from adaptive conflict. We use a Crow-Kimura quasispecies model of evolution where the fitness landscape is a function of Hamming distances from two reference sequences, which are assumed to optimize two different gene functions, to describe the dynamics of a mixed population of individuals with single and double copies of a pleiotropic gene. The evolution equations are solved through a spin coherent state path integral, and we find two phases: one is an escape from an adaptive conflict phase, where each copy of a duplicated gene evolves toward subfunctionalization, and the other is a duplication loss of function phase, where one copy maintains its pleiotropic form and the other copy undergoes neutral mutation. The phase is determined by a competition between the fitness benefits of subfunctionalization and the greater mutational load associated with maintaining two gene copies. In the escape phase, we find a dynamics of an initial population of single gene sequences only which escape adaptive conflict through gene duplication and find that there are two time regimes: until a time t* single gene sequences dominate, and after t* double gene sequences outgrow single gene sequences. The time t* is identified as the time necessary for subfunctionalization to evolve and spread throughout the double gene sequences, and we show that there is an optimum mutation rate which minimizes this time scale.

  8. Complex ordering in spin networks: Critical role of adaptation rate for dynamically evolving interactions

    Science.gov (United States)

    Pathak, Anand; Sinha, Sitabhra

    2015-09-01

    Many complex systems can be represented as networks of dynamical elements whose states evolve in response to interactions with neighboring elements, noise and external stimuli. The collective behavior of such systems can exhibit remarkable ordering phenomena such as chimera order corresponding to coexistence of ordered and disordered regions. Often, the interactions in such systems can also evolve over time responding to changes in the dynamical states of the elements. Link adaptation inspired by Hebbian learning, the dominant paradigm for neuronal plasticity, has been earlier shown to result in structural balance by removing any initial frustration in a system that arises through conflicting interactions. Here we show that the rate of the adaptive dynamics for the interactions is crucial in deciding the emergence of different ordering behavior (including chimera) and frustration in networks of Ising spins. In particular, we observe that small changes in the link adaptation rate about a critical value result in the system exhibiting radically different energy landscapes, viz., smooth landscape corresponding to balanced systems seen for fast learning, and rugged landscapes corresponding to frustrated systems seen for slow learning.

  9. Innate and adaptive immunity in the development of depression: An update on current knowledge and technological advances.

    Science.gov (United States)

    Haapakoski, Rita; Ebmeier, Klaus P; Alenius, Harri; Kivimäki, Mika

    2016-04-01

    The inflammation theory of depression, proposed over 20years ago, was influenced by early studies on T cell responses and since then has been a stimulus for numerous research projects aimed at understanding the relationship between immune function and depression. Observational studies have shown that indicators of immunity, especially C reactive protein and proinflammatory cytokines, such as interleukin 6, are associated with an increased risk of depressive disorders, although the evidence from randomized trials remains limited and only few studies have assessed the interplay between innate and adaptive immunity in depression. In this paper, we review current knowledge on the interactions between central and peripheral innate and adaptive immune molecules and the potential role of immune-related activation of microglia, inflammasomes and indoleamine-2,3-dioxygenase in the development of depressive symptoms. We highlight how combining basic immune methods with more advanced 'omics' technologies would help us to make progress in unravelling the complex associations between altered immune function and depressive disorders, in the identification of depression-specific biomarkers and in developing immunotherapeutic treatment strategies that take individual variability into account.

  10. Adaptive Landscape by Environment Interactions Dictate Evolutionary Dynamics in Models of Drug Resistance.

    Directory of Open Access Journals (Sweden)

    C Brandon Ogbunugafor

    2016-01-01

    Full Text Available The adaptive landscape analogy has found practical use in recent years, as many have explored how their understanding can inform therapeutic strategies that subvert the evolution of drug resistance. A major barrier to applications of these concepts is a lack of detail concerning how the environment affects adaptive landscape topography, and consequently, the outcome of drug treatment. Here we combine empirical data, evolutionary theory, and computer simulations towards dissecting adaptive landscape by environment interactions for the evolution of drug resistance in two dimensions-drug concentration and drug type. We do so by studying the resistance mediated by Plasmodium falciparum dihydrofolate reductase (DHFR to two related inhibitors-pyrimethamine and cycloguanil-across a breadth of drug concentrations. We first examine whether the adaptive landscapes for the two drugs are consistent with common definitions of cross-resistance. We then reconstruct all accessible pathways across the landscape, observing how their structure changes with drug environment. We offer a mechanism for non-linearity in the topography of accessible pathways by calculating of the interaction between mutation effects and drug environment, which reveals rampant patterns of epistasis. We then simulate evolution in several different drug environments to observe how these individual mutation effects (and patterns of epistasis influence paths taken at evolutionary "forks in the road" that dictate adaptive dynamics in silico. In doing so, we reveal how classic metrics like the IC50 and minimal inhibitory concentration (MIC are dubious proxies for understanding how evolution will occur across drug environments. We also consider how the findings reveal ambiguities in the cross-resistance concept, as subtle differences in adaptive landscape topography between otherwise equivalent drugs can drive drastically different evolutionary outcomes. Summarizing, we discuss the results with

  11. Adaptive Landscape by Environment Interactions Dictate Evolutionary Dynamics in Models of Drug Resistance.

    Science.gov (United States)

    Ogbunugafor, C Brandon; Wylie, C Scott; Diakite, Ibrahim; Weinreich, Daniel M; Hartl, Daniel L

    2016-01-01

    The adaptive landscape analogy has found practical use in recent years, as many have explored how their understanding can inform therapeutic strategies that subvert the evolution of drug resistance. A major barrier to applications of these concepts is a lack of detail concerning how the environment affects adaptive landscape topography, and consequently, the outcome of drug treatment. Here we combine empirical data, evolutionary theory, and computer simulations towards dissecting adaptive landscape by environment interactions for the evolution of drug resistance in two dimensions-drug concentration and drug type. We do so by studying the resistance mediated by Plasmodium falciparum dihydrofolate reductase (DHFR) to two related inhibitors-pyrimethamine and cycloguanil-across a breadth of drug concentrations. We first examine whether the adaptive landscapes for the two drugs are consistent with common definitions of cross-resistance. We then reconstruct all accessible pathways across the landscape, observing how their structure changes with drug environment. We offer a mechanism for non-linearity in the topography of accessible pathways by calculating of the interaction between mutation effects and drug environment, which reveals rampant patterns of epistasis. We then simulate evolution in several different drug environments to observe how these individual mutation effects (and patterns of epistasis) influence paths taken at evolutionary "forks in the road" that dictate adaptive dynamics in silico. In doing so, we reveal how classic metrics like the IC50 and minimal inhibitory concentration (MIC) are dubious proxies for understanding how evolution will occur across drug environments. We also consider how the findings reveal ambiguities in the cross-resistance concept, as subtle differences in adaptive landscape topography between otherwise equivalent drugs can drive drastically different evolutionary outcomes. Summarizing, we discuss the results with regards to their

  12. Adaptive Landscape by Environment Interactions Dictate Evolutionary Dynamics in Models of Drug Resistance

    Science.gov (United States)

    Ogbunugafor, C. Brandon; Wylie, C. Scott; Diakite, Ibrahim; Weinreich, Daniel M.; Hartl, Daniel L.

    2016-01-01

    The adaptive landscape analogy has found practical use in recent years, as many have explored how their understanding can inform therapeutic strategies that subvert the evolution of drug resistance. A major barrier to applications of these concepts is a lack of detail concerning how the environment affects adaptive landscape topography, and consequently, the outcome of drug treatment. Here we combine empirical data, evolutionary theory, and computer simulations towards dissecting adaptive landscape by environment interactions for the evolution of drug resistance in two dimensions—drug concentration and drug type. We do so by studying the resistance mediated by Plasmodium falciparum dihydrofolate reductase (DHFR) to two related inhibitors—pyrimethamine and cycloguanil—across a breadth of drug concentrations. We first examine whether the adaptive landscapes for the two drugs are consistent with common definitions of cross-resistance. We then reconstruct all accessible pathways across the landscape, observing how their structure changes with drug environment. We offer a mechanism for non-linearity in the topography of accessible pathways by calculating of the interaction between mutation effects and drug environment, which reveals rampant patterns of epistasis. We then simulate evolution in several different drug environments to observe how these individual mutation effects (and patterns of epistasis) influence paths taken at evolutionary “forks in the road” that dictate adaptive dynamics in silico. In doing so, we reveal how classic metrics like the IC50 and minimal inhibitory concentration (MIC) are dubious proxies for understanding how evolution will occur across drug environments. We also consider how the findings reveal ambiguities in the cross-resistance concept, as subtle differences in adaptive landscape topography between otherwise equivalent drugs can drive drastically different evolutionary outcomes. Summarizing, we discuss the results with

  13. Update of the 2 Kw Solar Dynamic Ground Test Demonstration Program

    Science.gov (United States)

    Shaltens, Richard K.; Boyle, Robert V.

    1994-01-01

    The Solar Dynamic (SD) Ground Test Demonstration (GTD) program demonstrates the operation of a complete 2 kW, SD system in a simulated space environment at a NASA Lewis Research Center (LeRC) thermal-vacuum facility. This paper reviews the goals and status of the SD GTD program. A brief description of the SD system identifying key design features of the system, subsystems, and components is included. An aerospace industry/government team is working together to design, fabricate, assemble, and test a complete SD system.

  14. Discussion on Dynamic Updating Mechanism of Continental Coastline%大陆海岸线动态更新机制探讨

    Institute of Scientific and Technical Information of China (English)

    罗美雪; 张加晋; 任岳森

    2016-01-01

    The delimitation of continental coastline provides the boundary of legal significance for the administration of sea area.Influenced by natural factors and human factors,the coastline is in a dynamic change.This paper used map grid to calculate the change rate of continental coastline, and selected the dynamic updating method to update the coastline.The following key issues should be solved to establish the dynamic updating mechanism of coastline,including the ways to obtain the data reflecting the change in coastline,the standard and the quality control of the upda-ting data,the implementation and the release of the updated coastline data.%大陆海岸线的划定为海域管理提供具有法律地位的海陆边界,然而受自然因素和人为因素的双重影响,海岸线处于动态变化之中,其现势性影响其使用价值。文章提出利用地图格网统计法计算海岸线变化率并对大陆海岸线进行动态更新,从数据资料的获取、数据的质量评价和标准、数据更新的实施和发布等方面提出建立海岸线动态更新机制的建议。

  15. Power-law dynamics in an auditory-nerve model can account for neural adaptation to sound-level statistics.

    Science.gov (United States)

    Zilany, Muhammad S A; Carney, Laurel H

    2010-08-04

    Neurons in the auditory system respond to recent stimulus-level history by adapting their response functions according to the statistics of the stimulus, partially alleviating the so-called "dynamic-range problem." However, the mechanism and source of this adaptation along the auditory pathway remain unknown. Inclusion of power-law dynamics in a phenomenological model of the inner hair cell (IHC)-auditory nerve (AN) synapse successfully explained neural adaptation to sound-level statistics, including the time course of adaptation of the mean firing rate and changes in the dynamic range observed in AN responses. A direct comparison between model responses to a dynamic stimulus and to an "inversely gated" static background suggested that AN dynamic-range adaptation largely results from the adaptation produced by the response history. These results support the hypothesis that the potential mechanism underlying the dynamic-range adaptation observed at the level of the auditory nerve is located peripheral to the spike generation mechanism and central to the IHC receptor potential.

  16. Differential flatness properties and multivariable adaptive control of ovarian system dynamics

    Science.gov (United States)

    Rigatos, Gerasimos

    2016-12-01

    The ovarian system exhibits nonlinear dynamics which is modeled by a set of coupled nonlinear differential equations. The paper proposes adaptive fuzzy control based on differential flatness theory for the complex dynamics of the ovarian system. It is proven that the dynamic model of the ovarian system, having as state variables the LH and the FSH hormones and their derivatives, is a differentially flat one. This means that all its state variables and its control inputs can be described as differential functions of the flat output. By exploiting differential flatness properties the system's dynamic model is written in the multivariable linear canonical (Brunovsky) form, for which the design of a state feedback controller becomes possible. After this transformation, the new control inputs of the system contain unknown nonlinear parts, which are identified with the use of neurofuzzy approximators. The learning procedure for these estimators is determined by the requirement the first derivative of the closed-loop's Lyapunov function to be a negative one. Moreover, Lyapunov stability analysis shows that H-infinity tracking performance is succeeded for the feedback control loop and this assures improved robustness to the aforementioned model uncertainty as well as to external perturbations. The efficiency of the proposed adaptive fuzzy control scheme is confirmed through simulation experiments.

  17. Adaptive workflow scheduling in grid computing based on dynamic resource availability

    Directory of Open Access Journals (Sweden)

    Ritu Garg

    2015-06-01

    Full Text Available Grid computing enables large-scale resource sharing and collaboration for solving advanced science and engineering applications. Central to the grid computing is the scheduling of application tasks to the resources. Various strategies have been proposed, including static and dynamic strategies. The former schedules the tasks to resources before the actual execution time and later schedules them at the time of execution. Static scheduling performs better but it is not suitable for dynamic grid environment. The lack of dedicated resources and variations in their availability at run time has made this scheduling a great challenge. In this study, we proposed the adaptive approach to schedule workflow tasks (dependent tasks to the dynamic grid resources based on rescheduling method. It deals with the heterogeneous dynamic grid environment, where the availability of computing nodes and links bandwidth fluctuations are inevitable due to existence of local load or load by other users. The proposed adaptive workflow scheduling (AWS approach involves initial static scheduling, resource monitoring and rescheduling with the aim to achieve the minimum execution time for workflow application. The approach differs from other techniques in literature as it considers the changes in resources (hosts and links availability and considers the impact of existing load over the grid resources. The simulation results using randomly generated task graphs and task graphs corresponding to real world problems (GE and FFT demonstrates that the proposed algorithm is able to deal with fluctuations of resource availability and provides overall optimal performance.

  18. Adaptive dynamic range optimization (ADRO): a digital amplification strategy for hearing aids and cochlear implants.

    Science.gov (United States)

    Blamey, Peter J

    2005-01-01

    Adaptive dynamic range optimization (ADRO) is an amplification strategy that uses digital signal processing techniques to improve the audibility, comfort, and intelligibility of sounds for people who use cochlear implants and/or hearing aids. The strategy uses statistical analysis to select the most information-rich section of the input dynamic range in multiple-frequency channels. Fuzzy logic rules control the gain in each frequency channel so that the selected section of the dynamic range is presented at an audible and comfortable level. The ADRO processing thus adaptively optimizes the dynamic range of the signal in multiple-frequency channels. Clinical studies show that ADRO can be fitted easily to all degrees of hearing loss for hearing aids and cochlear implants in a direct and intuitive manner, taking the preferences of the listener into account. The result is high acceptance by new and experienced hearing aid users and strong preferences for ADRO compared with alternative amplification strategies. The ADRO processing is particularly well suited to bimodal and hybrid stimulation which combine electric and acoustic stimulation in opposite ears or in the same ear, respectively.

  19. Reinforcement learning for partially observable dynamic processes: adaptive dynamic programming using measured output data.

    Science.gov (United States)

    Lewis, F L; Vamvoudakis, Kyriakos G

    2011-02-01

    Approximate dynamic programming (ADP) is a class of reinforcement learning methods that have shown their importance in a variety of applications, including feedback control of dynamical systems. ADP generally requires full information about the system internal states, which is usually not available in practical situations. In this paper, we show how to implement ADP methods using only measured input/output data from the system. Linear dynamical systems with deterministic behavior are considered herein, which are systems of great interest in the control system community. In control system theory, these types of methods are referred to as output feedback (OPFB). The stochastic equivalent of the systems dealt with in this paper is a class of partially observable Markov decision processes. We develop both policy iteration and value iteration algorithms that converge to an optimal controller that requires only OPFB. It is shown that, similar to Q -learning, the new methods have the important advantage that knowledge of the system dynamics is not needed for the implementation of these learning algorithms or for the OPFB control. Only the order of the system, as well as an upper bound on its "observability index," must be known. The learned OPFB controller is in the form of a polynomial autoregressive moving-average controller that has equivalent performance with the optimal state variable feedback gain.

  20. Discordant tasks and motor adjustments affect interactions between adaptations to altered kinematics and dynamics

    Directory of Open Access Journals (Sweden)

    Fritzie Arce

    2010-01-01

    Full Text Available Motor control and adaptation are multi-determinate processes with complex interactions. This is reflected for example in the ambiguous nature of interactions during sequential adaptation of reaching under kinematics and dynamics perturbations. It has been suggested that perturbations based on the same kinematic parameter interfere. Others posited that opposing motor adjustments underlie interference. Here, we examined the influence of discordances in task and in motor adjustments on sequential adaptations to visuomotor rotation and viscous force field perturbations. These two factors – perturbation direction and task discordance – have been examined separately by previous studies, thus the inherent difficulty to identify the roots of interference. Forty-eight human subjects adapted sequentially to one or two types of perturbations, of matched or conflicting directions. We found a gradient of interaction effects based on perturbation direction and task discordance. Perturbations of matched directions showed facilitation while perturbations of opposite directions, which required opposing motor adjustments, interfered with each other. Further, interaction effects increased with greater task discordance. We also found that force field and visuomotor rotation had mutual anterograde and retrograde effects. However, we found independence between anterograde and retrograde interferences between similar tasks. The results suggest that the newly acquired internal models of kinematic and dynamic perturbations are not independent but they share common neuronal resources and interact between them. Such overlap does not necessarily imply competition of resources. Rather, our results point to an additional principle of sensorimotor adaptation allowing the system to tap or harness common features across diverse sensory inputs and task contexts whenever available.

  1. Adaptive finite-volume WENO schemes on dynamically redistributed grids for compressible Euler equations

    Science.gov (United States)

    Pathak, Harshavardhana S.; Shukla, Ratnesh K.

    2016-08-01

    A high-order adaptive finite-volume method is presented for simulating inviscid compressible flows on time-dependent redistributed grids. The method achieves dynamic adaptation through a combination of time-dependent mesh node clustering in regions characterized by strong solution gradients and an optimal selection of the order of accuracy and the associated reconstruction stencil in a conservative finite-volume framework. This combined approach maximizes spatial resolution in discontinuous regions that require low-order approximations for oscillation-free shock capturing. Over smooth regions, high-order discretization through finite-volume WENO schemes minimizes numerical dissipation and provides excellent resolution of intricate flow features. The method including the moving mesh equations and the compressible flow solver is formulated entirely on a transformed time-independent computational domain discretized using a simple uniform Cartesian mesh. Approximations for the metric terms that enforce discrete geometric conservation law while preserving the fourth-order accuracy of the two-point Gaussian quadrature rule are developed. Spurious Cartesian grid induced shock instabilities such as carbuncles that feature in a local one-dimensional contact capturing treatment along the cell face normals are effectively eliminated through upwind flux calculation using a rotated Hartex-Lax-van Leer contact resolving (HLLC) approximate Riemann solver for the Euler equations in generalized coordinates. Numerical experiments with the fifth and ninth-order WENO reconstructions at the two-point Gaussian quadrature nodes, over a range of challenging test cases, indicate that the redistributed mesh effectively adapts to the dynamic flow gradients thereby improving the solution accuracy substantially even when the initial starting mesh is non-adaptive. The high adaptivity combined with the fifth and especially the ninth-order WENO reconstruction allows remarkably sharp capture of

  2. Grand-Canonical Adaptive Resolution Centroid Molecular Dynamics: Implementation and Application

    CERN Document Server

    Agarwal, Animesh

    2016-01-01

    We have implemented the Centroid Molecular Dynamics scheme (CMD) into the Grand Canonical-like version of the Adaptive Resolution Simulation Molecular Dynamics (GC-AdResS) method. We have tested the implementation on two different systems, liquid parahydrogen at extreme thermodynamic conditions and liquid water at ambient conditions; the reproduction of structural as well as dynamical results of reference systems are highly satisfactory. The capability of performing GC-AdResS CMD simulations allows for the treatment of a system characterized by some quantum features and open boundaries. This latter characteristic not only is of computational convenience, allowing for equivalent results of much larger and computationally more expensive systems, but also suggests a tool of analysis so far not explored, that is the unambiguous identification of the essential (quantum) degrees of freedom required for a given property.

  3. Grand-Canonical Adaptive Resolution Centroid Molecular Dynamics: Implementation and application

    Science.gov (United States)

    Agarwal, Animesh; Delle Site, Luigi

    2016-09-01

    We have implemented the Centroid Molecular Dynamics scheme (CMD) into the Grand Canonical-like version of the Adaptive Resolution Simulation Molecular Dynamics (GC-AdResS) method. We have tested the implementation on two different systems, liquid parahydrogen at extreme thermodynamic conditions and liquid water at ambient conditions; the reproduction of structural as well as dynamical results of reference systems are highly satisfactory. The capability of performing GC-AdResS CMD simulations allows for the treatment of a system characterized by some quantum features and open boundaries. This latter characteristic not only is of computational convenience, allowing for equivalent results of much larger and computationally more expensive systems, but also suggests a tool of analysis so far not explored, that is the unambiguous identification of the essential degrees of freedom required for a given property.

  4. Pairwise adaptive thermostats for improved accuracy and stability in dissipative particle dynamics

    CERN Document Server

    Leimkuhler, Benedict

    2016-01-01

    We examine the formulation and numerical treatment of dissipative particle dynamics (DPD) and momentum-conserving molecular dynamics. We show that it is possible to improve both the accuracy and the stability of DPD by employing a pairwise adaptive Langevin thermostat that precisely matches the dynamical characteristics of DPD simulations (e.g., autocorrelation functions) while automatically correcting thermodynamic averages using a negative feedback loop. In the low friction regime, it is possible to replace DPD by a simpler momentum-conserving variant of the Nos\\'{e}--Hoover--Langevin method based on thermostatting only pairwise interactions; we show that this method has an extra order of accuracy for an important class of observables (a superconvergence result), while also allowing larger timesteps than alternatives. All the methods mentioned in the article are easily implemented. Numerical experiments are performed in both equilibrium and nonequilibrium settings; using Lees--Edwards boundary conditions to...

  5. Optimal Output Regulation for Heterogeneous Multiagent Systems via Adaptive Dynamic Programming.

    Science.gov (United States)

    Zhang, Huaguang; Liang, Hongjing; Wang, Zhanshan; Feng, Tao

    2017-01-01

    In this paper, the optimal output regulation problem for partially model-free heterogeneous linear multiagent systems with disturbance generated by an exosystem is addressed by using adaptive dynamic programming and double compensator method. The topology graph for the information exchange of the agents has a spanning tree. The dynamic of individual agent is assumed to be nonidentical and of different dimensions. One distributed compensator is designed to deal with the nonidentical agents, and the other compensator is used to handle the optimal performance index. By constructing the double compensator, the distributed feedback control laws are designed to make the output of each agent synchronize with the reference output and minimize the energy of the output error simultaneously. To overcome the lack of the dynamics knowledge of each agent, a novel online policy iteration algorithm is developed to obtain the optimal feedback gain matrix. Finally, two examples are presented to illustrate the effectiveness of our results.

  6. Pairwise adaptive thermostats for improved accuracy and stability in dissipative particle dynamics

    Science.gov (United States)

    Leimkuhler, Benedict; Shang, Xiaocheng

    2016-11-01

    We examine the formulation and numerical treatment of dissipative particle dynamics (DPD) and momentum-conserving molecular dynamics. We show that it is possible to improve both the accuracy and the stability of DPD by employing a pairwise adaptive Langevin thermostat that precisely matches the dynamical characteristics of DPD simulations (e.g., autocorrelation functions) while automatically correcting thermodynamic averages using a negative feedback loop. In the low friction regime, it is possible to replace DPD by a simpler momentum-conserving variant of the Nosé-Hoover-Langevin method based on thermostatting only pairwise interactions; we show that this method has an extra order of accuracy for an important class of observables (a superconvergence result), while also allowing larger timesteps than alternatives. All the methods mentioned in the article are easily implemented. Numerical experiments are performed in both equilibrium and nonequilibrium settings; using Lees-Edwards boundary conditions to induce shear flow.

  7. Research Update: Utilizing magnetization dynamics in solid-state thermal energy conversion

    Science.gov (United States)

    Boona, Stephen R.; Watzman, Sarah J.; Heremans, Joseph P.

    2016-10-01

    We review the spin-Seebeck and magnon-electron drag effects in the context of solid-state energy conversion. These phenomena are driven by advective magnon-electron interactions. Heat flow through magnetic materials generates magnetization dynamics, which can strongly affect free electrons within or adjacent to the magnetic material, thereby producing magnetization-dependent (e.g., remnant) electric fields. The relative strength of spin-dependent interactions means that magnon-driven effects can generate significantly larger thermoelectric power factors as compared to classical thermoelectric phenomena. This is a surprising situation in which spin-based effects are larger than purely charge-based effects, potentially enabling new approaches to thermal energy conversion.

  8. Time-reversed particle dynamics calculation with field line tracing at Titan - an update

    Science.gov (United States)

    Bebesi, Zsofia; Erdos, Geza; Szego, Karoly; Juhasz, Antal; Lukacs, Katalin

    2014-05-01

    We use CAPS-IMS Singles data of Cassini measured between 2004 and 2010 to investigate the pickup process and dynamics of ions originating from Titan's atmosphere. A 4th order Runge-Kutta method was applied to calculate the test particle trajectories in a time reversed scenario, in the curved magnetic environment. We evaluated the minimum variance directions along the S/C trajectory for all Cassini flybys during which the CAPS instrument was in operation, and assumed that the field was homogeneous perpendicular to the minimum variance direction. We calculated the magnetic field lines with this method along the flyby orbits and we could determine those observational intervals when Cassini and the upper atmosphere of Titan could be magnetically connected. We used three ion species (1, 2 and 16 amu ions) for time reversed tracking, and also considered the categorization of Rymer et al. (2009) and Nemeth et al. (2011) for further features studies.

  9. Long-term dynamics of adaptive evolution in a globally important phytoplankton species to ocean acidification

    Science.gov (United States)

    Schlüter, Lothar; Lohbeck, Kai T.; Gröger, Joachim P.; Riebesell, Ulf; Reusch, Thorsten B. H.

    2016-01-01

    Marine phytoplankton may adapt to ocean change, such as acidification or warming, because of their large population sizes and short generation times. Long-term adaptation to novel environments is a dynamic process, and phenotypic change can take place thousands of generations after exposure to novel conditions. We conducted a long-term evolution experiment (4 years = 2100 generations), starting with a single clone of the abundant and widespread coccolithophore Emiliania huxleyi exposed to three different CO2 levels simulating ocean acidification (OA). Growth rates as a proxy for Darwinian fitness increased only moderately under both levels of OA [+3.4% and +4.8%, respectively, at 1100 and 2200 μatm partial pressure of CO2 (Pco2)] relative to control treatments (ambient CO2, 400 μatm). Long-term adaptation to OA was complex, and initial phenotypic responses of ecologically important traits were later reverted. The biogeochemically important trait of calcification, in particular, that had initially been restored within the first year of evolution was later reduced to levels lower than the performance of nonadapted populations under OA. Calcification was not constitutively lost but returned to control treatment levels when high CO2–adapted isolates were transferred back to present-day control CO2 conditions. Selection under elevated CO2 exacerbated a general decrease of cell sizes under long-term laboratory evolution. Our results show that phytoplankton may evolve complex phenotypic plasticity that can affect biogeochemically important traits, such as calcification. Adaptive evolution may play out over longer time scales (>1 year) in an unforeseen way under future ocean conditions that cannot be predicted from initial adaptation responses. PMID:27419227

  10. Adaptive feedback potential in dynamic stability during disturbed walking in the elderly.

    Science.gov (United States)

    Bierbaum, Stefanie; Peper, Andreas; Karamanidis, Kiros; Arampatzis, Adamantios

    2011-07-01

    After perturbation of the gait, feedback information may help regaining balance adequately, but it remains unknown whether adaptive feedback responses are possible after repetitive and unexpected perturbations during gait and if there are age-related differences. Prior experience may contribute to improved reactive behavior. Fourteen old (59-73 yrs) and fourteen young (22-31 yrs) males walked on a walkway which included one covered element. By exchanging this element participants either stepped on hard surface or unexpectedly on soft surface which caused a perturbation in gait. The gait protocol contained 5 unexpected soft trials to quantify the reactive adaptation. Each soft trial was followed by 4-8 hard trials to generate a wash-out effect. The dynamic stability was investigated by using the margin of stability (MoS), which was calculated as the difference between the anterior boundary of the base of support and the extrapolated position of the center of mass in the anterior-posterior direction. MoS at recovery leg touchdown were significantly lower in the unexpected soft trials compared to the baseline, indicating a less stable posture. However, MoS increased (p<0.05) in both groups within the disturbed trials, indicating feedback adaptive improvements. Young and old participants showed differences in the handling of the perturbation in the course of several trials. The magnitude of the reactive adaptation after the fifth unexpected perturbation was significantly different compared to the first unexpected perturbation (old: 49±30%; young: 77±40%), showing a tendency (p=0.065) for higher values in the young participants. Old individuals maintain the ability to adapt to feedback controlled perturbations. However, the locomotor behavior is more conservative compared to the young ones, leading to disadvantages in the reactive adaptation during disturbed walking.

  11. Adaptive modeling, identification, and control of dynamic structural systems. I. Theory

    Science.gov (United States)

    Safak, Erdal

    1989-01-01

    A concise review of the theory of adaptive modeling, identification, and control of dynamic structural systems based on discrete-time recordings is presented. Adaptive methods have four major advantages over the classical methods: (1) Removal of the noise from the signal is done over the whole frequency band; (2) time-varying characteristics of systems can be tracked; (3) systems with unknown characteristics can be controlled; and (4) a small segment of the data is needed during the computations. Included in the paper are the discrete-time representation of single-input single-output (SISO) systems, models for SISO systems with noise, the concept of stochastic approximation, recursive prediction error method (RPEM) for system identification, and the adaptive control. Guidelines for model selection and model validation and the computational aspects of the method are also discussed in the paper. The present paper is the first of two companion papers. The theory given in the paper is limited to that which is necessary to follow the examples for applications in structural dynamics presented in the second paper.

  12. Adaptive dynamics via Hamilton-Jacobi approach and entropy methods for a juvenile-adult model.

    Science.gov (United States)

    Carrillo, José Antonio; Cuadrado, Sílvia; Perthame, Benoît

    2007-01-01

    We consider a nonlinear system describing a juvenile-adult population undergoing small mutations. We analyze two aspects: from a mathematical point of view, we use an entropy method to prove that the population neither goes extinct nor blows-up; from an adaptive evolution point of view, we consider small mutations on a long time scale and study how a monomorphic or a dimorphic initial population evolves towards an Evolutionarily Stable State. Our method relies on an asymptotic analysis based on a constrained Hamilton-Jacobi equation. It allows to recover earlier predictions in Calsina and Cuadrado [A. Calsina, S. Cuadrado, Small mutation rate and evolutionarily stable strategies in infinite dimensional adaptive dynamics, J. Math. Biol. 48 (2004) 135; A. Calsina, S. Cuadrado, Stationary solutions of a selection mutation model: the pure mutation case, Math. Mod. Meth. Appl. Sci. 15(7) (2005) 1091.] that we also assert by direct numerical simulation. One of the interests here is to show that the Hamilton-Jacobi approach initiated in Diekmann et al. [O. Diekmann, P.-E. Jabin, S. Mischler, B. Perthame, The dynamics of adaptation: an illuminating example and a Hamilton-Jacobi approach, Theor. Popul. Biol. 67(4) (2005) 257.] extends to populations described by systems.

  13. Adaptive SLICE method: an enhanced method to determine nonlinear dynamic respiratory system mechanics.

    Science.gov (United States)

    Zhao, Zhanqi; Guttmann, Josef; Möller, Knut

    2012-01-01

    The objective of this paper is to introduce and evaluate the adaptive SLICE method (ASM) for continuous determination of intratidal nonlinear dynamic compliance and resistance. The tidal volume is subdivided into a series of volume intervals called slices. For each slice, one compliance and one resistance are calculated by applying a least-squares-fit method. The volume window (width) covered by each slice is determined based on the confidence interval of the parameter estimation. The method was compared to the original SLICE method and evaluated using simulation and animal data. The ASM was also challenged with separate analysis of dynamic compliance during inspiration. If the signal-to-noise ratio (SNR) in the respiratory data decreased from +∞ to 10 dB, the relative errors of compliance increased from 0.1% to 22% for the ASM and from 0.2% to 227% for the SLICE method. Fewer differences were found in resistance. When the SNR was larger than 40 dB, the ASM delivered over 40 parameter estimates (42.2 ± 1.3). When analyzing the compliance during inspiration separately, the estimates calculated with the ASM were more stable. The adaptive determination of slice bounds results in consistent and reliable parameter values. Online analysis of nonlinear respiratory mechanics will profit from such an adaptive selection of interval size.

  14. Dynamic Experiment Design Regularization Approach to Adaptive Imaging with Array Radar/SAR Sensor Systems

    Directory of Open Access Journals (Sweden)

    Stewart Santos

    2011-04-01

    Full Text Available We consider a problem of high-resolution array radar/SAR imaging formalized in terms of a nonlinear ill-posed inverse problem of nonparametric estimation of the power spatial spectrum pattern (SSP of the random wavefield scattered from a remotely sensed scene observed through a kernel signal formation operator and contaminated with random Gaussian noise. First, the Sobolev-type solution space is constructed to specify the class of consistent kernel SSP estimators with the reproducing kernel structures adapted to the metrics in such the solution space. Next, the “model-free” variational analysis (VA-based image enhancement approach and the “model-based” descriptive experiment design (DEED regularization paradigm are unified into a new dynamic experiment design (DYED regularization framework. Application of the proposed DYED framework to the adaptive array radar/SAR imaging problem leads to a class of two-level (DEED-VA regularized SSP reconstruction techniques that aggregate the kernel adaptive anisotropic windowing with the projections onto convex sets to enforce the consistency and robustness of the overall iterative SSP estimators. We also show how the proposed DYED regularization method may be considered as a generalization of the MVDR, APES and other high-resolution nonparametric adaptive radar sensing techniques. A family of the DYED-related algorithms is constructed and their effectiveness is finally illustrated via numerical simulations.

  15. On-Line Dynamic Index Hybrid Update Scheme Based on Self-Learning of Allocated Space%基于分配空间自学习的在线动态索引混合更新机制

    Institute of Scientific and Technical Information of China (English)

    刘小珠; 彭智勇

    2012-01-01

    To improve time and space efficiencies of index maintenance, an on-line dynamic index hybrid update (ODIHU) technique is proposed based on self-learning of allocated space. Based on Zipf theorem, ODIHU appropriately estimates the number of short and long lists with theoretical analysis, and manages short and long lists with uniform storage model of distinguishing long and short lists based on link. ODIHU manages long list space with history-based adaptive learning allocation (HALA) , and manages short list space with linear allocation (LA), exponential allocation (EA) , and uniform allocation (UA). To decrease index and retrieval cost, ODIHU divides index data set into limited sections and controls index merge with schemes. Then ODIHU merges short lists with immediate merge, and merges long lists with improved Y-limited contiguous multiple merge scheme, which balances the trade-off of the time and space efficiencies effectively. Based on the proposed RABIF, ODIHU not only considers both index level and inverted list level updating, but also effectively improves time and space efficiencies of index updating.%针对索引维护时间和空间效率低的问题,提出了一种基于分配空间自学习的在线动态索引混合更新机制(on-line dynamic index hybrid update,ODIHU).ODIHU根据Zipf分布原理对长短列表数量分布进行估计,并采用基于历史分配空间的自适应学习机制对长短列表空间进行有效管理,然后对短列表采用立即合并更新方式,长列表采用上限Y相邻多路合并的更新方式维护,实现索引更新与查询性能的有效折中.理论分析及实验结果表明,ODIHU能有效地提高索引维护与更新过程中的空间效率、索引合并与查询时间效率.

  16. Signaling and Adaptation Modulate the Dynamics of the Photosensoric Complex of Natronomonas pharaonis.

    Directory of Open Access Journals (Sweden)

    Philipp S Orekhov

    2015-10-01

    Full Text Available Motile bacteria and archaea respond to chemical and physical stimuli seeking optimal conditions for survival. To this end transmembrane chemo- and photoreceptors organized in large arrays initiate signaling cascades and ultimately regulate the rotation of flagellar motors. To unravel the molecular mechanism of signaling in an archaeal phototaxis complex we performed coarse-grained molecular dynamics simulations of a trimer of receptor/transducer dimers, namely NpSRII/NpHtrII from Natronomonas pharaonis. Signaling is regulated by a reversible methylation mechanism called adaptation, which also influences the level of basal receptor activation. Mimicking two extreme methylation states in our simulations we found conformational changes for the transmembrane region of NpSRII/NpHtrII which resemble experimentally observed light-induced changes. Further downstream in the cytoplasmic domain of the transducer the signal propagates via distinct changes in the dynamics of HAMP1, HAMP2, the adaptation domain and the binding region for the kinase CheA, where conformational rearrangements were found to be subtle. Overall these observations suggest a signaling mechanism based on dynamic allostery resembling models previously proposed for E. coli chemoreceptors, indicating similar properties of signal transduction for archaeal photoreceptors and bacterial chemoreceptors.

  17. An Adaptive Channel Access Method for Dynamic Super Dense Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Chunyang Lei

    2015-12-01

    Full Text Available Super dense and distributed wireless sensor networks have become very popular with the development of small cell technology, Internet of Things (IoT, Machine-to-Machine (M2M communications, Vehicular-to-Vehicular (V2V communications and public safety networks. While densely deployed wireless networks provide one of the most important and sustainable solutions to improve the accuracy of sensing and spectral efficiency, a new channel access scheme needs to be designed to solve the channel congestion problem introduced by the high dynamics of competing nodes accessing the channel simultaneously. In this paper, we firstly analyzed the channel contention problem using a novel normalized channel contention analysis model which provides information on how to tune the contention window according to the state of channel contention. We then proposed an adaptive channel contention window tuning algorithm in which the contention window tuning rate is set dynamically based on the estimated channel contention level. Simulation results show that our proposed adaptive channel access algorithm based on fast contention window tuning can achieve more than 95 % of the theoretical optimal throughput and 0 . 97 of fairness index especially in dynamic and dense networks.

  18. Dynamic optical aberration correction with adaptive coded apertures techniques in conformal imaging

    Science.gov (United States)

    Li, Yan; Hu, Bin; Zhang, Pengbin; Zhang, Binglong

    2015-02-01

    Conformal imaging systems are confronted with dynamic aberration in optical design processing. In classical optical designs, for combination high requirements of field of view, optical speed, environmental adaption and imaging quality, further enhancements can be achieved only by the introduction of increased complexity of aberration corrector. In recent years of computational imaging, the adaptive coded apertures techniques which has several potential advantages over more traditional optical systems is particularly suitable for military infrared imaging systems. The merits of this new concept include low mass, volume and moments of inertia, potentially lower costs, graceful failure modes, steerable fields of regard with no macroscopic moving parts. Example application for conformal imaging system design where the elements of a set of binary coded aperture masks are applied are optimization designed is presented in this paper, simulation results show that the optical performance is closely related to the mask design and the reconstruction algorithm optimization. As a dynamic aberration corrector, a binary-amplitude mask located at the aperture stop is optimized to mitigate dynamic optical aberrations when the field of regard changes and allow sufficient information to be recorded by the detector for the recovery of a sharp image using digital image restoration in conformal optical system.

  19. Adaptive dynamics of competition for nutritionally complementary resources: character convergence, displacement, and parallelism.

    Science.gov (United States)

    Vasseur, David A; Fox, Jeremy W

    2011-10-01

    Consumers acquire essential nutrients by ingesting the tissues of resource species. When these tissues contain essential nutrients in a suboptimal ratio, consumers may benefit from ingesting a mixture of nutritionally complementary resource species. We investigate the joint ecological and evolutionary consequences of competition for complementary resources, using an adaptive dynamics model of two consumers and two resources that differ in their relative content of two essential nutrients. In the absence of competition, a nutritionally balanced diet rarely maximizes fitness because of the dynamic feedbacks between uptake rate and resource density, whereas in sympatry, nutritionally balanced diets maximize fitness because competing consumers with different nutritional requirements tend to equalize the relative abundances of the two resources. Adaptation from allopatric to sympatric fitness optima can generate character convergence, divergence, and parallel shifts, depending not on the degree of diet overlap but on the match between resource nutrient content and consumer nutrient requirements. Contrary to previous verbal arguments that suggest that character convergence leads to neutral stability, coadaptation of competing consumers always leads to stable coexistence. Furthermore, we show that incorporating costs of consuming or excreting excess nonlimiting nutrients selects for nutritionally balanced diets and so promotes character convergence. This article demonstrates that resource-use overlap has little bearing on coexistence when resources are nutritionally complementary, and it highlights the importance of using mathematical models to infer the stability of ecoevolutionary dynamics.

  20. An Adaptive Channel Access Method for Dynamic Super Dense Wireless Sensor Networks.

    Science.gov (United States)

    Lei, Chunyang; Bie, Hongxia; Fang, Gengfa; Zhang, Xuekun

    2015-12-03

    Super dense and distributed wireless sensor networks have become very popular with the development of small cell technology, Internet of Things (IoT), Machine-to-Machine (M2M) communications, Vehicular-to-Vehicular (V2V) communications and public safety networks. While densely deployed wireless networks provide one of the most important and sustainable solutions to improve the accuracy of sensing and spectral efficiency, a new channel access scheme needs to be designed to solve the channel congestion problem introduced by the high dynamics of competing nodes accessing the channel simultaneously. In this paper, we firstly analyzed the channel contention problem using a novel normalized channel contention analysis model which provides information on how to tune the contention window according to the state of channel contention. We then proposed an adaptive channel contention window tuning algorithm in which the contention window tuning rate is set dynamically based on the estimated channel contention level. Simulation results show that our proposed adaptive channel access algorithm based on fast contention window tuning can achieve more than 95 % of the theoretical optimal throughput and 0 . 97 of fairness index especially in dynamic and dense networks.

  1. Evolution in functional complexity of heart rate dynamics: a measure of cardiac allograft adaptability.

    Science.gov (United States)

    Kresh, J Y; Izrailtyan, I

    1998-09-01

    The capacity of self-organized systems to adapt is embodied in the functional organization of intrinsic control mechanisms. Evolution in functional complexity of heart rate variability (HRV) was used as measure of the capacity of the transplanted heart to express newly emergent regulatory order. In a cross-sectional study of 100 patients after (0-10 yr) heart transplantation (HTX), heart rate dynamics were assessed using pointwise correlation dimension (PD2) analysis. A new observation is that, commencing with the acute event of allograft transplantation, the dynamics of rhythm formation proceed through complex phase transitions. At implantation, the donor heart manifested metronome-like chronotropic behavior (PD2 approximately 1.0). At 11-100 days, dimensional complexity of HRV reached a peak (PD2 approximately 2.0) associated with resurgence in the high-frequency component (0.15-0.5 Hz) of the power spectral density. Subsequent dimensional loss to PD2 approximately 1.0 at 20-30 mo after HTX was followed by a progressive near-linear gain in system complexity, reaching PD2 approximately 3.0 7-10 yr after HTX. The "dynamic reorganization" in the allograft rhythm-generating system, seen in the first 100 days, is a manifestation of the adaptive capacity of intrinsic control mechanisms. The loss of HRV 2 yr after HTX implies a withdrawal of intrinsic autonomic control and/or development of an entrained dynamic pattern characteristic of extrinsic sympathetic input. The subsequent long-term progressive rise in dimensional complexity of HRV can be attributed to the restoration of a functional order patterning parasympathetic control. The recognition that the decentralized heart can restitute the multidimensional state space of HR generator dynamics independent of external autonomic signaling may provide a new perspective on principles that constitute homeodynamic regulation.

  2. Aircraft-on-ground path following control by dynamical adaptive backstepping

    Institute of Scientific and Technical Information of China (English)

    Chen Bihua; Jiao Zongxia; Shuzhi Sam Ge

    2013-01-01

    The necessity of improving the air traffic and reducing the aviation emissions drives to investigate automatic steering for aircraft to effectively roll on the ground.This paper addresses the path following control problem of aircraft-on-ground and focuses on the task that the aircraft is required to follow the desired path on the runway by nose wheel automatic steering.The proposed approach is based on dynamical adaptive backstepping so that the system model does not have to be transformed into a canonical triangular form which is necessary in conventional backstepping design.This adaptive controller performs well despite the lack of information on the aerodynamic load and the tire cornering stiffness parameters.Simulation results clearly demonstrate the advantages and effectiveness of the proposed approach.

  3. Adaptive iteration method for star centroid extraction under highly dynamic conditions

    Science.gov (United States)

    Gao, Yushan; Qin, Shiqiao; Wang, Xingshu

    2016-10-01

    Star centroiding accuracy decreases significantly when star sensor works under highly dynamic conditions or star images are corrupted by severe noise, reducing the output attitude precision. Herein, an adaptive iteration method is proposed to solve this problem. Firstly, initial star centroids are predicted by traditional method, and then based on initial reported star centroids and angular velocities of the star sensor, adaptive centroiding windows are generated to cover the star area and then an iterative method optimizing the location of centroiding window is used to obtain the final star spot extraction results. Simulation results shows that, compared with traditional star image restoration method and Iteratively Weighted Center of Gravity method, AWI algorithm maintains higher extraction accuracy when rotation velocities or noise level increases.

  4. Dynamic optimization of the complex adaptive controlling by the structure of enterprise’s product range

    Directory of Open Access Journals (Sweden)

    Andrey Fyodorovich Shorikov

    2013-06-01

    Full Text Available This paper reviews a methodical approach to solve multi-step dynamic problem of optimal integrated adaptive management of a product portfolio structure of the enterprise. For the organization of optimal adaptive terminal control of the system the recurrent algorithm, which reduces an initial multistage problem to the realization of the final sequence of problems of optimal program terminal control is offered. In turn, the decision of each problem of optimal program terminal control is reduced to the realization of the final sequence only single-step operations in the form of the problems solving of linear and convex mathematical programming. Thus, the offered approach allows to develop management solutions at current information support, which consider feedback, and which create the optimal structure of an enterprise’s product lines, contributing to optimising of profits, as well as maintenance of the desired level of profit for a long period of time

  5. Turing pattern dynamics and adaptive discretization for a super-diffusive Lotka-Volterra model.

    Science.gov (United States)

    Bendahmane, Mostafa; Ruiz-Baier, Ricardo; Tian, Canrong

    2016-05-01

    In this paper we analyze the effects of introducing the fractional-in-space operator into a Lotka-Volterra competitive model describing population super-diffusion. First, we study how cross super-diffusion influences the formation of spatial patterns: a linear stability analysis is carried out, showing that cross super-diffusion triggers Turing instabilities, whereas classical (self) super-diffusion does not. In addition we perform a weakly nonlinear analysis yielding a system of amplitude equations, whose study shows the stability of Turing steady states. A second goal of this contribution is to propose a fully adaptive multiresolution finite volume method that employs shifted Grünwald gradient approximations, and which is tailored for a larger class of systems involving fractional diffusion operators. The scheme is aimed at efficient dynamic mesh adaptation and substantial savings in computational burden. A numerical simulation of the model was performed near the instability boundaries, confirming the behavior predicted by our analysis.

  6. Adaptive free energy sampling in multidimensional collective variable space using boxed molecular dynamics.

    Science.gov (United States)

    O'Connor, Mike; Paci, Emanuele; McIntosh-Smith, Simon; Glowacki, David R

    2016-12-22

    The past decade has seen the development of a new class of rare event methods in which molecular configuration space is divided into a set of boundaries/interfaces, and then short trajectories are run between boundaries. For all these methods, an important concern is how to generate boundaries. In this paper, we outline an algorithm for adaptively generating boundaries along a free energy surface in multi-dimensional collective variable (CV) space, building on the boxed molecular dynamics (BXD) rare event algorithm. BXD is a simple technique for accelerating the simulation of rare events and free energy sampling which has proven useful for calculating kinetics and free energy profiles in reactive and non-reactive molecular dynamics (MD) simulations across a range of systems, in both NVT and NVE ensembles. Two key developments outlined in this paper make it possible to automate BXD, and to adaptively map free energy and kinetics in complex systems. First, we have generalized BXD to multidimensional CV space. Using strategies from rigid-body dynamics, we have derived a simple and general velocity-reflection procedure that conserves energy for arbitrary collective variable definitions in multiple dimensions, and show that it is straightforward to apply BXD to sampling in multidimensional CV space so long as the Cartesian gradients ∇CV are available. Second, we have modified BXD to undertake on-the-fly statistical analysis during a trajectory, harnessing the information content latent in the dynamics to automatically determine boundary locations. Such automation not only makes BXD considerably easier to use; it also guarantees optimal boundaries, speeding up convergence. We have tested the multidimensional adaptive BXD procedure by calculating the potential of mean force for a chemical reaction recently investigated using both experimental and computational approaches - i.e., F + CD3CN → DF + D2CN in both the gas phase and a strongly coupled explicit CD3CN solvent

  7. Evaluation of adaptive dynamic range optimization in adverse listening conditions for cochlear implants

    Science.gov (United States)

    Ali, Hussnain; Hazrati, Oldooz; Tobey, Emily A.; Hansen, John H. L

    2014-01-01

    The aim of this study is to investigate the effect of Adaptive Dynamic Range Optimization (ADRO) on speech identification for cochlear implant (CI) users in adverse listening conditions. In this study, anechoic quiet, noisy, reverberant, noisy reverberant, and reverberant noisy conditions are evaluated. Two scenarios are considered when modeling the combined effects of reverberation and noise: (a) noise is added to the reverberant speech, and (b) noisy speech is reverberated. CI users were tested in different listening environments using IEEE sentences presented at 65 dB sound pressure level. No significant effect of ADRO processing on speech intelligibility was observed. PMID:25190428

  8. The tele-connections of long duration floods and their implications for dynamically updating the Flood Control Pool

    Science.gov (United States)

    Devineni, Naresh; Najibi, Nasser; Lall, Upmanu

    2016-04-01

    Traditional approaches to flood risk assessment are typically indexed to an instantaneous peak flow event at a specific recording gage on a river, and then extrapolated through hydraulic modeling of that peak flow to the potential area that is likely to be inundated. However, property losses tend to be determined as much by the duration and volume of flooding as by the depth and velocity of inundation. We argue that the existing notion of a flood risk assessment and consequent reservoir flood control operations needs to be revisited, especially for floods due to persistent rainfall (>30 day duration). Our interest lies in explicitly understanding the dependence of the likelihood or frequency and intensity of extreme regional floods on a causal chain of ocean-atmosphere processes whose slow variation and regime-like changes translate into significant and persistent changes in the probability of major floods in the large river basins. An understanding and mapping of these factors into a dynamic risk framework is important for establishing a process by which flood risk for large basins could be systematically updated reflecting changing climate conditions, whether due to human influence, or as part of the natural cycles of climate variation. In this study, we developed an inference system for climate informed flood risk assessment using an integrated statistical modeling approach. We first develop multivariate flood attributes and classify their characteristic spatial variability using the hierarchical clustering approach. Depending on the flood event type, different rainfall inducing mechanisms (e.g. tropical storm, local convection, frontal system, recurrent tropical waves) may be involved with characteristic spatial scales and statistical properties. Hence, we identify the antecedent rainfall conditions for the flood types and map their corresponding specific atmospheric circulation patterns using compositing of the NCEP/NCAR reanalysis data and the storm tracks

  9. Adaptive Pulsed Laser Line Extraction for Terrain Reconstruction using a Dynamic Vision Sensor

    Directory of Open Access Journals (Sweden)

    Christian eBrandli

    2014-01-01

    Full Text Available Mobile robots need to know the terrain in which they are moving for path planning and obstacle avoidance. This paper proposes the combination of a bio-inspired, redundancy-suppressing dynamic vision sensor with a pulsed line laser to allow fast terrain reconstruction. A stable laser stripe extraction is achieved by exploiting the sensor’s ability to capture the temporal dynamics in a scene. An adaptive temporal filter for the sensor output allows a reliable reconstruction of 3D terrain surfaces. Laser stripe extractions up to pulsing frequencies of 500Hz were achieved using a line laser of 3mW at a distance of 45cm using an event-based algorithm that exploits the sparseness of the sensor output. As a proof of concept, unstructured rapid prototype terrain samples have been successfully reconstructed with an accuracy of 2mm.

  10. MECHANICAL DYNAMICS ANALYSIS OF PM GENERATOR USING H-ADAPTIVE REFINEMENT

    Directory of Open Access Journals (Sweden)

    AJAY KUMAR

    2010-03-01

    Full Text Available This paper describes the dynamic analysis of permanent magnet (PM rotor generator using COMSOL Multiphysics, a Finite Element Analysis (FEA based package and Simulink, a system simulation program. Model of PM rotor generator is developed for its mechanical dynamics and computational of torque resulting from magnetic force. For the model the mesh is constructed using first order Lagrange quadratic elements and h-adaptive refinement technique based upon bank bisection is used for improving accuracy of the model. Effect of rotor moment of inertia (MI on the winding resistance and winding inductance has been studied by using Simulink. It is shown that the system MI has a significant effect on optimal winding resistance and inductance to achieve steady state operation in shortest period of time.

  11. Optimal control for unknown discrete-time nonlinear Markov jump systems using adaptive dynamic programming.

    Science.gov (United States)

    Zhong, Xiangnan; He, Haibo; Zhang, Huaguang; Wang, Zhanshan

    2014-12-01

    In this paper, we develop and analyze an optimal control method for a class of discrete-time nonlinear Markov jump systems (MJSs) with unknown system dynamics. Specifically, an identifier is established for the unknown systems to approximate system states, and an optimal control approach for nonlinear MJSs is developed to solve the Hamilton-Jacobi-Bellman equation based on the adaptive dynamic programming technique. We also develop detailed stability analysis of the control approach, including the convergence of the performance index function for nonlinear MJSs and the existence of the corresponding admissible control. Neural network techniques are used to approximate the proposed performance index function and the control law. To demonstrate the effectiveness of our approach, three simulation studies, one linear case, one nonlinear case, and one single link robot arm case, are used to validate the performance of the proposed optimal control method.

  12. Adaptive lambda square dynamics simulation: an efficient conformational sampling method for biomolecules.

    Science.gov (United States)

    Ikebe, Jinzen; Sakuraba, Shun; Kono, Hidetoshi

    2014-01-05

    A novel, efficient sampling method for biomolecules is proposed. The partial multicanonical molecular dynamics (McMD) was recently developed as a method that improved generalized ensemble (GE) methods to focus sampling only on a part of a system (GEPS); however, it was not tested well. We found that partial McMD did not work well for polylysine decapeptide and gave significantly worse sampling efficiency than a conventional GE. Herein, we elucidate the fundamental reason for this and propose a novel GEPS, adaptive lambda square dynamics (ALSD), which can resolve the problem faced when using partial McMD. We demonstrate that ALSD greatly increases the sampling efficiency over a conventional GE. We believe that ALSD is an effective method and is applicable to the conformational sampling of larger and more complicated biomolecule systems. Copyright © 2013 Wiley Periodicals, Inc.

  13. Distributed neural network control for adaptive synchronization of uncertain dynamical multiagent systems.

    Science.gov (United States)

    Peng, Zhouhua; Wang, Dan; Zhang, Hongwei; Sun, Gang

    2014-08-01

    This paper addresses the leader-follower synchronization problem of uncertain dynamical multiagent systems with nonlinear dynamics. Distributed adaptive synchronization controllers are proposed based on the state information of neighboring agents. The control design is developed for both undirected and directed communication topologies without requiring the accurate model of each agent. This result is further extended to the output feedback case where a neighborhood observer is proposed based on relative output information of neighboring agents. Then, distributed observer-based synchronization controllers are derived and a parameter-dependent Riccati inequality is employed to prove the stability. This design has a favorable decouple property between the observer and the controller designs for nonlinear multiagent systems. For both cases, the developed controllers guarantee that the state of each agent synchronizes to that of the leader with bounded residual errors. Two illustrative examples validate the efficacy of the proposed methods.

  14. Robust adaptive control of spacecraft proximity maneuvers under dynamic coupling and uncertainty

    Science.gov (United States)

    Sun, Liang; Huo, Wei

    2015-11-01

    This paper provides a solution for the position tracking and attitude synchronization problem of the close proximity phase in spacecraft rendezvous and docking. The chaser spacecraft must be driven to a certain fixed position along the docking port direction of the target spacecraft, while the attitude of the two spacecraft must be synchronized for subsequent docking operations. The kinematics and dynamics for relative position and relative attitude are modeled considering dynamic coupling, parametric uncertainties and external disturbances. The relative motion model has a new form with a novel definition of the unknown parameters. An original robust adaptive control method is developed for the concerned problem, and a proof of the asymptotic stability is given for the six degrees of freedom closed-loop system. A numerical example is displayed in simulation to verify the theoretical results.

  15. Characterising Steady-State Topologies of SIS Dynamics on Adaptive Networks

    CERN Document Server

    Wieland, Stefan; Parisi, Andrea; Nunes, Ana

    2012-01-01

    Disease awareness in epidemiology can be modelled with adaptive contact networks, where the interplay of disease dynamics and network alteration often adds new phases to the standard models (Gross et al. 2006, Shaw et al. 2008) and, in stochastic simulations, lets network topology settle down to a steady state that can be static (in the frozen phase) or dynamic (in the endemic phase). We show for the SIS model that, in the endemic phase, this steady state does not depend on the initial network topology, only on the disease and rewiring parameters and on the link density of the network, which is conserved. We give an analytic description of the structure of this co-evolving network of infection through its steady-state degree distribution.

  16. Adaptive Stabilization for Uncertain Nonholonomic Dynamic Mobile Robots Based on Visual Servoing Feedback

    Institute of Scientific and Technical Information of China (English)

    YANG Fang; WANG Chao-Li

    2011-01-01

    The stabilization problem of nonholonomic dynamic mobile robots with a fixed (ceiling-mounted) camera is addressed in this paper.First,a camera-object visual servding kinematic model is introduced by utilizing the pin-hole camera model and a kinematic stabilizing controller is given for the kinematic model.Then,an adaptive sliding mode controller is designed to stabilize uncertain dynamic mobile robot in the presence of parametric uncertainties associated with the camera system.The proposed controller is robust not only to structured uncertainty such as mass variation but also to unstructured one such as disturbances.The stability of the proposed control system and the boundedness of estimated parameters are rigorously proved by Lyapunov method.Simulation results are presented to illustrate the performance of the control law.

  17. Adaptive coded spreading OFDM signal for dynamic-λ optical access network

    Science.gov (United States)

    Liu, Bo; Zhang, Lijia; Xin, Xiangjun

    2015-12-01

    This paper proposes and experimentally demonstrates a novel adaptive coded spreading (ACS) orthogonal frequency division multiplexing (OFDM) signal for dynamic distributed optical ring-based access network. The wavelength can be assigned to different remote nodes (RNs) according to the traffic demand of optical network unit (ONU). The ACS can provide dynamic spreading gain to different signals according to the split ratio or transmission length, which offers flexible power budget for the network. A 10×13.12 Gb/s OFDM access with ACS is successfully demonstrated over two RNs and 120 km transmission in the experiment. The demonstrated method may be viewed as one promising for future optical metro access network.

  18. Receiver-channel based adaptive blind equalization approach for GPS dynamic multipath mitigation

    Institute of Scientific and Technical Information of China (English)

    Zhao Yun; Xue Xiaonan; Zhang Tingfei

    2013-01-01

    Aiming at mitigating multipath effect in dynamic global positioning system (GPS) satellite navigation applications,an approach based on channel blind equalization and real-time recursive least square (RLS) algorithm is proposed,which is an application of the wireless communication channel equalization theory to GPS receiver tracking loops.The blind equalization mechanism builds upon the detection of the correlation distortion due to multipath channels; there-fore an increase in the number of correlator channels is required compared with conventional GPS receivers.An adaptive estimator based on the real-time RLS algorithm is designed for dynamic estimation of multipath channel response.Then,the code and carrier phase receiver tracking errors are compensated by removing the estimated multipath components from the correlators' outputs.To demonstrate the capabilities of the proposed approach,this technique is integrated into a GPS software receiver connected to a navigation satellite signal simulator,thus simulations under controlled dynamic multipath scenarios can be carried out.Simulation results show that in a dynamic and fairly severe multipath environment,the proposed approach achieves simultaneously instantaneous accurate multipath channel estimation and significant multipath tracking errors reduction in both code delay and carrier phase.

  19. Mutational effects and population dynamics during viral adaptation challenge current models.

    Science.gov (United States)

    Miller, Craig R; Joyce, Paul; Wichman, Holly A

    2011-01-01

    Adaptation in haploid organisms has been extensively modeled but little tested. Using a microvirid bacteriophage (ID11), we conducted serial passage adaptations at two bottleneck sizes (10(4) and 10(6)), followed by fitness assays and whole-genome sequencing of 631 individual isolates. Extensive genetic variation was observed including 22 beneficial, several nearly neutral, and several deleterious mutations. In the three large bottleneck lines, up to eight different haplotypes were observed in samples of 23 genomes from the final time point. The small bottleneck lines were less diverse. The small bottleneck lines appeared to operate near the transition between isolated selective sweeps and conditions of complex dynamics (e.g., clonal interference). The large bottleneck lines exhibited extensive interference and less stochasticity, with multiple beneficial mutations establishing on a variety of backgrounds. Several leapfrog events occurred. The distribution of first-step adaptive mutations differed significantly from the distribution of second-steps, and a surprisingly large number of second-step beneficial mutations were observed on a highly fit first-step background. Furthermore, few first-step mutations appeared as second-steps and second-steps had substantially smaller selection coefficients. Collectively, the results indicate that the fitness landscape falls between the extremes of smooth and fully uncorrelated, violating the assumptions of many current mutational landscape models.

  20. Nonlinear Adaptive Dynamic Output-Feedback Power-Level Control of Nuclear Heating Reactors

    Directory of Open Access Journals (Sweden)

    Zhe Dong

    2013-01-01

    Full Text Available Due to the high safety performance of small nuclear reactors, there is a promising future for small reactors. Nuclear heating reactor (NHR is a small reactor that has many advanced safety features such as the integrated arrangement, natural circulation at any power levels, self-pressurization, hydraulic control rod driving, and passive residual heating removing and can be applied to the fields of district heating, seawater desalination, and electricity production. Since the NHR dynamics has strong nonlinearity and uncertainty, it is meaningful to develop the nonlinear adaptive power-level control technique. From the idea of physically based control design method, a novel nonlinear adaptive power-level control is given for the NHR in this paper. It is theoretically proved that this newly built controller does not only provide globally asymptotic closed-loop stability but is also adaptive to the system uncertainty. Numerical simulation results show the feasibility of this controller and the relationship between the performance and controller parameters.

  1. Adaptive Control for Linear Uncertain Systems with Unmodeled Dynamics Revisited via Optimal Control Modification

    Science.gov (United States)

    Nguyen, Nhan

    2013-01-01

    This paper presents the optimal control modification for linear uncertain plants. The Lyapunov analysis shows that the modification parameter has a limiting value depending on the nature of the uncertainty. The optimal control modification exhibits a linear asymptotic property that enables it to be analyzed in a linear time invariant framework for linear uncertain plants. The linear asymptotic property shows that the closed-loop plants in the limit possess a scaled input-output mapping. Using this property, we can derive an analytical closed-loop transfer function in the limit as the adaptive gain tends to infinity. The paper revisits the Rohrs counterexample problem that illustrates the nature of non-robustness of model-reference adaptive control in the presence of unmodeled dynamics. An analytical approach is developed to compute exactly the modification parameter for the optimal control modification that stabilizes the plant in the Rohrs counterexample. The linear asymptotic property is also used to address output feedback adaptive control for non-minimum phase plants with a relative degree 1.

  2. Color correction for high dynamic range images using a chromatic adaptation method

    Science.gov (United States)

    Yun, Byoung-Ju; Park, Jinhyung; Kim, Seunghae; Kim, Hyun-Deok; Choi, Ho-Hyoung

    2013-01-01

    In the image capturing process using a camera, poor illumination has an influence on the image quality, especially in regards to the contrast and details in the dark regions. Generally, high dynamic range (HDR) imaging techniques are used to match the quality between the real scene and the displayed image. However, in images using the multi-exposure technique or regular photography, the images are limited by the veiling glare, which is scene-, exposure-, lens-, aperture-, and camera-dependent. This study mainly addressed images using the multi-exposure technique and developed a color correction scheme that uses a chromatic adaptation method. In the tone mapping using a Gaussian pyramid, the adaptation level is obtained based on a linear Gaussian filter. The resulting image is then processed through the developed tone-mapping function. This allows the chromatic adaptation method to address the mismatches between the real world and the displayed image. The experiment results show that the proposed method yields a better color correction performance compared to conventional methods.

  3. Dynamic formant extraction of wa language based on adaptive variational mode decomposition

    Science.gov (United States)

    Fu, Meijun; Dong, Huazhen; Pan, Wenlin

    2017-08-01

    Wa language is one of Chinese minority languages spoken by the Wa nationality who lives in Yunnan Province, China. Until now, it has not been studied from the perspective of Engineering Phonetics. In this paper, for the above reason, by the adaptive variational mode decomposition (AVMD) we have investigated the dynamic formant characteristics of Wa language. Firstly, more precisely, use the synthetic dimension to split Wa language isolated words into voiceless and voiced segment, initials and finals. Secondly, use Linear Prediction Coding to estimate the first three formant frequencies and their bandwidths roughly. Thirdly, select the appropriate equilibrium constraint parameter and the number of decomposed layers so that Adaptive Variational Mode Decomposition (AVMD) can decompose the signal into some intrinsic mode functions (IMFs) without pattern aliasing. Fourthly, use the estimated formant frequencies and bandwidths to determine precisely the required IMFs. Fifthly, use the Hilbert transform to calculate the instantaneous frequency of the above determinate IMFs. Further, we implement the weight average operation on instantaneous frequencies to obtain the first three formant frequencies for each frame. Finally, comparing the first three formant frequencies obtained by the adaptive variance modal decomposition and by Praat software respectively, so we have drawn the conclusion that the relative correct rate of the former to the latter can reach 86% averagely in terms of the selected isolated words, which has shown that our method is effective on Wa language.

  4. High Dynamic Range adaptive ΔΣ-based Focal Plane Array architecture

    KAUST Repository

    Yao, Shun

    2012-10-16

    In this paper, an Adaptive Delta-Sigma based architecture for High Dynamic Range (HDR) Focal Plane Arrays is presented. The noise shaping effect of the Delta-Sigma modulation in the low end, and the distortion noise induced in the high end of Photo-diode current were analyzed in detail. The proposed architecture can extend the DR for about 20N log2 dB at the high end of Photo-diode current with an N bit Up-Down counter. At the low end, it can compensate for the larger readout noise by employing Extended Counting. The Adaptive Delta-Sigma architecture employing a 4-bit Up-Down counter achieved about 160dB in the DR, with a Peak SNR (PSNR) of 80dB at the high end. Compared to the other HDR architectures, the Adaptive Delta-Sigma based architecture provides the widest DR with the best SNR performance in the extended range.

  5. Adaptive digital fringe projection technique for high dynamic range three-dimensional shape measurement.

    Science.gov (United States)

    Lin, Hui; Gao, Jian; Mei, Qing; He, Yunbo; Liu, Junxiu; Wang, Xingjin

    2016-04-04

    It is a challenge for any optical method to measure objects with a large range of reflectivity variation across the surface. Image saturation results in incorrect intensities in captured fringe pattern images, leading to phase and measurement errors. This paper presents a new adaptive digital fringe projection technique which avoids image saturation and has a high signal to noise ratio (SNR) in the three-dimensional (3-D) shape measurement of objects that has a large range of reflectivity variation across the surface. Compared to previous high dynamic range 3-D scan methods using many exposures and fringe pattern projections, which consumes a lot of time, the proposed technique uses only two preliminary steps of fringe pattern projection and image capture to generate the adapted fringe patterns, by adaptively adjusting the pixel-wise intensity of the projected fringe patterns based on the saturated pixels in the captured images of the surface being measured. For the bright regions due to high surface reflectivity and high illumination by the ambient light and surfaces interreflections, the projected intensity is reduced just to be low enough to avoid image saturation. Simultaneously, the maximum intensity of 255 is used for those dark regions with low surface reflectivity to maintain high SNR. Our experiments demonstrate that the proposed technique can achieve higher 3-D measurement accuracy across a surface with a large range of reflectivity variation.

  6. An Adaptive Dynamic Surface Controller for Ultralow Altitude Airdrop Flight Path Angle with Actuator Input Nonlinearity

    Directory of Open Access Journals (Sweden)

    Mao-long Lv

    2016-01-01

    Full Text Available In the process of ultralow altitude airdrop, many factors such as actuator input dead-zone, backlash, uncertain external atmospheric disturbance, and model unknown nonlinearity affect the precision of trajectory tracking. In response, a robust adaptive neural network dynamic surface controller is developed. As a result, the aircraft longitudinal dynamics with actuator input nonlinearity is derived; the unknown nonlinear model functions are approximated by means of the RBF neural network. Also, an adaption strategy is used to achieve robustness against model uncertainties. Finally, it has been proved that all the signals in the closed-loop system are bounded and the tracking error converges to a small residual set asymptotically. Simulation results demonstrate the perfect tracking performance and strong robustness of the proposed method, which is not only applicable to the actuator with input dead-zone but also suitable for the backlash nonlinearity. At the same time, it can effectively overcome the effects of dead-zone and the atmospheric disturbance on the system and ensure the fast track of the desired flight path angle instruction, which overthrows the assumption that system functions must be known.

  7. Control of Quantum Fluid Dynamics and Adaptive Phase Compensation for Laser Propagation in Turbulence

    Science.gov (United States)

    Gustafsson, Jonathan; Sritharan, Sivaguru S.

    2015-11-01

    Equations of High Energy Laser propagation in a turbulent medium and the equations of quantum fluid dynamics are connected through a mathematical transformation. In this way the problem of adaptive phase compensation can be phrased as an initial velocity control problem for quantum fluid dynamics. The quantum hydrodynamics equation can be derived by applying the Madelung transformation to the time-dependent linear or nonlinear Schrödinger equation. The resulting equations are similar to incompressible Euler equations with an additional term denoted the quantum pressure term. The quantum hydrodynamics equation can thus be a good way to understand adaptive optics and laser propagation through the atmosphere. A Riemann solver within the Clawpack framework has been developed. An initial value optimization problem will be solved using adjoint methods. The initial phase can be controlled when the beam leaves the laser appartus. The control method can also be coupled to a Navier-Stokes solver in order to study thermal blooming where the laser heats the air and changes the index of refraction. The change in refractive index will in turn affect the propagation of the Laser beam. Using optimal control techniques, it is possible to adjust the beam in order to compensate for the heating.

  8. Adaptive Real-Time Estimation on Road Disturbances Properties Considering Load Variation via Vehicle Vertical Dynamics

    Directory of Open Access Journals (Sweden)

    Wuhui Yu

    2013-01-01

    Full Text Available Vehicle dynamics are directly dependent on tire-road contact forces and torques which are themselves dependent on the wheels’ load and tire-road friction characteristics. An acquisition of the road disturbance property is essential for the enhancement of vehicle suspension control systems. This paper focuses on designing an adaptive real-time road profile estimation observer considering load variation via vehicle vertical dynamics. Firstly, a road profile estimator based on a linear Kalman filter is proposed, which has great advantages on vehicle online control. Secondly, to minimize the estimation errors, an online identification system based on the Recursive Least-Squares Estimation is applied to estimate sprung mass, which is used to refresh the system matrix of the adaptive observer to improve the road estimation efficiency. Last, for mining road category from the estimated various road profile sequencse, a road categorizer considering road frequency and amplitude simultaneously is approached and its efficiency is validated via numerical simulations, in which the road condition is categorized into six special ranges, and this road detection strategy can provide the suspension control system with a better compromise for the vehicle ride comfort, handling, and safety performance.

  9. Hierarchical adaptive stereo matching algorithm for obstacle detection with dynamic programming

    Institute of Scientific and Technical Information of China (English)

    Ming BAI; Yan ZHUANG; Wei WANG

    2009-01-01

    An adaptive weighted stereo matching algorithm with multilevel and bidirectional dynamic programming based on ground control points(GCPs) is presented.To decrease time complexity without losing matching precision,using a multilevel search scheme,the coarse matching is processed in typical disparity space image,while the fine matching is processed in disparity-offset space image.In the upper level,GCPs are obtained by enhanced volumetric iterative algorithm enforcing the mutual constraint and the threshold constraint.Under the supervision of the highly reliable GCPs,bidirec-tional dynamic programming framework is employed to solve the inconsistency in the optimization path.In the lower level,to reduce running time,disparity-offset space is proposed to efficiently achieve the dense disparity image.In addition,an adaptive dual support-weight strategy is presented to aggregate matching cost,which considers photometric and geomet-ric information.Further,post-processing algorithm can ameliorate disparity results in areas with depth discontinuities and related by occlusions using dual threshold algorithm,where missing stereo information is substituted from surrounding re-gions.To demonstrate the effectiveness of the algorithm,we present the two groups of experimental results for four widely used standard stereo data sets,including discussion on performance and comparison with other methods,which show that the algorithm has not only a fast speed,but also significantly improves the efficiency of holistic optimization.

  10. Adaptive terminal sliding mode control for high-order nonlinear dynamic systems

    Institute of Scientific and Technical Information of China (English)

    庄开宇; 苏宏业; 张克勤; 褚健

    2003-01-01

    An adaptive terminal sliding mode control (SMC) technique is proposed to deal with the tracking problem for a class of high-order nonlinear dynamic systems. It is shown that a function augmented sliding hyperplane can be used to develop a new terminal sliding mode for high-order nonlinear systems. A terminal SMC controller based on Lyapunov theory is designed to force the state variables of the closed-loop system to reach and remain on the terminal sliding mode, so that the output tracking error then converges to zero in finite time which can be set arbitrarily. An adaptive mechanism is introduced to estimate the unknown parameters of the upper bounds of system uncertainties. The estimates are then used as controller parameters so that the effects of uncertain dynamics can be eliminated. It is also shown that the stability of the closed-loop system can be guaranteed with the proposed control strategy. The simulation of a numerical example is provided to show the effectiveness of the new method.

  11. Adaptive Interval Configuration to Enhance Dynamic Approach for Mining Association Rules

    Institute of Scientific and Technical Information of China (English)

    1999-01-01

    Most proposed algorithms for mining association rules follow the conventional le vel-wise approach. The dynamic candidate generation idea introduced in the dyna mic itemset counting (DIC) a lgorithm broke away from the level-wise limitation which could find the large i t emsets using fewer passes over the database than level-wise algorithms. However , the dynamic approach is very sensitive to the data distribution of the database and it requires a proper interval size. In this paper an optimization technique named adaptive interval configuration (AIC) has been developed to enhance the d y namic approach. The AIC optimization has the following two functions. The first is that a homogeneous distribution of large itemsets over intervals can be achie ved so that less unnecessary candidates could be generated and less database sca nning passes are guaranteed. The second is that the near optimal interval size c ould be determined adaptively to produce the best response time. We also develop ed a candidate pruning technique named virtual partition pruning to reduce the s ize-2 candidate set and incorporated it into the AIC optimization. Based on the optimization technique, we proposed the efficient AIC algorithm for mining asso c iation rules. The algorithms of AIC, DIC and the classic Apriori were implemente d on a Sun Ultra Enterprise 4000 for performance comparison. The results show th at the AIC performed much better than both DIC and Apriori, and showed a strong robustness.

  12. Organizational dynamics in adaptive distributed search processes:effects on performance and the role of complexity #

    Institute of Scientific and Technical Information of China (English)

    Friederike WALL

    2016-01-01

    In this paper, the effects of altering the organizational setting of distributed adaptive search processes in the course of search are investigated. We put particular emphasis on the complexity of interactions between partial search problems assigned to search agents. Employing an agent-based simulation based on the framework of NK landscapes we analyze different temporal change modes of the organizational set-up. The organizational properties under change include, for example, the coordination mechanisms among search agents. Results suggest that inducing organizational dynamics has the potential to increase the effectiveness of distributed adaptive search processes with respect to various performance measures like the fi nal performance achieved at the end of the search, the chance to fi nd the optimal solution of the search problem, or the average performance per period achieved during the search process. However, results also indicate that the mode of temporal change in conjunction with the complexity of the search problem considerably affects the order of magnitude of these benefi cial effects. In particular, results suggest that organizational dynamics induces a shift towards more exploration, i.e., discovery of new areas in the fi tness landscape, and less exploitation, i.e., stepwise improvement.

  13. Stochastic Optimal Regulation of Nonlinear Networked Control Systems by Using Event-Driven Adaptive Dynamic Programming.

    Science.gov (United States)

    Sahoo, Avimanyu; Jagannathan, Sarangapani

    2017-02-01

    In this paper, an event-driven stochastic adaptive dynamic programming (ADP)-based technique is introduced for nonlinear systems with a communication network within its feedback loop. A near optimal control policy is designed using an actor-critic framework and ADP with event sampled state vector. First, the system dynamics are approximated by using a novel neural network (NN) identifier with event sampled state vector. The optimal control policy is generated via an actor NN by using the NN identifier and value function approximated by a critic NN through ADP. The stochastic NN identifier, actor, and critic NN weights are tuned at the event sampled instants leading to aperiodic weight tuning laws. Above all, an adaptive event sampling condition based on estimated NN weights is designed by using the Lyapunov technique to ensure ultimate boundedness of all the closed-loop signals along with the approximation accuracy. The net result is event-driven stochastic ADP technique that can significantly reduce the computation and network transmissions. Finally, the analytical design is substantiated with simulation results.

  14. A Self-adaptive Dynamic Evaluation Model for Diabetes Mellitus, Based on Evolutionary Strategies

    Directory of Open Access Journals (Sweden)

    An-Jiang Lu

    2016-03-01

    Full Text Available In order to evaluate diabetes mellitus objectively and accurately, this paper builds a self-adaptive dynamic evaluation model for diabetes mellitus, based on evolutionary strategies. First of all, on the basis of a formalized description of the evolutionary process of diabetes syndromes, using a state transition function, it judges whether a disease is evolutionary, through an excitation parameter. It then, provides evidence for the rebuilding of the evaluation index system. After that, by abstracting and rebuilding the composition of evaluation indexes, it makes use of a heuristic algorithm to determine the composition of the evolved evaluation index set of diabetes mellitus, It then, calculates the weight of each index in the evolved evaluation index set of diabetes mellitus by building a dependency matrix and realizes the self-adaptive dynamic evaluation of diabetes mellitus under an evolutionary environment. Using this evaluation model, it is possible to, quantify all kinds of diagnoses and treatment experiences of diabetes and finally to adopt ideal diagnoses and treatment measures for different patients with diabetics.

  15. Measuring dynamics of household vulnerability in selected coastal megacities to inform transformative adaptation

    Science.gov (United States)

    Birkmann, J.; Solecki, W. D.

    2016-12-01

    Understanding conditions and dynamics of household vulnerability and risk is key for building community resilience. Two different methodological approaches of vulnerability, risk and resilience assessment for selected global megacities are presented to address this research issue. First, an indicator-based approach was executed to compare susceptibility, coping and adaptive capacities for Lagos, Kolkata, Lagos, London, New York, and Tokyo on a neighborhood by neighborhood scale. Second, a household survey that has been conducted in Kolkata, Lagos, and New York to explore specific features of susceptibility, risk management capacities and transformations within at risk neighborhoods. The results of both methods underscore the dynamics of vulnerability. Lessons learned for disaster risk management and urban planning are derived, particularly in terms of defining priorities for a more inclusive and resilient urban development, and transformative adaptation. The findings also provide opportunity to critically review the potential outcomes of the New Urban Agenda (outcome of UN-Habitat III). The research has been undertaken within a larger international research team in the Belmont funded project Transformation of Urban Coasts.

  16. ALEGRA -- A massively parallel h-adaptive code for solid dynamics

    Energy Technology Data Exchange (ETDEWEB)

    Summers, R.M.; Wong, M.K.; Boucheron, E.A.; Weatherby, J.R. [Sandia National Labs., Albuquerque, NM (United States)

    1997-12-31

    ALEGRA is a multi-material, arbitrary-Lagrangian-Eulerian (ALE) code for solid dynamics designed to run on massively parallel (MP) computers. It combines the features of modern Eulerian shock codes, such as CTH, with modern Lagrangian structural analysis codes using an unstructured grid. ALEGRA is being developed for use on the teraflop supercomputers to conduct advanced three-dimensional (3D) simulations of shock phenomena important to a variety of systems. ALEGRA was designed with the Single Program Multiple Data (SPMD) paradigm, in which the mesh is decomposed into sub-meshes so that each processor gets a single sub-mesh with approximately the same number of elements. Using this approach the authors have been able to produce a single code that can scale from one processor to thousands of processors. A current major effort is to develop efficient, high precision simulation capabilities for ALEGRA, without the computational cost of using a global highly resolved mesh, through flexible, robust h-adaptivity of finite elements. H-adaptivity is the dynamic refinement of the mesh by subdividing elements, thus changing the characteristic element size and reducing numerical error. The authors are working on several major technical challenges that must be met to make effective use of HAMMER on MP computers.

  17. Learning from adaptive neural dynamic surface control of strict-feedback systems.

    Science.gov (United States)

    Wang, Min; Wang, Cong

    2015-06-01

    Learning plays an essential role in autonomous control systems. However, how to achieve learning in the nonstationary environment for nonlinear systems is a challenging problem. In this paper, we present learning method for a class of n th-order strict-feedback systems by adaptive dynamic surface control (DSC) technology, which achieves the human-like ability of learning by doing and doing with learned knowledge. To achieve the learning, this paper first proposes stable adaptive DSC with auxiliary first-order filters, which ensures the boundedness of all the signals in the closed-loop system and the convergence of tracking errors in a finite time. With the help of DSC, the derivative of the filter output variable is used as the neural network (NN) input instead of traditional intermediate variables. As a result, the proposed adaptive DSC method reduces greatly the dimension of NN inputs, especially for high-order systems. After the stable DSC design, we decompose the stable closed-loop system into a series of linear time-varying perturbed subsystems. Using a recursive design, the recurrent property of NN input variables is easily verified since the complexity is overcome using DSC. Subsequently, the partial persistent excitation condition of the radial basis function NN is satisfied. By combining a state transformation, accurate approximations of the closed-loop system dynamics are recursively achieved in a local region along recurrent orbits. Then, the learning control method using the learned knowledge is proposed to achieve the closed-loop stability and the improved control performance. Simulation studies are performed to demonstrate the proposed scheme can not only reuse the learned knowledge to achieve the better control performance with the faster tracking convergence rate and the smaller tracking error but also greatly alleviate the computational burden because of reducing the number and complexity of NN input variables.

  18. Flexible and adaptive water systems operations through more informed and dynamic decisions

    Science.gov (United States)

    Castelletti, A.; Giuliani, M.

    2016-12-01

    Timely adapting the operations of water systems to be resilient against rapid changes in both hydroclimatic and socioeconomic forcing is generally recommended as a part of planning and managing water resources under uncertain futures. A great opportunity to make the operations more flexible and adaptive is offered by the unprecedented amount of information that is becoming available to water system operators, providing a wide range of data at increasingly higher temporal and spatial resolution. Yet, many water systems are still operated using very simple information systems, typically based on basic statistical analysis and the operator's experience. In this work, we discuss the potential offered by incorporating improved information to enhance water systems operation and increase their ability of adapting to different external conditions and resolving potential conflicts across sectors. In particular, we focus on the use of different variables associated to different dynamics of the system (slow and fast) diversely impacting the operating objectives on the short-, medium- and long-term. The multi-purpose operations of the Hoa Binh reservoir in the Red River Basin (Vietnam) is used to demonstrate our approach. Numerical results show that our procedure is able to automatically select the most valuable information for improving the Hoa Binh operations and mitigating the conflict between short-term objectives, i.e. hydropower production and flood control. Moreover, we also successfully identify low-frequency climate information associated to El-Nino Southern Oscillation for improving the performance in terms of long-term objectives, i.e. water supply. Finally, we assess the value of better informing operational decisions for adapting the system operations to changing conditions by considering different climate change projections.

  19. Adaptive fingerprint image enhancement with emphasis on preprocessing of data.

    Science.gov (United States)

    Bartůnek, Josef Ström; Nilsson, Mikael; Sällberg, Benny; Claesson, Ingvar

    2013-02-01

    This article proposes several improvements to an adaptive fingerprint enhancement method that is based on contextual filtering. The term adaptive implies that parameters of the method are automatically adjusted based on the input fingerprint image. Five processing blocks comprise the adaptive fingerprint enhancement method, where four of these blocks are updated in our proposed system. Hence, the proposed overall system is novel. The four updated processing blocks are: 1) preprocessing; 2) global analysis; 3) local analysis; and 4) matched filtering. In the preprocessing and local analysis blocks, a nonlinear dynamic range adjustment method is used. In the global analysis and matched filtering blocks, different forms of order statistical filters are applied. These processing blocks yield an improved and new adaptive fingerprint image processing method. The performance of the updated processing blocks is presented in the evaluation part of this paper. The algorithm is evaluated toward the NIST developed NBIS software for fingerprint recognition on FVC databases.

  20. Fast adaptive OFDM-PON over single fiber loopback transmission using dynamic rate adaptation-based algorithm for channel performance improvement

    Science.gov (United States)

    Kartiwa, Iwa; Jung, Sang-Min; Hong, Moon-Ki; Han, Sang-Kook

    2014-03-01

    In this paper, we propose a novel fast adaptive approach that was applied to an OFDM-PON 20-km single fiber loopback transmission system to improve channel performance in term of stabilized BER below 2 × 10-3 and higher throughput beyond 10 Gb/s. The upstream transmission is performed through light source-seeded modulation using 1-GHz RSOA at the ONU. Experimental results indicated that the dynamic rate adaptation algorithm based on greedy Levin-Campello could be an effective solution to mitigate channel instability and data rate degradation caused by the Rayleigh back scattering effect and inefficient resource subcarrier allocation.

  1. The puzzle of partial migration: Adaptive dynamics and evolutionary game theory perspectives.

    Science.gov (United States)

    De Leenheer, Patrick; Mohapatra, Anushaya; Ohms, Haley A; Lytle, David A; Cushing, J M

    2017-01-07

    We consider the phenomenon of partial migration which is exhibited by populations in which some individuals migrate between habitats during their lifetime, but others do not. First, using an adaptive dynamics approach, we show that partial migration can be explained on the basis of negative density dependence in the per capita fertilities alone, provided that this density dependence is attenuated for increasing abundances of the subtypes that make up the population. We present an exact formula for the optimal proportion of migrants which is expressed in terms of the vital rates of migrant and non-migrant subtypes only. We show that this allocation strategy is both an evolutionary stable strategy (ESS) as well as a convergence stable strategy (CSS). To establish the former, we generalize the classical notion of an ESS because it is based on invasion exponents obtained from linearization arguments, which fail to capture the stabilizing effects of the nonlinear density dependence. These results clarify precisely when the notion of a "weak ESS", as proposed in Lundberg (2013) for a related model, is a genuine ESS. Secondly, we use an evolutionary game theory approach, and confirm, once again, that partial migration can be attributed to negative density dependence alone. In this context, the result holds even when density dependence is not attenuated. In this case, the optimal allocation strategy towards migrants is the same as the ESS stemming from the analysis based on the adaptive dynamics. The key feature of the population models considered here is that they are monotone dynamical systems, which enables a rather comprehensive mathematical analysis.

  2. NN-adaptive output feedback tracking control for a class of discrete-time non-affine systems with a dynamic compensator

    Science.gov (United States)

    Zhang, Lijun; Zhao, Jiemei; Qi, Xue; Jia, Heming

    2013-06-01

    The problem of tracking control for a class of uncertain non-affine discrete-time nonlinear systems with internal dynamics is addressed. The fixed point theorem is first employed to ensure the control problem in question is solvable and well-defined. Based on it, an adaptive output feedback control scheme based on neural network (NN) is presented. The proposed control algorithm consists of two parts: a dynamic compensator is introduced to stabilise the linear portion of the tracking error system; a single-hidden-layer neural network (SHL NN) approximation mechanism is introduced to cancel the uncertainties resulting from the non-affine function, where the recursive weight update rules of NN estimation are derived from the discrete-time version of Lyapunov control theory. Ultimate boundedness of the error signals is shown through Lyapunov's direct method and the discrete-time version of input-to-state stability (ISS) theory. Finally, a model of automatical underwater vehicle (AUV) is considered to show the effectiveness of the proposed control scheme.

  3. Quantifying the effect of heat stress on daily milk yield and monitoring dynamic changes using an adaptive dynamic model.

    Science.gov (United States)

    André, G; Engel, B; Berentsen, P B M; Vellinga, Th V; Lansink, A G J M Oude

    2011-09-01

    Automation and use of robots are increasingly being used within dairy farming and result in large amounts of real time data. This information provides a base for the new management concept of precision livestock farming. From 2003 to 2006, time series of herd mean daily milk yield were collected on 6 experimental research farms in the Netherlands. These time series were analyzed with an adaptive dynamic model following a Bayesian method to quantify the effect of heat stress. The effect of heat stress was quantified in terms of critical temperature above which heat stress occurred, duration of heat stress periods, and resulting loss in milk yield. In addition, dynamic changes in level and trend were monitored, including the estimation of a weekly pattern. Monitoring comprised detection of potential outliers and other deteriorations. The adaptive dynamic model fitted the data well; the root mean squared error of the forecasts ranged from 0.55 to 0.99 kg of milk/d. The percentages of potential outliers and signals for deteriorations ranged from 5.5 to 9.7%. The Bayesian procedure for time series analysis and monitoring provided a useful tool for process control. Online estimates (based on past and present only) and retrospective estimates (determined afterward from all data) of level and trend in daily milk yield showed an almost yearly cycle that was in agreement with the calving pattern: most cows calved in winter and early spring versus summer and autumn. Estimated weekly patterns in terms of weekday effects could be related to specific management actions, such as change of pasture during grazing. For the effect of heat stress, the mean estimated critical temperature above which heat stress was expected was 17.8±0.56°C. The estimated duration of the heat stress periods was 5.5±1.03 d, and the estimated loss was 31.4±12.2 kg of milk/cow per year. Farm-specific estimates are helpful to identify management factors like grazing, housing and feeding, that affect the

  4. Systems and Methods for Derivative-Free Adaptive Control

    Science.gov (United States)

    Yucelen, Tansel (Inventor); Kim, Kilsoo (Inventor); Calise, Anthony J. (Inventor)

    2015-01-01

    An adaptive control system is disclosed. The control system can control uncertain dynamic systems. The control system can employ one or more derivative-free adaptive control architectures. The control system can further employ one or more derivative-free weight update laws. The derivative-free weight update laws can comprise a time-varying estimate of an ideal vector of weights. The control system of the present invention can therefore quickly stabilize systems that undergo sudden changes in dynamics, caused by, for example, sudden changes in weight. Embodiments of the present invention can also provide a less complex control system than existing adaptive control systems. The control system can control aircraft and other dynamic systems, such as, for example, those with non-minimum phase dynamics.

  5. Paxos based directory updates for geo-replicated cloud storage

    OpenAIRE

    Rangarajan, Srivathsava

    2014-01-01

    Modern cloud data stores (e.g., Spanner, Cassandra) replicate data across geographically distributed data centers for availability, redundancy and optimized latencies.^ An important class of cloud data stores involves the use of directories to track the location of individual data objects. Directory-based datastores allow flexible data placement, and the ability to adapt placement in response to changing workload dynamics. However, a key challenge is maintaining and updating the directory sta...

  6. Adaptive Anchoring Model: How Static and Dynamic Presentations of Time Series Influence Judgments and Predictions.

    Science.gov (United States)

    Kusev, Petko; van Schaik, Paul; Tsaneva-Atanasova, Krasimira; Juliusson, Asgeir; Chater, Nick

    2017-04-06

    When attempting to predict future events, people commonly rely on historical data. One psychological characteristic of judgmental forecasting of time series, established by research, is that when people make forecasts from series, they tend to underestimate future values for upward trends and overestimate them for downward ones, so-called trend-damping (modeled by anchoring on, and insufficient adjustment from, the average of recent time series values). Events in a time series can be experienced sequentially (dynamic mode), or they can also be retrospectively viewed simultaneously (static mode), not experienced individually in real time. In one experiment, we studied the influence of presentation mode (dynamic and static) on two sorts of judgment: (a) predictions of the next event (forecast) and (b) estimation of the average value of all the events in the presented series (average estimation). Participants' responses in dynamic mode were anchored on more recent events than in static mode for all types of judgment but with different consequences; hence, dynamic presentation improved prediction accuracy, but not estimation. These results are not anticipated by existing theoretical accounts; we develop and present an agent-based model-the adaptive anchoring model (ADAM)-to account for the difference between processing sequences of dynamically and statically presented stimuli (visually presented data). ADAM captures how variation in presentation mode produces variation in responses (and the accuracy of these responses) in both forecasting and judgment tasks. ADAM's model predictions for the forecasting and judgment tasks fit better with the response data than a linear-regression time series model. Moreover, ADAM outperformed autoregressive-integrated-moving-average (ARIMA) and exponential-smoothing models, while neither of these models accounts for people's responses on the average estimation task. Copyright © 2017 The Authors. Cognitive Science published by Wiley

  7. Robust dynamic sliding-mode control using adaptive RENN for magnetic levitation system.

    Science.gov (United States)

    Lin, Faa-Jeng; Chen, Syuan-Yi; Shyu, Kuo-Kai

    2009-06-01

    In this paper, a robust dynamic sliding mode control system (RDSMC) using a recurrent Elman neural network (RENN) is proposed to control the position of a levitated object of a magnetic levitation system considering the uncertainties. First, a dynamic model of the magnetic levitation system is derived. Then, a proportional-integral-derivative (PID)-type sliding-mode control system (SMC) is adopted for tracking of the reference trajectories. Moreover, a new PID-type dynamic sliding-mode control system (DSMC) is proposed to reduce the chattering phenomenon. However, due to the hardware being limited and the uncertainty bound being unknown of the switching function for the DSMC, an RDSMC is proposed to improve the control performance and further increase the robustness of the magnetic levitation system. In the RDSMC, an RENN estimator is used to estimate an unknown nonlinear function of lumped uncertainty online and replace the switching function in the hitting control of the DSMC directly. The adaptive learning algorithms that trained the parameters of the RENN online are derived using Lyapunov stability theorem. Furthermore, a robust compensator is proposed to confront the uncertainties including approximation error, optimal parameter vectors, and higher order terms in Taylor series. Finally, some experimental results of tracking the various periodic trajectories demonstrate the validity of the proposed RDSMC for practical applications.

  8. Iterative Adaptive Dynamic Programming for Solving Unknown Nonlinear Zero-Sum Game Based on Online Data.

    Science.gov (United States)

    Zhu, Yuanheng; Zhao, Dongbin; Li, Xiangjun

    2017-03-01

    H∞ control is a powerful method to solve the disturbance attenuation problems that occur in some control systems. The design of such controllers relies on solving the zero-sum game (ZSG). But in practical applications, the exact dynamics is mostly unknown. Identification of dynamics also produces errors that are detrimental to the control performance. To overcome this problem, an iterative adaptive dynamic programming algorithm is proposed in this paper to solve the continuous-time, unknown nonlinear ZSG with only online data. A model-free approach to the Hamilton-Jacobi-Isaacs equation is developed based on the policy iteration method. Control and disturbance policies and value are approximated by neural networks (NNs) under the critic-actor-disturber structure. The NN weights are solved by the least-squares method. According to the theoretical analysis, our algorithm is equivalent to a Gauss-Newton method solving an optimization problem, and it converges uniformly to the optimal solution. The online data can also be used repeatedly, which is highly efficient. Simulation results demonstrate its feasibility to solve the unknown nonlinear ZSG. When compared with other algorithms, it saves a significant amount of online measurement time.

  9. Adaptive Indoor Positioning Model Based on WLAN-Fingerprinting for Dynamic and Multi-Floor Environments

    Directory of Open Access Journals (Sweden)

    Iyad Husni Alshami

    2017-08-01

    Full Text Available The Global Positioning System demonstrates the significance of Location Based Services but it cannot be used indoors due to the lack of line of sight between satellites and receivers. Indoor Positioning Systems are needed to provide indoor Location Based Services. Wireless LAN fingerprints are one of the best choices for Indoor Positioning Systems because of their low cost, and high accuracy, however they have many drawbacks: creating radio maps is time consuming, the radio maps will become outdated with any environmental change, different mobile devices read the received signal strength (RSS differently, and peoples’ presence in LOS between access points and mobile device affects the RSS. This research proposes a new Adaptive Indoor Positioning System model (called DIPS based on: a dynamic radio map generator, RSS certainty technique and peoples’ presence effect integration for dynamic and multi-floor environments. Dynamic in our context refers to the effects of people and device heterogeneity. DIPS can achieve 98% and 92% positioning accuracy for floor and room positioning, and it achieves 1.2 m for point positioning error. RSS certainty enhanced the positioning accuracy for floor and room for different mobile devices by 11% and 9%. Then by considering the peoples’ presence effect, the error is reduced by 0.2 m. In comparison with other works, DIPS achieves better positioning without extra devices.

  10. The adaptive dynamics of Lotka-Volterra systems with trade-offs.

    Science.gov (United States)

    Bowers, Roger G; White, Andrew

    2002-02-01

    We analyse the adaptive dynamics of a generalised type of Lotka-Volterra model subject to an explicit trade-off between two parameters. A simple expression for the fitness of a mutant strategy in an environment determined by the established, resident strategy is obtained leading to general results for the position of the evolutionary singular strategy and the associated second-order partial derivatives of the mutant fitness with respect to the mutant and resident strategies. Combinations of these results can be used to determine the evolutionary behaviour of the system. The theory is motivated by an example of prey evolution in a predator-prey system in which results show that only (non-EUS) evolutionary repellor dynamics, where evolution is directed away from a singular strategy, or dynamics where the singular strategy is an evolutionary attractor, are possible. Moreover, the general theory can be used to show that these results are the only possibility for all Lotka-Volterra systems in which aside from the trade-offs all parameters are independent and in which the interaction terms are of quadratic order or less. The applicability of the theory is highlighted by examining the evolution of an intermediate predator in a tri-trophic model.

  11. Data-based virtual unmodeled dynamics driven multivariable nonlinear adaptive switching control.

    Science.gov (United States)

    Chai, Tianyou; Zhang, Yajun; Wang, Hong; Su, Chun-Yi; Sun, Jing

    2011-12-01

    For a complex industrial system, its multivariable and nonlinear nature generally make it very difficult, if not impossible, to obtain an accurate model, especially when the model structure is unknown. The control of this class of complex systems is difficult to handle by the traditional controller designs around their operating points. This paper, however, explores the concepts of controller-driven model and virtual unmodeled dynamics to propose a new design framework. The design consists of two controllers with distinct functions. First, using input and output data, a self-tuning controller is constructed based on a linear controller-driven model. Then the output signals of the controller-driven model are compared with the true outputs of the system to produce so-called virtual unmodeled dynamics. Based on the compensator of the virtual unmodeled dynamics, the second controller based on a nonlinear controller-driven model is proposed. Those two controllers are integrated by an adaptive switching control algorithm to take advantage of their complementary features: one offers stabilization function and another provides improved performance. The conditions on the stability and convergence of the closed-loop system are analyzed. Both simulation and experimental tests on a heavily coupled nonlinear twin-tank system are carried out to confirm the effectiveness of the proposed method.

  12. Reduced short term adaptation to robot generated dynamic environment in children affected by Cerebral Palsy

    Directory of Open Access Journals (Sweden)

    Di Rosa Giuseppe

    2011-05-01

    Full Text Available Abstract Background It is known that healthy adults can quickly adapt to a novel dynamic environment, generated by a robotic manipulandum as a structured disturbing force field. We suggest that it may be of clinical interest to evaluate to which extent this kind of motor learning capability is impaired in children affected by cerebal palsy. Methods We adapted the protocol already used with adults, which employs a velocity dependant viscous field, and compared the performance of a group of subjects affected by Cerebral Palsy (CP group, 7 subjects with a Control group of unimpaired age-matched children. The protocol included a familiarization phase (FA, during which no force was applied, a force field adaptation phase (CF, and a wash-out phase (WO in which the field was removed. During the CF phase the field was shut down in a number of randomly selected "catch" trials, which were used in order to evaluate the "learning index" for each single subject and the two groups. Lateral deviation, speed and acceleration peaks and average speed were evaluated for each trajectory; a directional analysis was performed in order to inspect the role of the limb's inertial anisotropy in the different experimental phases. Results During the FA phase the movements of the CP subjects were more curved, displaying greater and variable directional error; over the course of the CF phase both groups showed a decreasing trend in the lateral error and an after-effect at the beginning of the wash-out, but the CP group had a non significant adaptation rate and a lower learning index, suggesting that CP subjects have reduced ability to learn to compensate external force. Moreover, a directional analysis of trajectories confirms that the control group is able to better predict the force field by tuning the kinematic features of the movements along different directions in order to account for the inertial anisotropy of arm. Conclusions Spatial abnormalities in children affected

  13. Reduced short term adaptation to robot generated dynamic environment in children affected by Cerebral Palsy

    Science.gov (United States)

    2011-01-01

    Background It is known that healthy adults can quickly adapt to a novel dynamic environment, generated by a robotic manipulandum as a structured disturbing force field. We suggest that it may be of clinical interest to evaluate to which extent this kind of motor learning capability is impaired in children affected by cerebal palsy. Methods We adapted the protocol already used with adults, which employs a velocity dependant viscous field, and compared the performance of a group of subjects affected by Cerebral Palsy (CP group, 7 subjects) with a Control group of unimpaired age-matched children. The protocol included a familiarization phase (FA), during which no force was applied, a force field adaptation phase (CF), and a wash-out phase (WO) in which the field was removed. During the CF phase the field was shut down in a number of randomly selected "catch" trials, which were used in order to evaluate the "learning index" for each single subject and the two groups. Lateral deviation, speed and acceleration peaks and average speed were evaluated for each trajectory; a directional analysis was performed in order to inspect the role of the limb's inertial anisotropy in the different experimental phases. Results During the FA phase the movements of the CP subjects were more curved, displaying greater and variable directional error; over the course of the CF phase both groups showed a decreasing trend in the lateral error and an after-effect at the beginning of the wash-out, but the CP group had a non significant adaptation rate and a lower learning index, suggesting that CP subjects have reduced ability to learn to compensate external force. Moreover, a directional analysis of trajectories confirms that the control group is able to better predict the force field by tuning the kinematic features of the movements along different directions in order to account for the inertial anisotropy of arm. Conclusions Spatial abnormalities in children affected by cerebral palsy may be

  14. Reduced short term adaptation to robot generated dynamic environment in children affected by Cerebral Palsy.

    Science.gov (United States)

    Masia, Lorenzo; Frascarelli, Flaminia; Morasso, Pietro; Di Rosa, Giuseppe; Petrarca, Maurizio; Castelli, Enrico; Cappa, Paolo

    2011-05-21

    It is known that healthy adults can quickly adapt to a novel dynamic environment, generated by a robotic manipulandum as a structured disturbing force field. We suggest that it may be of clinical interest to evaluate to which extent this kind of motor learning capability is impaired in children affected by cerebal palsy. We adapted the protocol already used with adults, which employs a velocity dependant viscous field, and compared the performance of a group of subjects affected by Cerebral Palsy (CP group, 7 subjects) with a Control group of unimpaired age-matched children. The protocol included a familiarization phase (FA), during which no force was applied, a force field adaptation phase (CF), and a wash-out phase (WO) in which the field was removed. During the CF phase the field was shut down in a number of randomly selected "catch" trials, which were used in order to evaluate the "learning index" for each single subject and the two groups. Lateral deviation, speed and acceleration peaks and average speed were evaluated for each trajectory; a directional analysis was performed in order to inspect the role of the limb's inertial anisotropy in the different experimental phases. During the FA phase the movements of the CP subjects were more curved, displaying greater and variable directional error; over the course of the CF phase both groups showed a decreasing trend in the lateral error and an after-effect at the beginning of the wash-out, but the CP group had a non significant adaptation rate and a lower learning index, suggesting that CP subjects have reduced ability to learn to compensate external force. Moreover, a directional analysis of trajectories confirms that the control group is able to better predict the force field by tuning the kinematic features of the movements along different directions in order to account for the inertial anisotropy of arm. Spatial abnormalities in children affected by cerebral palsy may be related not only to disturbance in

  15. Adaptive Output Feedback Control for a Class of Stochastic Nonlinear Systems with SiISS Inverse Dynamics

    Directory of Open Access Journals (Sweden)

    Na Duan

    2012-01-01

    Full Text Available The adaptive stabilization scheme based on tuning function for stochastic nonlinear systems with stochastic integral input-to-state stability (SiISS inverse dynamics is investigated. By combining the stochastic LaSalle theorem and small-gain type conditions on SiISS, an adaptive output feedback controller is constructively designed. It is shown that all the closed-loop signals are bounded almost surely and the stochastic closed-loop system is globally stable in probability.

  16. Approaches to adaptive digital control focusing on the second order modal descriptions of large, flexible spacecraft dynamics

    Science.gov (United States)

    Johnson, C. R., Jr.

    1979-01-01

    The widespread modal analysis of flexible spacecraft and recognition of the poor a priori parameterization possible of the modal descriptions of individual structures have prompted the consideration of adaptive modal control strategies for distributed parameter systems. The current major approaches to computationally efficient adaptive digital control useful in these endeavors are explained in an original, lucid manner using modal second order structure dynamics for algorithm explication. Difficulties in extending these lumped-parameter techniques to distributed-parameter system expansion control are cited.

  17. A Novel Fuzzy Logic Based Adaptive Super-Twisting Sliding Mode Control Algorithm for Dynamic Uncertain Systems

    OpenAIRE

    Abdul Kareem; Mohammad Fazle Azeem

    2012-01-01

    This paper presents a novel fuzzy logic based Adaptive Super-twisting Sliding Mode Controller for the control of dynamic uncertain systems. The proposed controller combines the advantages of Second order Sliding Mode Control, Fuzzy Logic Control and Adaptive Control. The reaching conditions, stability and robustness of the system with the proposed controller are guaranteed. In addition, the proposed controller is well suited for simple design and implementation. The effectiveness ...

  18. Individualised and adaptive upper limb rehabilitation with industrial robot using dynamic movement primitives

    DEFF Research Database (Denmark)

    Nielsen, Jacob; Sørensen, Anders Stengaard; Christensen, Thomas Søndergaard

    Stroke is a leading cause of serious long-term disability. Post-stroke rehabilitation is a demanding task for the patient and a costly challenge for both society and healthcare systems. We present a novel approach for training of upper extremities after a stroke by utilising an industrial robotic...... arm and dynamic movement primitives (DMPs) with force feedback. We show how pre-recorded and learned DMPs can act as basis exercises, that can be modified into individualized and adaptive rehabilitation exercises that fit with the patient’s physical prop- erties and impairments. We conclude that our...... novel approach allows for easy and flexible set-up of rehabilitation exercises and has the potential to provide the therapists and patients much easier interaction with such complex technology...

  19. Adaptive fuzzy dynamic surface control for the chaotic permanent magnet synchronous motor using Nussbaum gain

    Energy Technology Data Exchange (ETDEWEB)

    Luo, Shaohua [School of Automation, Chongqing University, Chongqing 400044, China and College of Mechanical Engineering, Hunan University of Arts and Science, Hunan 415000 (China)

    2014-09-01

    This paper is concerned with the problem of adaptive fuzzy dynamic surface control (DSC) for the permanent magnet synchronous motor (PMSM) system with chaotic behavior, disturbance and unknown control gain and parameters. Nussbaum gain is adopted to cope with the situation that the control gain is unknown. And the unknown items can be estimated by fuzzy logic system. The proposed controller guarantees that all the signals in the closed-loop system are bounded and the system output eventually converges to a small neighborhood of the desired reference signal. Finally, the numerical simulations indicate that the proposed scheme can suppress the chaos of PMSM and show the effectiveness and robustness of the proposed method.

  20. Emerging roles of tRNA in adaptive translation, signalling dynamics and disease.

    Science.gov (United States)

    Kirchner, Sebastian; Ignatova, Zoya

    2015-02-01

    tRNAs, nexus molecules between mRNAs and proteins, have a central role in translation. Recent discoveries have revealed unprecedented complexity of tRNA biosynthesis, modification patterns, regulation and function. In this Review, we present emerging concepts regarding how tRNA abundance is dynamically regulated and how tRNAs (and their nucleolytic fragments) are centrally involved in stress signalling and adaptive translation, operating across a wide range of timescales. Mutations in tRNAs or in genes affecting tRNA biogenesis are also linked to complex human diseases with surprising heterogeneity in tissue vulnerability, and we highlight cell-specific aspects that modulate the disease penetrance of tRNA-based pathologies.

  1. Adaptive polarization image fusion based on regional energy dynamic weighted average

    Institute of Scientific and Technical Information of China (English)

    ZHAO Yong-qiang; PAN Quan; ZHANG Hong-cai

    2005-01-01

    According to the principle of polarization imaging and the relation between Stokes parameters and the degree of linear polarization, there are much redundant and complementary information in polarized images. Since man-made objects and natural objects can be easily distinguished in images of degree of linear polarization and images of Stokes parameters contain rich detailed information of the scene, the clutters in the images can be removed efficiently while the detailed information can be maintained by combining these images. An algorithm of adaptive polarization image fusion based on regional energy dynamic weighted average is proposed in this paper to combine these images. Through an experiment and simulations,most clutters are removed by this algorithm. The fusion method is used for different light conditions in simulation, and the influence of lighting conditions on the fusion results is analyzed.

  2. Adaptive fuzzy dynamic surface control for the chaotic permanent magnet synchronous motor using Nussbaum gain

    Science.gov (United States)

    Luo, Shaohua

    2014-09-01

    This paper is concerned with the problem of adaptive fuzzy dynamic surface control (DSC) for the permanent magnet synchronous motor (PMSM) system with chaotic behavior, disturbance and unknown control gain and parameters. Nussbaum gain is adopted to cope with the situation that the control gain is unknown. And the unknown items can be estimated by fuzzy logic system. The proposed controller guarantees that all the signals in the closed-loop system are bounded and the system output eventually converges to a small neighborhood of the desired reference signal. Finally, the numerical simulations indicate that the proposed scheme can suppress the chaos of PMSM and show the effectiveness and robustness of the proposed method.

  3. Dynamical Adaptive Integral Sliding Backstepping Control of Nonlinear Nontriangular Uncertain Systems

    Directory of Open Access Journals (Sweden)

    Mahmood Pervaiz

    2014-01-01

    Full Text Available We present a control strategy for nonlinear nontriangular uncertain systems. The proposed control method is a synergy between the dynamic adaptive backstepping (DAB and integral sliding mode (ISM and is referred to as DAB-ISMC. Our main objective is to find a recursive procedure to transform a nontriangular system into an implementable form that enables designing a control law which almost eliminates the reaching-phase. The proposed method further facilitates minimization of chattering which is believed to be a shortcoming of the sliding mode control. In this methodology, the ISM, as an integrated subsystem of DAB, is introduced at the final stage of backstepping. This strategy works very well to obtain a system that is robust against model imperfections, matching and unmatching uncertainties. The DAB-ISMC method is applied on a continuous stirred tank reactor (CSTR and simulation results obtained on Matlab are found to be very promising.

  4. Consensus for Multiagent Systems with Nonlinear Dynamics and Time Delays Using a Two-Hop Relay Adaptive Method

    Directory of Open Access Journals (Sweden)

    Qian Cao

    2014-01-01

    Full Text Available This paper investigates the consensus problem for multiagent systems with nonlinear dynamics and time delays. A distributed adaptive consensus protocol is proposed in which the time delays are explicitly included in the adaptive algorithm. It is shown that the resultant closed loop system involves doubly larger time delays, making the stability analysis nontrivial. Stability condition on maximum tolerable time delay is established and controlled by the proposed two-hop adaptive algorithm. The explicit expression of the delay margin is derived and analyzed in the frequency domain. Both the agent state errors and the estimation parameter errors converge to zero. A simulation example is illustrated to verify the theory results.

  5. Adaptive Fuzzy Control for Nonstrict Feedback Systems With Unmodeled Dynamics and Fuzzy Dead Zone via Output Feedback.

    Science.gov (United States)

    Wang, Lijie; Li, Hongyi; Zhou, Qi; Lu, Renquan

    2017-09-01

    This paper investigates the problem of observer-based adaptive fuzzy control for a category of nonstrict feedback systems subject to both unmodeled dynamics and fuzzy dead zone. Through constructing a fuzzy state observer and introducing a center of gravity method, unmeasurable states are estimated and the fuzzy dead zone is defuzzified, respectively. By employing fuzzy logic systems to identify the unknown functions. And combining small-gain approach with adaptive backstepping control technique, a novel adaptive fuzzy output feedback control strategy is developed, which ensures that all signals involved are semi-globally uniformly bounded. Simulation results are given to demonstrate the effectiveness of the presented method.

  6. Physiological complexity and system adaptability: evidence from postural control dynamics of older adults.

    Science.gov (United States)

    Manor, Brad; Costa, Madalena D; Hu, Kun; Newton, Elizabeth; Starobinets, Olga; Kang, Hyun Gu; Peng, C K; Novak, Vera; Lipsitz, Lewis A

    2010-12-01

    The degree of multiscale complexity in human behavioral regulation, such as that required for postural control, appears to decrease with advanced aging or disease. To help delineate causes and functional consequences of complexity loss, we examined the effects of visual and somatosensory impairment on the complexity of postural sway during quiet standing and its relationship to postural adaptation to cognitive dual tasking. Participants of the MOBILIZE Boston Study were classified into mutually exclusive groups: controls [intact vision and foot somatosensation, n = 299, 76 ± 5 (SD) yr old], visual impairment only (Postural sway (i.e., center-of-pressure) dynamics were assessed during quiet standing and cognitive dual tasking, and a complexity index was quantified using multiscale entropy analysis. Postural sway speed and area, which did not correlate with complexity, were also computed. During quiet standing, the complexity index (mean ± SD) was highest in controls (9.5 ± 1.2) and successively lower in the visual (9.1 ± 1.1), somatosensory (8.6 ± 1.6), and combined (7.8 ± 1.3) impairment groups (P = 0.001). Dual tasking resulted in increased sway speed and area but reduced complexity (P postural sway speed from quiet standing to dual-tasking conditions. Sensory impairments contributed to decreased postural sway complexity, which reflected reduced adaptive capacity of the postural control system. Relatively low baseline complexity may, therefore, indicate control systems that are more vulnerable to cognitive and other stressors.

  7. [Dynamics of adaptation processes and morbidity risk for the popupation of the territory of industrial cities].

    Science.gov (United States)

    Prusakov, V M; Prusakova, A V

    2014-01-01

    There was investigated the character of the adaptation processes in the population residing in conditions ofprolonged exposure to environmental pollution in the territory of the industrial cities of the Irkutsk region in order to identify the possible periodicity of their manifestations in the formation of the morbidity risk for the population of different age groups. Under conditions of prolonged exposure to air pollution and other adverse unfavorable factors of industrial cities in the population of all age groups long cyclic changes of adaptation processes in the body in the form of repeated 11-15-years cycles in which a period of relative destabilization of physiological functions with lowered resistance is replaced by the period with the state of elevated nonspecific resistance were established to be observed. Undulating changes of the dynamics of the relative risks of general morbidity should be considered in the assessment of the medical and environmental situation in the territory and making the managing decisions at the base on the data of public health monitoring.

  8. Integrating dynamic stopping, transfer learning and language models in an adaptive zero-training ERP speller

    Science.gov (United States)

    Kindermans, Pieter-Jan; Tangermann, Michael; Müller, Klaus-Robert; Schrauwen, Benjamin

    2014-06-01

    Objective. Most BCIs have to undergo a calibration session in which data is recorded to train decoders with machine learning. Only recently zero-training methods have become a subject of study. This work proposes a probabilistic framework for BCI applications which exploit event-related potentials (ERPs). For the example of a visual P300 speller we show how the framework harvests the structure suitable to solve the decoding task by (a) transfer learning, (b) unsupervised adaptation, (c) language model and (d) dynamic stopping. Approach. A simulation study compares the proposed probabilistic zero framework (using transfer learning and task structure) to a state-of-the-art supervised model on n = 22 subjects. The individual influence of the involved components (a)-(d) are investigated. Main results. Without any need for a calibration session, the probabilistic zero-training framework with inter-subject transfer learning shows excellent performance—competitive to a state-of-the-art supervised method using calibration. Its decoding quality is carried mainly by the effect of transfer learning in combination with continuous unsupervised adaptation. Significance. A high-performing zero-training BCI is within reach for one of the most popular BCI paradigms: ERP spelling. Recording calibration data for a supervised BCI would require valuable time which is lost for spelling. The time spent on calibration would allow a novel user to spell 29 symbols with our unsupervised approach. It could be of use for various clinical and non-clinical ERP-applications of BCI.

  9. Evolutionary dynamics of molecular markers during local adaptation: a case study in Drosophila subobscura

    Directory of Open Access Journals (Sweden)

    Matos Margarida

    2009-06-01

    Full Text Available Abstract Here we present a correction to our article "Evolutionary dynamics of molecular markers during local adaptation: a case study in Drosophila subobscura". We have recently detected an error concerning the application of the Ln RH formula – a test to detect positive selection – to our microsatellite data. Here we provide the corrected data and discuss its implications for our overall findings. The corrections presented here have produced some changes relative to our previous results, namely in a locus (dsub14 that presents indications of being affected by positive selection. In general, our populations present less consistent indications of positive selection for this particular locus in both periods studied – between generations 3 and 14 and between generation 14 and 40 of laboratory adaptation. Despite this, the main findings of our study regarding the possibility of positive selection acting on that particular microsatellite still hold. As previously concluded in our article, further studies should be performed on this specific microsatellite locus (and neighboring areas to elucidate in greater detail the evolutionary forces acting on this specific region of the O chromosome of Drosophila subobscura.

  10. Adaptive robust stabilisation for a class of uncertain nonlinear time-delay dynamical systems

    Science.gov (United States)

    Wu, Hansheng

    2013-02-01

    The problem of adaptive robust stabilisation is considered for a class of uncertain nonlinear dynamical systems with multiple time-varying delays. It is assumed that the upper bounds of the nonlinear delayed state perturbations are unknown and that the time-varying delays are any non-negative continuous and bounded functions which do not require that their derivatives have to be less than one. In particular, it is only required that the nonlinear uncertainties, which can also include time-varying delays, are bounded in any non-negative nonlinear functions which are not required to be known for the system designer. For such a class of uncertain nonlinear time-delay systems, a new method is presented whereby a class of continuous memoryless adaptive robust state feedback controllers with a rather simpler structure is proposed. It is also shown that the solutions of uncertain nonlinear time-delay systems can be guaranteed to be uniformly exponentially convergent towards a ball which can be as small as desired. Finally, as an application, an uncertain nonlinear time-delay ecosystem with two competing species is given to demonstrate the validity of the results.

  11. Adaptive Neural Control of Pure-Feedback Nonlinear Time-Delay Systems via Dynamic Surface Technique.

    Science.gov (United States)

    Min Wang; Xiaoping Liu; Peng Shi

    2011-12-01

    This paper is concerned with robust stabilization problem for a class of nonaffine pure-feedback systems with unknown time-delay functions and perturbed uncertainties. Novel continuous packaged functions are introduced in advance to remove unknown nonlinear terms deduced from perturbed uncertainties and unknown time-delay functions, which avoids the functions with control law to be approximated by radial basis function (RBF) neural networks. This technique combining implicit function and mean value theorems overcomes the difficulty in controlling the nonaffine pure-feedback systems. Dynamic surface control (DSC) is used to avoid "the explosion of complexity" in the backstepping design. Design difficulties from unknown time-delay functions are overcome using the function separation technique, the Lyapunov-Krasovskii functionals, and the desirable property of hyperbolic tangent functions. RBF neural networks are employed to approximate desired virtual controls and desired practical control. Under the proposed adaptive neural DSC, the number of adaptive parameters required is reduced significantly, and semiglobal uniform ultimate boundedness of all of the signals in the closed-loop system is guaranteed. Simulation studies are given to demonstrate the effectiveness of the proposed design scheme.

  12. Dynamics of genetic variability in Anastrepha fraterculus (Diptera: Tephritidae) during adaptation to laboratory rearing conditions.

    Science.gov (United States)

    Parreño, María A; Scannapieco, Alejandra C; Remis, María I; Juri, Marianela; Vera, María T; Segura, Diego F; Cladera, Jorge L; Lanzavecchia, Silvia B

    2014-01-01

    Anastrepha fraterculus is one of the most important fruit fly plagues in the American continent and only chemical control is applied in the field to diminish its population densities. A better understanding of the genetic variability during the introduction and adaptation of wild A. fraterculus populations to laboratory conditions is required for the development of stable and vigorous experimental colonies and mass-reared strains in support of successful Sterile Insect Technique (SIT) efforts. The present study aims to analyze the dynamics of changes in genetic variability during the first six generations under artificial rearing conditions in two populations: a) a wild population recently introduced to laboratory culture, named TW and, b) a long-established control line, named CL. Results showed a declining tendency of genetic variability in TW. In CL, the relatively high values of genetic variability appear to be maintained across generations and could denote an intrinsic capacity to avoid the loss of genetic diversity in time. The impact of evolutionary forces on this species during the adaptation process as well as the best approach to choose strategies to introduce experimental and mass-reared A. fraterculus strains for SIT programs are discussed.

  13. TCP throughput adaptation in WiMax networks using replicator dynamics.

    Science.gov (United States)

    Anastasopoulos, Markos P; Petraki, Dionysia K; Kannan, Rajgopal; Vasilakos, Athanasios V

    2010-06-01

    The high-frequency segment (10-66 GHz) of the IEEE 802.16 standard seems promising for the implementation of wireless backhaul networks carrying large volumes of Internet traffic. In contrast to wireline backbone networks, where channel errors seldom occur, the TCP protocol in IEEE 802.16 Worldwide Interoperability for Microwave Access networks is conditioned exclusively by wireless channel impairments rather than by congestion. This renders a cross-layer design approach between the transport and physical layers more appropriate during fading periods. In this paper, an adaptive coding and modulation (ACM) scheme for TCP throughput maximization is presented. In the current approach, Internet traffic is modulated and coded employing an adaptive scheme that is mathematically equivalent to the replicator dynamics model. The stability of the proposed ACM scheme is proven, and the dependence of the speed of convergence on various physical-layer parameters is investigated. It is also shown that convergence to the strategy that maximizes TCP throughput may be further accelerated by increasing the amount of information from the physical layer.

  14. Noise in adaptive interferometric fiber sensor based on population dynamic grating in erbium-doped fiber.

    Science.gov (United States)

    Stepanov, Serguei; Sánchez, Marcos Plata; Hernández, Eliseo Hernández

    2016-09-10

    Experimental investigations of the main noise sources that limit the sensitivity of the adaptive interferometric all-fiber sensors operating in the communication wavelength region are reported. Adaptive properties (i.e., the autostabilization of an optimal operation point of the interferometer) are enabled by the dynamic population grating recorded in a segment of the erbium-doped fiber (EDF) at milliwatt-scale cw power in the 1480-1560 nm spectral range. The utilized symmetric Sagnac configuration with low light internal reflections ensures reduced sensitivity of the sensor to phase noise of the laser, while intensity noise is reduced to an insignificant level by the balanced detection scheme. It is shown that the fluorescence from the erbium ions, excited by the counterpropagating waves recording the grating, increases the noise level from the fundamental shot noise approximately by a factor of 2-3 only. It is also shown that conventional communication distributed feedback (DFB) semiconductor lasers with megahertz linewidth are not suitable for high-sensitivity applications of such sensors. Because of inevitable backreflections from the output terminal devices (photodiodes, insulators, circulator), the above-mentioned fundamental noise level is increased by 2 orders of magnitude due to high phase noise of the DFB laser.

  15. Dynamic Adaptive Median Filter (DAMF for Removal of High Density Impulse Noise

    Directory of Open Access Journals (Sweden)

    Punyaban Patel

    2012-10-01

    Full Text Available This paper proposes a novel adaptive filtering scheme to remove impulse noise from images. The scheme replaces the corrupted test pixel with the median value of non-corrupted neighboring pixels selected from a window dynamically. If the number of non-corrupted pixels in the selected window is not sufficient, a window of next higher size is chosen. Thus window size is automatically adapted based on the density of noise in the image as well as the density of corruption local to a window. As a result window size may vary pixel to pixel while filtering. The scheme is simple to implement and do not require multiple iterations. The efficacy of the proposed scheme is evaluated with respect to subjective as well as objective parameters on standard images on various noise densities. Comparative analysis reveals that the proposed scheme has improved performance over other schemes, preferably in high density impulse noise cases. Further, the computational overhead is also less as compared its competent scheme.

  16. A Dynamically Adaptable Impedance-Matching System for Midrange Wireless Power Transfer with Misalignment

    Directory of Open Access Journals (Sweden)

    Thuc Phi Duong

    2015-07-01

    Full Text Available To enable the geometrical freedom envisioned for wireless power transfer (WPT, fast dynamic adaptation to unpredictable changes in receiver position is needed. In this paper, we propose an adaptive impedance-searching system that achieves good impedance matching quickly. For fast and robust operation, the proposed method consists of three steps: system calibration, coarse search, and fine search. The proposed WPT system is characterized using distance variation and lateral and angular misalignment between coils. The measured results indicate that the proposed method significantly reduces searching time from a few minutes to approximately one second. Furthermore, the proposed system achieves impedance matching with good accuracy. The robust impedance-searching capability of the proposed system significantly improves power transfer efficiency. At 6.78 MHz, we achieve a maximum efficiency of 89.7% and a high efficiency of >80% up to a distance of 50 cm. When the center-to-center misalignment is 35 cm, the efficiency is improved from 48.4% to 74.1% with the proposed method. At a distance of 40 cm, the efficiency is higher than 74% for up to 60° of angular rotation. These results agree well with the simulated results obtained using a lumped-element circuit model.

  17. Integrating dynamic stopping, transfer learning and language models in an adaptive zero-training ERP speller.

    Science.gov (United States)

    Kindermans, Pieter-Jan; Tangermann, Michael; Müller, Klaus-Robert; Schrauwen, Benjamin

    2014-06-01

    Most BCIs have to undergo a calibration session in which data is recorded to train decoders with machine learning. Only recently zero-training methods have become a subject of study. This work proposes a probabilistic framework for BCI applications which exploit event-related potentials (ERPs). For the example of a visual P300 speller we show how the framework harvests the structure suitable to solve the decoding task by (a) transfer learning, (b) unsupervised adaptation, (c) language model and (d) dynamic stopping. A simulation study compares the proposed probabilistic zero framework (using transfer learning and task structure) to a state-of-the-art supervised model on n = 22 subjects. The individual influence of the involved components (a)-(d) are investigated. Without any need for a calibration session, the probabilistic zero-training framework with inter-subject transfer learning shows excellent performance--competitive to a state-of-the-art supervised method using calibration. Its decoding quality is carried mainly by the effect of transfer learning in combination with continuous unsupervised adaptation. A high-performing zero-training BCI is within reach for one of the most popular BCI paradigms: ERP spelling. Recording calibration data for a supervised BCI would require valuable time which is lost for spelling. The time spent on calibration would allow a novel user to spell 29 symbols with our unsupervised approach. It could be of use for various clinical and non-clinical ERP-applications of BCI.

  18. Micro-Level Adaptation, Macro-Level Selection, and the Dynamics of Market Partitioning.

    Science.gov (United States)

    García-Díaz, César; van Witteloostuijn, Arjen; Péli, Gábor

    2015-01-01

    This paper provides a micro-foundation for dual market structure formation through partitioning processes in marketplaces by developing a computational model of interacting economic agents. We propose an agent-based modeling approach, where firms are adaptive and profit-seeking agents entering into and exiting from the market according to their (lack of) profitability. Our firms are characterized by large and small sunk costs, respectively. They locate their offerings along a unimodal demand distribution over a one-dimensional product variety, with the distribution peak constituting the center and the tails standing for the peripheries. We found that large firms may first advance toward the most abundant demand spot, the market center, and release peripheral positions as predicted by extant dual market explanations. However, we also observed that large firms may then move back toward the market fringes to reduce competitive niche overlap in the center, triggering nonlinear resource occupation behavior. Novel results indicate that resource release dynamics depend on firm-level adaptive capabilities, and that a minimum scale of production for low sunk cost firms is key to the formation of the dual structure.

  19. MEKANISME SEGMENTASI LAJU BIT PADA DYNAMIC ADAPTIVE STREAMING OVER HTTP (DASH UNTUK APLIKASI VIDEO STREAMING

    Directory of Open Access Journals (Sweden)

    Muhammad Audy Bazly

    2015-12-01

    Full Text Available This paper aims to analyze Internet-based streaming video service in the communication media with variable bit rates. The proposed scheme on Dynamic Adaptive Streaming over HTTP (DASH using the internet network that adapts to the protocol Hyper Text Transfer Protocol (HTTP. DASH technology allows a video in the video segmentation into several packages that will distreamingkan. DASH initial stage is to compress the video source to lower the bit rate video codec uses H.26. Video compressed further in the segmentation using MP4Box generates streaming packets with the specified duration. These packages are assembled into packets in a streaming media format Presentation Description (MPD or known as MPEG-DASH. Streaming video format MPEG-DASH run on a platform with the player bitdash teritegrasi bitcoin. With this scheme, the video will have several variants of the bit rates that gave rise to the concept of scalability of streaming video services on the client side. The main target of the mechanism is smooth the MPEG-DASH streaming video display on the client. The simulation results show that the scheme based scalable video streaming MPEG- DASH able to improve the quality of image display on the client side, where the procedure bufering videos can be made constant and fine for the duration of video views

  20. Output Feedback Adaptive Dynamic Surface Control of Permanent Magnet Synchronous Motor with Uncertain Time Delays via RBFNN

    Directory of Open Access Journals (Sweden)

    Shaohua Luo

    2014-01-01

    Full Text Available This paper focuses on an adaptive dynamic surface control based on the Radial Basis Function Neural Network for a fourth-order permanent magnet synchronous motor system wherein the unknown parameters, disturbances, chaos, and uncertain time delays are presented. Neural Network systems are used to approximate the nonlinearities and an adaptive law is employed to estimate accurate parameters. Then, a simple and effective controller has been obtained by introducing dynamic surface control technique on the basis of first-order filters. Asymptotically tracking stability in the sense of uniformly ultimate boundedness is achieved in a short time. Finally, the performance of the proposed control has been illustrated through simulation results.

  1. Analysis of Static and Dynamic E-Reference Content at a Multi-Campus University Shows, that Updated Content is Associated with Greater Annual Usage

    Directory of Open Access Journals (Sweden)

    Laura Costello

    2016-03-01

    Full Text Available Objective – To discover whether there is a difference in use over time between dynamically updated and changing subscription e-reference titles and collections, and static purchased e-reference titles and collections. Design – Case study. Setting – A multi-campus Canadian university with 9,200 students enrolled in both graduate and undergraduate programs. Subjects – E-reference book packages and individual e-reference titles. Methods – The author compared data from individual e-reference books and packages. First, individual subscription e-reference books that periodically added updated content were compared to individually purchased e-reference books that remained static after purchase. The author then compared two e-reference book packages that provided new and updated content to two static e-reference book packages. The author compared data from patron usage to new content added over time using regression analysis. Main Results – As the library acquired e-reference titles, dynamic title subscriptions added to the collection were associated with 2,246 to 4,635 views per subscription while static title additions were associated with 8 to 123 views per purchase. The author also found that there was a strong linear relationship between views and dynamic titles added to the collection (R2=0.79 and a very weak linear relationship (R2=0.18 with views when static titles are added to the collection. Regression analysis of dynamic e-reference collections revealed that the number of titles added to each collection was strongly associated with views of the material (R2=0.99, while static e-reference collections were less strongly linked (R2=0.43. Conclusion – Dynamic e-reference titles and collections experienced increases in usage each year while static titles and collections experienced decreases in usage. This indicates that collections and titles that offer new content to users each year will continue to see growth in usage while static

  2. Societal transformation and adaptation necessary to manage dynamics in flood hazard and risk mitigation (TRANS-ADAPT)

    Science.gov (United States)

    Fuchs, Sven; Thaler, Thomas; Bonnefond, Mathieu; Clarke, Darren; Driessen, Peter; Hegger, Dries; Gatien-Tournat, Amandine; Gralepois, Mathilde; Fournier, Marie; Mees, Heleen; Murphy, Conor; Servain-Courant, Sylvie

    2015-04-01

    Facing the challenges of climate change, this project aims to analyse and to evaluate the multiple use of flood alleviation schemes with respect to social transformation in communities exposed to flood hazards in Europe. The overall goals are: (1) the identification of indicators and parameters necessary for strategies to increase societal resilience, (2) an analysis of the institutional settings needed for societal transformation, and (3) perspectives of changing divisions of responsibilities between public and private actors necessary to arrive at more resilient societies. This proposal assesses societal transformations from the perspective of changing divisions of responsibilities between public and private actors necessary to arrive at more resilient societies. Yet each risk mitigation measure is built on a narrative of exchanges and relations between people and therefore may condition the outputs. As such, governance is done by people interacting and defining risk mitigation measures as well as climate change adaptation are therefore simultaneously both outcomes of, and productive to, public and private responsibilities. Building off current knowledge this project will focus on different dimensions of adaptation and mitigation strategies based on social, economic and institutional incentives and settings, centring on the linkages between these different dimensions and complementing existing flood risk governance arrangements. The policy dimension of adaptation, predominantly decisions on the societal admissible level of vulnerability and risk, will be evaluated by a human-environment interaction approach using multiple methods and the assessment of social capacities of stakeholders across scales. As such, the challenges of adaptation to flood risk will be tackled by converting scientific frameworks into practical assessment and policy advice. In addressing the relationship between these dimensions of adaptation on different temporal and spatial scales, this

  3. COLLABORATIVE RESEARCH: CONTINUOUS DYNAMIC GRID ADAPTATION IN A GLOBAL ATMOSPHERIC MODEL: APPLICATION AND REFINEMENT

    Energy Technology Data Exchange (ETDEWEB)

    Gutowski, William J.; Prusa, Joseph M.; Smolarkiewicz, Piotr K.

    2012-05-08

    This project had goals of advancing the performance capabilities of the numerical general circulation model EULAG and using it to produce a fully operational atmospheric global climate model (AGCM) that can employ either static or dynamic grid stretching for targeted phenomena. The resulting AGCM combined EULAG's advanced dynamics core with the "physics" of the NCAR Community Atmospheric Model (CAM). Effort discussed below shows how we improved model performance and tested both EULAG and the coupled CAM-EULAG in several ways to demonstrate the grid stretching and ability to simulate very well a wide range of scales, that is, multi-scale capability. We leveraged our effort through interaction with an international EULAG community that has collectively developed new features and applications of EULAG, which we exploited for our own work summarized here. Overall, the work contributed to over 40 peer-reviewed publications and over 70 conference/workshop/seminar presentations, many of them invited. 3a. EULAG Advances EULAG is a non-hydrostatic, parallel computational model for all-scale geophysical flows. EULAG's name derives from its two computational options: EULerian (flux form) or semi-LAGrangian (advective form). The model combines nonoscillatory forward-in-time (NFT) numerical algorithms with a robust elliptic Krylov solver. A signature feature of EULAG is that it is formulated in generalized time-dependent curvilinear coordinates. In particular, this enables grid adaptivity. In total, these features give EULAG novel advantages over many existing dynamical cores. For EULAG itself, numerical advances included refining boundary conditions and filters for optimizing model performance in polar regions. We also added flexibility to the model's underlying formulation, allowing it to work with the pseudo-compressible equation set of Durran in addition to EULAG's standard anelastic formulation. Work in collaboration with others also extended the

  4. Adaptive resolution simulation of a biomolecule and its hydration shell: Structural and dynamical properties

    Science.gov (United States)

    Fogarty, Aoife C.; Potestio, Raffaello; Kremer, Kurt

    2015-05-01

    A fully atomistic modelling of many biophysical and biochemical processes at biologically relevant length- and time scales is beyond our reach with current computational resources, and one approach to overcome this difficulty is the use of multiscale simulation techniques. In such simulations, when system properties necessitate a boundary between resolutions that falls within the solvent region, one can use an approach such as the Adaptive Resolution Scheme (AdResS), in which solvent particles change their resolution on the fly during the simulation. Here, we apply the existing AdResS methodology to biomolecular systems, simulating a fully atomistic protein with an atomistic hydration shell, solvated in a coarse-grained particle reservoir and heat bath. Using as a test case an aqueous solution of the regulatory protein ubiquitin, we first confirm the validity of the AdResS approach for such systems, via an examination of protein and solvent structural and dynamical properties. We then demonstrate how, in addition to providing a computational speedup, such a multiscale AdResS approach can yield otherwise inaccessible physical insights into biomolecular function. We use our methodology to show that protein structure and dynamics can still be correctly modelled using only a few shells of atomistic water molecules. We also discuss aspects of the AdResS methodology peculiar to biomolecular simulations.

  5. Spectral assessment of mesh adaptations for the analysis of the dynamical longitudinal behavior of railway bridges

    Energy Technology Data Exchange (ETDEWEB)

    Toth, J. [Inst. for Transportation Technologies, FAMU-FSU College of Engineering, Tallahassee, FL (United States); Ruge, P. [Inst. of Dynamics of Structures, Dresden Univ. of Technology (Germany)

    2001-07-01

    Extensive studies, concerning the longitudinal behavior of long railway bridges due to braking forces have been done by measurements in situ, and by statical, as well as dynamical simulations. Thereby, the only consistent numerical realization with respect to the measured data was the dynamical one. However, the consecutive discretizations in space and time with time-dependent system matrices are extremely time consuming due to the moving loads and varying stiffness of the ballast under, and in front of, the moving train. Therefore, every effort should be made to optimize the discretization in the space domain. This paper presents a strategy for assessing the quality of finite elements in space and for applying an adaptive mesh-refinement for this special engineering problem. The method is characterized by a spectral assessment, comparing a certain set of eigenvalues of the actual discretization with those of a very fine and rather exact numerical model. The error estimator introduced in this paper controls a whole set of global eigenvalues with corresponding natural vibration modes in order to assess certain types of shape functions. Thus, the procedure estimates local modifications on the one hand and p-properties on the other by means of global indication. (orig.)

  6. Adaptive resolution simulation of a biomolecule and its hydration shell: Structural and dynamical properties

    Energy Technology Data Exchange (ETDEWEB)

    Fogarty, Aoife C., E-mail: fogarty@mpip-mainz.mpg.de; Potestio, Raffaello, E-mail: potestio@mpip-mainz.mpg.de; Kremer, Kurt, E-mail: kremer@mpip-mainz.mpg.de [Max Planck Institute for Polymer Research, Ackermannweg 10, 55128 Mainz (Germany)

    2015-05-21

    A fully atomistic modelling of many biophysical and biochemical processes at biologically relevant length- and time scales is beyond our reach with current computational resources, and one approach to overcome this difficulty is the use of multiscale simulation techniques. In such simulations, when system properties necessitate a boundary between resolutions that falls within the solvent region, one can use an approach such as the Adaptive Resolution Scheme (AdResS), in which solvent particles change their resolution on the fly during the simulation. Here, we apply the existing AdResS methodology to biomolecular systems, simulating a fully atomistic protein with an atomistic hydration shell, solvated in a coarse-grained particle reservoir and heat bath. Using as a test case an aqueous solution of the regulatory protein ubiquitin, we first confirm the validity of the AdResS approach for such systems, via an examination of protein and solvent structural and dynamical properties. We then demonstrate how, in addition to providing a computational speedup, such a multiscale AdResS approach can yield otherwise inaccessible physical insights into biomolecular function. We use our methodology to show that protein structure and dynamics can still be correctly modelled using only a few shells of atomistic water molecules. We also discuss aspects of the AdResS methodology peculiar to biomolecular simulations.

  7. Highly Dynamic and Adaptive Traffic Congestion Avoidance in Real-Time Inspired by Honey Bee Behavior

    Science.gov (United States)

    Wedde, Horst F.; Lehnhoff, Sebastian; van Bonn, Bernhard; Bay, Z.; Becker, S.; Böttcher, S.; Brunner, C.; Büscher, A.; Fürst, T.; Lazarescu, A. M.; Rotaru, E.; Senge, S.; Steinbach, B.; Yilmaz, F.; Zimmermann, T.

    Traffic congestions have become a major problem in metropolitan areas world-wide, within and between cities, to an extent where they make driving and transportation times largely unpredictable. Due to the highly dynamic character of congestion building and dissolving this phenomenon appears even to resist a formal treatment. Static approaches, and even more their global management, have proven counterproductive in practice. Given the latest progress in VANET technology and the remarkable commercially driven efforts like in the European C2C consortium, or the VSC Project in the US, allow meanwhile to tackle various aspects of traffic regulation through VANET communication. In this paper we introduce a novel, completely decentralized multi-agent routing algorithm (termed BeeJamA) which we have derived from the foraging behavior of honey bees. It is highly dynamic, adaptive, robust, and scalable, and it allows for both avoiding congestions, and minimizing traveling times to individual destinations. Vehicle guidance is provided well ahead of every intersection, depending on the individual speeds. Thus strict deadlines are imposed on, and respected by, the BeeJamA algorithm. We report on extensive simulation experiments which show the superior performance of BeeJamA over conventional approaches.

  8. The canonical equation of adaptive dynamics for Mendelian diploids and haplo-diploids

    Science.gov (United States)

    Metz, Johan A. J.; de Kovel, Carolien G. F.

    2013-01-01

    One of the powerful tools of adaptive dynamics is its so-called canonical equation (CE), a differential equation describing how the prevailing trait vector changes over evolutionary time. The derivation of the CE is based on two simplifying assumptions, separation of population dynamical and mutational time scales and small mutational steps. (It may appear that these two conditions rarely go together. However, for small step sizes the time-scale separation need not be very strict.) The CE was derived in 1996, with mathematical rigour being added in 2003. Both papers consider only well-mixed clonal populations with the simplest possible life histories. In 2008, the CE's reach was heuristically extended to locally well-mixed populations with general life histories. We, again heuristically, extend it further to Mendelian diploids and haplo-diploids. Away from strict time-scale separation the CE does an even better approximation job in the Mendelian than in the clonal case owing to gene substitutions occurring effectively in parallel, which obviates slowing down by clonal interference. PMID:24516713

  9. High-dynamic range compressive spectral imaging by grayscale coded aperture adaptive filtering

    Directory of Open Access Journals (Sweden)

    Nelson Eduardo Diaz

    2015-12-01

    Full Text Available The coded aperture snapshot spectral imaging system (CASSI is an imaging architecture which senses the three dimensional informa-tion of a scene with two dimensional (2D focal plane array (FPA coded projection measurements. A reconstruction algorithm takes advantage of the compressive measurements sparsity to recover the underlying 3D data cube. Traditionally, CASSI uses block-un-block coded apertures (BCA to spatially modulate the light. In CASSI the quality of the reconstructed images depends on the design of these coded apertures and the FPA dynamic range. This work presents a new CASSI architecture based on grayscaled coded apertu-res (GCA which reduce the FPA saturation and increase the dynamic range of the reconstructed images. The set of GCA is calculated in a real-time adaptive manner exploiting the information from the FPA compressive measurements. Extensive simulations show the attained improvement in the quality of the reconstructed images when GCA are employed.  In addition, a comparison between traditional coded apertures and GCA is realized with respect to noise tolerance.

  10. Transforming the sensing and numerical prediction of high-impact local weather through dynamic adaptation.

    Science.gov (United States)

    Droegemeier, Kelvin K

    2009-03-13

    Mesoscale weather, such as convective systems, intense local rainfall resulting in flash floods and lake effect snows, frequently is characterized by unpredictable rapid onset and evolution, heterogeneity and spatial and temporal intermittency. Ironically, most of the technologies used to observe the atmosphere, predict its evolution and compute, transmit or store information about it, operate in a static pre-scheduled framework that is fundamentally inconsistent with, and does not accommodate, the dynamic behaviour of mesoscale weather. As a result, today's weather technology is highly constrained and far from optimal when applied to any particular situation. This paper describes a new cyberinfrastructure framework, in which remote and in situ atmospheric sensors, data acquisition and storage systems, assimilation and prediction codes, data mining and visualization engines, and the information technology frameworks within which they operate, can change configuration automatically, in response to evolving weather. Such dynamic adaptation is designed to allow system components to achieve greater overall effectiveness, relative to their static counterparts, for any given situation. The associated service-oriented architecture, known as Linked Environments for Atmospheric Discovery (LEAD), makes advanced meteorological and cyber tools as easy to use as ordering a book on the web. LEAD has been applied in a variety of settings, including experimental forecasting by the US National Weather Service, and allows users to focus much more attention on the problem at hand and less on the nuances of data formats, communication protocols and job execution environments.

  11. Adaptive Generalized Projective Synchronization of Takagi-Sugeno Fuzzy Drive-response Dynamical Networks with Time Delay

    Science.gov (United States)

    Zheng, Yong-Ai

    2012-02-01

    Time-delay Takagi-Sugeno fuzzy drive-response dynamical networks (TD-TSFDRDNs) are defined by extending the drive-response dynamical networks. Based on the LaSalle invariant principle, a simple and systematic adaptive control scheme is proposed to synchronize the TD-TSFDRDNs with a desired scalar factor. A sufficient condition for the generalized projective synchronization in TD-TSFDRDNs is derived. Moreover, numerical simulations are provided to verify the correctness and effectiveness of the scheme.

  12. Coupled Flow-Structure-Biochemistry Simulations of Dynamic Systems of Blood Cells Using an Adaptive Surface Tracking Method

    OpenAIRE

    Hoskins, M.H.; Kunz, R.F.; Bistline, J.E.; Dong, C.

    2009-01-01

    A method for the computation of low Reynolds number dynamic blood cell systems is presented. The specific system of interest here is interaction between cancer cells and white blood cells in an experimental flow system. Fluid dynamics, structural mechanics, six-degree-of freedom motion control and surface biochemistry analysis components are coupled in the context of adaptive octree-based grid generation. Analytical and numerical verification of the quasi-steady assumption for the fluid mecha...

  13. Optimized adaptation algorithm for HEVC/H.265 dynamic adaptive streaming over HTTP using variable segment duration

    Science.gov (United States)

    Irondi, Iheanyi; Wang, Qi; Grecos, Christos

    2016-04-01

    Adaptive video streaming using HTTP has become popular in recent years for commercial video delivery. The recent MPEG-DASH standard allows interoperability and adaptability between servers and clients from different vendors. The delivery of the MPD (Media Presentation Description) files in DASH and the DASH client behaviours are beyond the scope of the DASH standard. However, the different adaptation algorithms employed by the clients do affect the overall performance of the system and users' QoE (Quality of Experience), hence the need for research in this field. Moreover, standard DASH delivery is based on fixed segments of the video. However, there is no standard segment duration for DASH where various fixed segment durations have been employed by different commercial solutions and researchers with their own individual merits. Most recently, the use of variable segment duration in DASH has emerged but only a few preliminary studies without practical implementation exist. In addition, such a technique requires a DASH client to be aware of segment duration variations, and this requirement and the corresponding implications on the DASH system design have not been investigated. This paper proposes a segment-duration-aware bandwidth estimation and next-segment selection adaptation strategy for DASH. Firstly, an MPD file extension scheme to support variable segment duration is proposed and implemented in a realistic hardware testbed. The scheme is tested on a DASH client, and the tests and analysis have led to an insight on the time to download next segment and the buffer behaviour when fetching and switching between segments of different playback durations. Issues like sustained buffering when switching between segments of different durations and slow response to changing network conditions are highlighted and investigated. An enhanced adaptation algorithm is then proposed to accurately estimate the bandwidth and precisely determine the time to download the next

  14. Application of Non-Kolmogorovian Probability and Quantum Adaptive Dynamics to Unconscious Inference in Visual Perception Process

    Science.gov (United States)

    Accardi, Luigi; Khrennikov, Andrei; Ohya, Masanori; Tanaka, Yoshiharu; Yamato, Ichiro

    2016-07-01

    Recently a novel quantum information formalism — quantum adaptive dynamics — was developed and applied to modelling of information processing by bio-systems including cognitive phenomena: from molecular biology (glucose-lactose metabolism for E.coli bacteria, epigenetic evolution) to cognition, psychology. From the foundational point of view quantum adaptive dynamics describes mutual adapting of the information states of two interacting systems (physical or biological) as well as adapting of co-observations performed by the systems. In this paper we apply this formalism to model unconscious inference: the process of transition from sensation to perception. The paper combines theory and experiment. Statistical data collected in an experimental study on recognition of a particular ambiguous figure, the Schröder stairs, support the viability of the quantum(-like) model of unconscious inference including modelling of biases generated by rotation-contexts. From the probabilistic point of view, we study (for concrete experimental data) the problem of contextuality of probability, its dependence on experimental contexts. Mathematically contextuality leads to non-Komogorovness: probability distributions generated by various rotation contexts cannot be treated in the Kolmogorovian framework. At the same time they can be embedded in a “big Kolmogorov space” as conditional probabilities. However, such a Kolmogorov space has too complex structure and the operational quantum formalism in the form of quantum adaptive dynamics simplifies the modelling essentially.

  15. Failure of large transformation projects from the viewpoint of complex adaptive systems: Management principles for dealing with project dynamics

    NARCIS (Netherlands)

    Janssen, M.; Voort, H. van der; Veenstra, A.F.E. van

    2015-01-01

    Many large transformation projects do not result in the outcomes desired or envisioned by the stakeholders. This type of project is characterised by dynamics which are both caused by and result of uncertainties and unexpected behaviour. In this paper a complex adaptive system (CAS) view was adopted

  16. Computer assisted dynamic adaptive policy design for sustainable water management in river deltas in a changing environment

    NARCIS (Netherlands)

    Kwakkel, J.H.; Haasnoot, M.

    2012-01-01

    Sustainable water management in a changing environment full of uncertainty is a profound challenge. To deal with uncertainties, dynamic adaptive policies can be used. Such policies can change over time in response to how the future unfolds, to what we learn about the system, to changes in environmen

  17. Dynamic DNS update security, based on cryptographically generated addresses and ID-based cryptography, in an IPv6 autoconfiguration context

    OpenAIRE

    Combes, Jean-Michel; Arfaoui, Ghada; LAURENT, Maryline

    2012-01-01

    International audience; This paper proposes a new security method for protecting signalling for Domain Name System (DNS) architecture. That is, it makes secure DNS update messages for binding a Fully Qualified Domain Name (FQDN) of an IPv6 node and the IPv6 address of the node owning this FQDN. This method is based on the use of Cryptographically Generated Addresses (CGA) and IDBased Cryptography (IBC). Combination of these two techniques allows DNS server to check the ownership of the IPv6 a...

  18. Adaptive current compensation with nonlinear disturbance observer for single-sided linear induction motor considering dynamic eddy-effect

    Institute of Scientific and Technical Information of China (English)

    DENG Jiang-ming; CHEN Te-fang; CHEN Chun-yang

    2015-01-01

    An adaptive current compensation control for a single-sided linear induction motor (SLIM) with nonlinear disturbance observer was developed. First, to maintaint-axis secondary component flux constant with consideration of the specially dynamic eddy-effect (DEE) of the SLIM, a instantaneously tracing compensation ofm-axis current component was analyzed. Second, adaptive current compensation based on Taylor-discretization algorithm was proposed. Third, an effective kind of nonlinear disturbance observer (NDOB) was employed to estimate and compensate the undesired load vibrations, then the robustness of the control system could be guaranteed. Experimental verification of the feasibility of the proposed method for an SLIM control system was performed, and it showed that the proposed adaptive compensation scheme with NDOB could significantly promote speed dynamical response and minimize speed ripple under the conditions of external load coupled vibrations and unavoidable feedback control variables measured errors, i.e., current and speed.

  19. STEADY ESTIMATION ALGORITHMS OF THE DYNAMIC SYSTEMS CONDITION ON THE BASIS OF CONCEPTS OF THE ADAPTIVE FILTRATION AND CONTROL

    Directory of Open Access Journals (Sweden)

    H.Z. Igamberdiyev

    2014-07-01

    Full Text Available Dynamic systems condition estimation regularization algorithms in the conditions of signals and hindrances statistical characteristics aprioristic uncertainty are offered. Regular iterative algorithms of strengthening matrix factor elements of the Kalman filter, allowing to adapt the filter to changing hindrance-alarm conditions are developed. Steady adaptive estimation algorithms of a condition vector in the aprioristic uncertainty conditions of covariance matrixes of object noise and the measurements hindrances providing a certain roughness of filtration process in relation to changing statistical characteristics of signals information parameters are offered. Offered practical realization results of the dynamic systems condition estimation algorithms are given at the adaptive management systems synthesis problems solution by technological processes of granulation drying of an ammophos pulp and receiving ammonia.

  20. An adaptive overcurrent protection in smart distribution grid

    DEFF Research Database (Denmark)

    Bhattarai, Bishnu Prasad; Bak-Jensen, Birgitte; Chaudhary, Sanjay Kumar

    2015-01-01

    High penetration of distributed energy resources (DERs) creates various protection challenges, such as protection blinding, false tripping, unsynchronized reclosing, etc. Additionally, adaptation of active network management approaches namely demand response and network reconfiguration also threats...... existing protection practice. In this study, a combination of a local adaptive and communication assisted central protection is proposed, whereby the relay settings are dynamically updated based on online identification of the network topologies and status of DERs. Particularly, the local adaptive...... protection updates relay settings based on DERs status (ON/OFF) employing locally acquired information, whereas the centralized protection updates the relay settings during major changes in grid topologies: network reconfiguration and switching between islanded and gridconnected modes. The effectiveness...