Robust dynamic classes revealed by measuring the response function of a social system.
Crane, Riley; Sornette, Didier
2008-10-14
We study the relaxation response of a social system after endogenous and exogenous bursts of activity using the time series of daily views for nearly 5 million videos on YouTube. We find that most activity can be described accurately as a Poisson process. However, we also find hundreds of thousands of examples in which a burst of activity is followed by an ubiquitous power-law relaxation governing the timing of views. We find that these relaxation exponents cluster into three distinct classes and allow for the classification of collective human dynamics. This is consistent with an epidemic model on a social network containing two ingredients: a power-law distribution of waiting times between cause and action and an epidemic cascade of actions becoming the cause of future actions. This model is a conceptual extension of the fluctuation-dissipation theorem to social systems [Ruelle, D (2004) Phys Today 57:48-53] and [Roehner BM, et al., (2004) Int J Mod Phys C 15:809-834], and provides a unique framework for the investigation of timing in complex systems.
Dynamics robustness of cascading systems.
Directory of Open Access Journals (Sweden)
Jonathan T Young
2017-03-01
Full Text Available A most important property of biochemical systems is robustness. Static robustness, e.g., homeostasis, is the insensitivity of a state against perturbations, whereas dynamics robustness, e.g., homeorhesis, is the insensitivity of a dynamic process. In contrast to the extensively studied static robustness, dynamics robustness, i.e., how a system creates an invariant temporal profile against perturbations, is little explored despite transient dynamics being crucial for cellular fates and are reported to be robust experimentally. For example, the duration of a stimulus elicits different phenotypic responses, and signaling networks process and encode temporal information. Hence, robustness in time courses will be necessary for functional biochemical networks. Based on dynamical systems theory, we uncovered a general mechanism to achieve dynamics robustness. Using a three-stage linear signaling cascade as an example, we found that the temporal profiles and response duration post-stimulus is robust to perturbations against certain parameters. Then analyzing the linearized model, we elucidated the criteria of when signaling cascades will display dynamics robustness. We found that changes in the upstream modules are masked in the cascade, and that the response duration is mainly controlled by the rate-limiting module and organization of the cascade's kinetics. Specifically, we found two necessary conditions for dynamics robustness in signaling cascades: 1 Constraint on the rate-limiting process: The phosphatase activity in the perturbed module is not the slowest. 2 Constraints on the initial conditions: The kinase activity needs to be fast enough such that each module is saturated even with fast phosphatase activity and upstream changes are attenuated. We discussed the relevance of such robustness to several biological examples and the validity of the above conditions therein. Given the applicability of dynamics robustness to a variety of systems, it
Tiwari, Shivendra N.; Padhi, Radhakant
2018-01-01
Following the philosophy of adaptive optimal control, a neural network-based state feedback optimal control synthesis approach is presented in this paper. First, accounting for a nominal system model, a single network adaptive critic (SNAC) based multi-layered neural network (called as NN1) is synthesised offline. However, another linear-in-weight neural network (called as NN2) is trained online and augmented to NN1 in such a manner that their combined output represent the desired optimal costate for the actual plant. To do this, the nominal model needs to be updated online to adapt to the actual plant, which is done by synthesising yet another linear-in-weight neural network (called as NN3) online. Training of NN3 is done by utilising the error information between the nominal and actual states and carrying out the necessary Lyapunov stability analysis using a Sobolev norm based Lyapunov function. This helps in training NN2 successfully to capture the required optimal relationship. The overall architecture is named as 'Dynamically Re-optimised single network adaptive critic (DR-SNAC)'. Numerical results for two motivating illustrative problems are presented, including comparison studies with closed form solution for one problem, which clearly demonstrate the effectiveness and benefit of the proposed approach.
Robustness Analysis of Dynamic Watermarks
Directory of Open Access Journals (Sweden)
Ivan V. Nechta
2017-06-01
Full Text Available In this paper we consider previously known scheme of dynamic watermarks embedding (Ra- dix-n that is used for preventing illegal use of software. According to the scheme a watermark is dynamic linked data structure (graph, which is created in memory during program execution. Hidden data, such as information about author, can be represented in a different type of graph structure. This data can be extracted and demonstrated in judicial proceedings. This paper declared that the above mentioned scheme was previously one of the most reliable, has a number of features that allows an attacker to detect a stage of watermark construction in the program, and therefore it can be corrupted or deleted. The author of this article shows the weakness of Radix-N scheme, which consists in the fact that we can reveal dynamic data structures of a program by using information received from some API-functions hooker which catches function calls of dynamic memory allocation. One of these data structures is the watermark. Pointers on dynamically created objects (arrays, variables, class items, etc. of a program can be detected by content analysis of computer's RAM. Different dynamic objects in memory interconnected by pointers form dynamic data structures of a program such as lists, stacks, trees and other graphs (including the watermark. Our experiment shows that in the vast majority of cases the amount of data structure in programs is small, which increases probability of a successful attack. Also we present an algorithm for finding connected components of a graph with linear time-consuming in cases where the number of nodes is about 106. On the basis of the experimental findings the new watermarking scheme has been presented, which is resistant to the proposed attack. It is offered to use different graph structure representation of a watermark, where edges are implemented using unique signatures. Our scheme uses content encrypting of graph nodes (except signature
Robust adaptive synchronization of general dynamical networks ...
Indian Academy of Sciences (India)
Robust adaptive synchronization; dynamical network; multiple delays; multiple uncertainties. ... Networks such as neural networks, communication transmission networks, social rela- tionship networks etc. ..... a very good effect. Pramana – J.
Robust control synthesis for uncertain dynamical systems
Byun, Kuk-Whan; Wie, Bong; Sunkel, John
1989-01-01
This paper presents robust control synthesis techniques for uncertain dynamical systems subject to structured parameter perturbation. Both QFT (quantitative feedback theory) and H-infinity control synthesis techniques are investigated. Although most H-infinity-related control techniques are not concerned with the structured parameter perturbation, a new way of incorporating the parameter uncertainty in the robust H-infinity control design is presented. A generic model of uncertain dynamical systems is used to illustrate the design methodologies investigated in this paper. It is shown that, for a certain noncolocated structural control problem, use of both techniques results in nonminimum phase compensation.
Robust synchronization of a class of chaotic networks
Czech Academy of Sciences Publication Activity Database
Čelikovský, Sergej; Lynnyk, Volodymyr; Chen, G.
2013-01-01
Roč. 350, č. 10 (2013), s. 2936-2948 ISSN 0016-0032 R&D Projects: GA ČR(CZ) GAP103/12/1794 Institutional support: RVO:67985556 Keywords : generalized Lorenz system * robust synchronization * dynamical complex network Subject RIV: BC - Control Systems Theory Impact factor: 2.260, year: 2013 http://library.utia.cas.cz/separaty/2013/TR/celikovsky-0398127.pdf
Robustness of dynamic systems with parameter uncertainties
Balemi, S; Truöl, W
1992-01-01
Robust Control is one of the fastest growing and promising areas of research today. In many practical systems there exist uncertainties which have to be considered in the analysis and design of control systems. In the last decade methods were developed for dealing with dynamic systems with unstructured uncertainties such as HOO_ and £I-optimal control. For systems with parameter uncertainties, the seminal paper of V. L. Kharitonov has triggered a large amount of very promising research. An international workshop dealing with all aspects of robust control was successfully organized by S. P. Bhattacharyya and L. H. Keel in San Antonio, Texas, USA in March 1991. We organized the second international workshop in this area in Ascona, Switzer land in April 1992. However, this second workshop was restricted to robust control of dynamic systems with parameter uncertainties with the objective to concentrate on some aspects of robust control. This book contains a collection of papers presented at the International W...
Robust transient dynamics and brain functions
Directory of Open Access Journals (Sweden)
Mikhail I Rabinovich
2011-06-01
Full Text Available In the last few decades several concepts of Dynamical Systems Theory (DST have guided psychologists, cognitive scientists, and neuroscientists to rethink about sensory motor behavior and embodied cognition. A critical step in the progress of DST application to the brain (supported by modern methods of brain imaging and multi-electrode recording techniques has been the transfer of its initial success in motor behavior to mental function, i.e., perception, emotion, and cognition. Open questions from research in genetics, ecology, brain sciences, etc. have changed DST itself and lead to the discovery of a new dynamical phenomenon, i.e., reproducible and robust transients that are at the same time sensitive to informational signals. The goal of this review is to describe a new mathematical framework -heteroclinic sequential dynamics- to understand self-organized activity in the brain that can explain certain aspects of robust itinerant behavior. Specifically, we discuss a hierarchy of coarse-grain models of mental dynamics in the form of kinetic equations of modes. These modes compete for resources at three levels: (i within the same modality, (ii among different modalities from the same family (like perception, and (iii among modalities from different families (like emotion and cognition. The analysis of the conditions for robustness, i.e., the structural stability of transient (sequential dynamics, give us the possibility to explain phenomena like the finite capacity of our sequential working memory -a vital cognitive function-, and to find specific dynamical signatures -different kinds of instabilities- of several brain functions and mental diseases.
Synchronization of a class of chaotic signals via robust observer design
Energy Technology Data Exchange (ETDEWEB)
Aguilar-Lopez, Ricardo [Departamento de Energia, Universidad Autonoma Metropolitana - Azcapotzalco, San Pablo 180, Reynosa-Tamaulipas, Azcapotzalco 02200, Mexico, D.F. (Mexico)], E-mail: raguilar@correo.azc.uam.mx; Martinez-Guerra, Rafael [Departamento de Energia, Universidad Autonoma Metropolitana - Azcapotzalco, San Pablo 180, Reynosa-Tamaulipas, Azcapotzalco 02200, Mexico, D.F. (Mexico); Departamento de Control Automatico, CINVESTAV IPN, Apartado Postal 14-740, Mexico, D.F. C.P. 07360 (Mexico)], E-mail: rguerra@ctrl.cinvestav.mx
2008-07-15
In this paper the signal synchronization of a class of chaotic systems based on robust observer design is tackled. The task is the synchronization of the signals generated by two Chen oscillators with different initial condition. The proposed observer is robust against model uncertainties and noisy output measurements. An alternative system representation is proposed to transform the measured disturbance onto system disturbance, which leads a more adequate observer structure. The proposed methodology contains an uncertainty estimator based on the predictive contribution to infer the unobservable uncertainties and corrective contribution to estimate the observable uncertainties; which provides robustness against noisy measurements and model uncertainties. Convergence analysis of the proposed estimation methodology is realized, analyzing the dynamic equation of the estimation error, where asymptotic convergence is shown. Numerical experiments illustrate the good performance of the proposed methodology.
Synchronization of a class of chaotic signals via robust observer design
International Nuclear Information System (INIS)
Aguilar-Lopez, Ricardo; Martinez-Guerra, Rafael
2008-01-01
In this paper the signal synchronization of a class of chaotic systems based on robust observer design is tackled. The task is the synchronization of the signals generated by two Chen oscillators with different initial condition. The proposed observer is robust against model uncertainties and noisy output measurements. An alternative system representation is proposed to transform the measured disturbance onto system disturbance, which leads a more adequate observer structure. The proposed methodology contains an uncertainty estimator based on the predictive contribution to infer the unobservable uncertainties and corrective contribution to estimate the observable uncertainties; which provides robustness against noisy measurements and model uncertainties. Convergence analysis of the proposed estimation methodology is realized, analyzing the dynamic equation of the estimation error, where asymptotic convergence is shown. Numerical experiments illustrate the good performance of the proposed methodology
Robust w-Estimators for Cryo-EM Class Means
Huang, Chenxi; Tagare, Hemant D.
2016-01-01
A critical step in cryogenic electron microscopy (cryo-EM) image analysis is to calculate the average of all images aligned to a projection direction. This average, called the “class mean”, improves the signal-to-noise ratio in single particle reconstruction (SPR). The averaging step is often compromised because of outlier images of ice, contaminants, and particle fragments. Outlier detection and rejection in the majority of current cryo-EM methods is done using cross-correlation with a manually determined threshold. Empirical assessment shows that the performance of these methods is very sensitive to the threshold. This paper proposes an alternative: a “w-estimator” of the average image, which is robust to outliers and which does not use a threshold. Various properties of the estimator, such as consistency and influence function are investigated. An extension of the estimator to images with different contrast transfer functions (CTFs) is also provided. Experiments with simulated and real cryo-EM images show that the proposed estimator performs quite well in the presence of outliers. PMID:26841397
Robust adaptive synchronization of general dynamical networks ...
Indian Academy of Sciences (India)
Home; Journals; Pramana – Journal of Physics; Volume 86; Issue 6. Robust ... 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 ...
Robust adaptive fuzzy neural tracking control for a class of unknown ...
Indian Academy of Sciences (India)
In this paper, an adaptive fuzzy neural controller (AFNC) for a class of unknown chaotic systems is ... The robust controller is used to guarantee the stability and to control the per- ..... From the above analysis we have the following theorem:.
Robust filtering and prediction for systems with embedded finite-state Markov-Chain dynamics
International Nuclear Information System (INIS)
Pate, E.B.
1986-01-01
This research developed new methodologies for the design of robust near-optimal filters/predictors for a class of system models that exhibit embedded finite-state Markov-chain dynamics. These methodologies are developed through the concepts and methods of stochastic model building (including time-series analysis), game theory, decision theory, and filtering/prediction for linear dynamic systems. The methodology is based on the relationship between the robustness of a class of time-series models and quantization which is applied to the time series as part of the model identification process. This relationship is exploited by utilizing the concept of an equivalence, through invariance of spectra, between the class of Markov-chain models and the class of autoregressive moving average (ARMA) models. This spectral equivalence permits a straightforward implementation of the desirable robust properties of the Markov-chain approximation in a class of models which may be applied in linear-recursive form in a linear Kalman filter/predictor structure. The linear filter/predictor structure is shown to provide asymptotically optimal estimates of states which represent one or more integrations of the Markov-chain state. The development of a new saddle-point theorem for a game based on the Markov-chain model structure gives rise to a technique for determining a worst case Markov-chain process, upon which a robust filter/predictor design if based
Robust dynamical effects in traffic and chaotic maps on trees
Indian Academy of Sciences (India)
Here we study two types of well-defined diffusive dynamics on scale-free trees: traffic of packets as navigated random walks, and chaotic standard maps coupled along the network links. We show that in both cases robust collective dynamic effects appear, which can be measured statistically and related to non-ergodicity of ...
The structural dynamics of social class.
Kraus, Michael W; Park, Jun Won
2017-12-01
Individual agency accounts of social class persist in society and even in psychological science despite clear evidence for the role of social structures. This article argues that social class is defined by the structural dynamics of society. Specifically, access to powerful networks, groups, and institutions, and inequalities in wealth and other economic resources shape proximal social environments that influence how individuals express their internal states and motivations. An account of social class that highlights the means by which structures shape and are shaped by individuals guides our understanding of how people move up or down in the social class hierarchy, and provides a framework for interpreting neuroscience studies, experimental paradigms, and approaches that attempt to intervene on social class disparities. Copyright © 2017 Elsevier Ltd. All rights reserved.
Nonlinear Dynamics in Gene Regulation Promote Robustness and Evolvability of Gene Expression Levels.
Steinacher, Arno; Bates, Declan G; Akman, Ozgur E; Soyer, Orkun S
2016-01-01
Cellular phenotypes underpinned by regulatory networks need to respond to evolutionary pressures to allow adaptation, but at the same time be robust to perturbations. This creates a conflict in which mutations affecting regulatory networks must both generate variance but also be tolerated at the phenotype level. Here, we perform mathematical analyses and simulations of regulatory networks to better understand the potential trade-off between robustness and evolvability. Examining the phenotypic effects of mutations, we find an inverse correlation between robustness and evolvability that breaks only with nonlinearity in the network dynamics, through the creation of regions presenting sudden changes in phenotype with small changes in genotype. For genotypes embedding low levels of nonlinearity, robustness and evolvability correlate negatively and almost perfectly. By contrast, genotypes embedding nonlinear dynamics allow expression levels to be robust to small perturbations, while generating high diversity (evolvability) under larger perturbations. Thus, nonlinearity breaks the robustness-evolvability trade-off in gene expression levels by allowing disparate responses to different mutations. Using analytical derivations of robustness and system sensitivity, we show that these findings extend to a large class of gene regulatory network architectures and also hold for experimentally observed parameter regimes. Further, the effect of nonlinearity on the robustness-evolvability trade-off is ensured as long as key parameters of the system display specific relations irrespective of their absolute values. We find that within this parameter regime genotypes display low and noisy expression levels. Examining the phenotypic effects of mutations, we find an inverse correlation between robustness and evolvability that breaks only with nonlinearity in the network dynamics. Our results provide a possible solution to the robustness-evolvability trade-off, suggest an explanation for
Nonlinear Dynamics in Gene Regulation Promote Robustness and Evolvability of Gene Expression Levels.
Directory of Open Access Journals (Sweden)
Arno Steinacher
Full Text Available Cellular phenotypes underpinned by regulatory networks need to respond to evolutionary pressures to allow adaptation, but at the same time be robust to perturbations. This creates a conflict in which mutations affecting regulatory networks must both generate variance but also be tolerated at the phenotype level. Here, we perform mathematical analyses and simulations of regulatory networks to better understand the potential trade-off between robustness and evolvability. Examining the phenotypic effects of mutations, we find an inverse correlation between robustness and evolvability that breaks only with nonlinearity in the network dynamics, through the creation of regions presenting sudden changes in phenotype with small changes in genotype. For genotypes embedding low levels of nonlinearity, robustness and evolvability correlate negatively and almost perfectly. By contrast, genotypes embedding nonlinear dynamics allow expression levels to be robust to small perturbations, while generating high diversity (evolvability under larger perturbations. Thus, nonlinearity breaks the robustness-evolvability trade-off in gene expression levels by allowing disparate responses to different mutations. Using analytical derivations of robustness and system sensitivity, we show that these findings extend to a large class of gene regulatory network architectures and also hold for experimentally observed parameter regimes. Further, the effect of nonlinearity on the robustness-evolvability trade-off is ensured as long as key parameters of the system display specific relations irrespective of their absolute values. We find that within this parameter regime genotypes display low and noisy expression levels. Examining the phenotypic effects of mutations, we find an inverse correlation between robustness and evolvability that breaks only with nonlinearity in the network dynamics. Our results provide a possible solution to the robustness-evolvability trade-off, suggest
Effect of robust torus on the dynamical transport
International Nuclear Information System (INIS)
Martins, C G L; Carvalho, R Egydio de; Caldas, I L; Roberto, M
2010-01-01
In the present work, we quantify the fraction of trajectories that reach a specific region of the phase space when we vary a control parameter using two symplectic maps: one non-twist and another one twist. The two maps were studied with and without a robust torus. We compare the obtained patterns and we identify the effect of the robust torus on the dynamical transport. We show that the effect of meandering-like barriers loses importance in blocking the radial transport when the robust torus is present.
Superlinearly scalable noise robustness of redundant coupled dynamical systems.
Kohar, Vivek; Kia, Behnam; Lindner, John F; Ditto, William L
2016-03-01
We illustrate through theory and numerical simulations that redundant coupled dynamical systems can be extremely robust against local noise in comparison to uncoupled dynamical systems evolving in the same noisy environment. Previous studies have shown that the noise robustness of redundant coupled dynamical systems is linearly scalable and deviations due to noise can be minimized by increasing the number of coupled units. Here, we demonstrate that the noise robustness can actually be scaled superlinearly if some conditions are met and very high noise robustness can be realized with very few coupled units. We discuss these conditions and show that this superlinear scalability depends on the nonlinearity of the individual dynamical units. The phenomenon is demonstrated in discrete as well as continuous dynamical systems. This superlinear scalability not only provides us an opportunity to exploit the nonlinearity of physical systems without being bogged down by noise but may also help us in understanding the functional role of coupled redundancy found in many biological systems. Moreover, engineers can exploit superlinear noise suppression by starting a coupled system near (not necessarily at) the appropriate initial condition.
Robust input design for nonlinear dynamic modeling of AUV.
Nouri, Nowrouz Mohammad; Valadi, Mehrdad
2017-09-01
Input design has a dominant role in developing the dynamic model of autonomous underwater vehicles (AUVs) through system identification. Optimal input design is the process of generating informative inputs that can be used to generate the good quality dynamic model of AUVs. In a problem with optimal input design, the desired input signal depends on the unknown system which is intended to be identified. In this paper, the input design approach which is robust to uncertainties in model parameters is used. The Bayesian robust design strategy is applied to design input signals for dynamic modeling of AUVs. The employed approach can design multiple inputs and apply constraints on an AUV system's inputs and outputs. Particle swarm optimization (PSO) is employed to solve the constraint robust optimization problem. The presented algorithm is used for designing the input signals for an AUV, and the estimate obtained by robust input design is compared with that of the optimal input design. According to the results, proposed input design can satisfy both robustness of constraints and optimality. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.
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. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.
Robustness analysis of uncertain dynamical neural networks with multiple time delays.
Senan, Sibel
2015-10-01
This paper studies the problem of global robust asymptotic stability of the equilibrium point for the class of dynamical neural networks with multiple time delays with respect to the class of slope-bounded activation functions and in the presence of the uncertainties of system parameters of the considered neural network model. By using an appropriate Lyapunov functional and exploiting the properties of the homeomorphism mapping theorem, we derive a new sufficient condition for the existence, uniqueness and global robust asymptotic stability of the equilibrium point for the class of neural networks with multiple time delays. The obtained stability condition basically relies on testing some relationships imposed on the interconnection matrices of the neural system, which can be easily verified by using some certain properties of matrices. An instructive numerical example is also given to illustrate the applicability of our result and show the advantages of this new condition over the previously reported corresponding results. Copyright © 2015 Elsevier Ltd. All rights reserved.
Robust Control Design for Uncertain Nonlinear Dynamic Systems
Kenny, Sean P.; Crespo, Luis G.; Andrews, Lindsey; Giesy, Daniel P.
2012-01-01
Robustness to parametric uncertainty is fundamental to successful control system design and as such it has been at the core of many design methods developed over the decades. Despite its prominence, most of the work on robust control design has focused on linear models and uncertainties that are non-probabilistic in nature. Recently, researchers have acknowledged this disparity and have been developing theory to address a broader class of uncertainties. This paper presents an experimental application of robust control design for a hybrid class of probabilistic and non-probabilistic parametric uncertainties. The experimental apparatus is based upon the classic inverted pendulum on a cart. The physical uncertainty is realized by a known additional lumped mass at an unknown location on the pendulum. This unknown location has the effect of substantially altering the nominal frequency and controllability of the nonlinear system, and in the limit has the capability to make the system neutrally stable and uncontrollable. Another uncertainty to be considered is a direct current motor parameter. The control design objective is to design a controller that satisfies stability, tracking error, control power, and transient behavior requirements for the largest range of parametric uncertainties. This paper presents an overview of the theory behind the robust control design methodology and the experimental results.
A class of convergent neural network dynamics
Fiedler, Bernold; Gedeon, Tomáš
1998-01-01
We consider a class of systems of differential equations in Rn which exhibits convergent dynamics. We find a Lyapunov function and show that every bounded trajectory converges to the set of equilibria. Our result generalizes the results of Cohen and Grossberg (1983) for convergent neural networks. It replaces the symmetry assumption on the matrix of weights by the assumption on the structure of the connections in the neural network. We prove the convergence result also for a large class of Lotka-Volterra systems. These are naturally defined on the closed positive orthant. We show that there are no heteroclinic cycles on the boundary of the positive orthant for the systems in this class.
Robust adaptive fuzzy neural tracking control for a class of unknown ...
Indian Academy of Sciences (India)
In this paper, an adaptive fuzzy neural controller (AFNC) for a class of unknown chaotic systems is proposed. The proposed AFNC is comprised of a fuzzy neural controller and a robust controller. The fuzzy neural controller including a fuzzy neural network identiﬁer (FNNI) is the principal controller. The FNNI is used for ...
Robustness of pinning a general complex dynamical network
International Nuclear Information System (INIS)
Wang Lei; Sun Youxian
2010-01-01
This Letter studies the robustness problem of pinning a general complex dynamical network toward an assigned synchronous evolution. Several synchronization criteria are presented to guarantee the convergence of the pinning process locally and globally by construction of Lyapunov functions. In particular, if a pinning strategy has been designed for synchronization of a given complex dynamical network, then no matter what uncertainties occur among the pinned nodes, synchronization can still be guaranteed through the pinning. The analytical results show that pinning control has a certain robustness against perturbations on network architecture: adding, deleting and changing the weights of edges. Numerical simulations illustrated by scale-free complex networks verify the theoretical results above-acquired.
Robust uniform persistence in discrete and continuous dynamical systems using Lyapunov exponents.
Salceanu, Paul L
2011-07-01
This paper extends the work of Salceanu and Smith [12, 13] where Lyapunov exponents were used to obtain conditions for uniform persistence ina class of dissipative discrete-time dynamical systems on the positive orthant of R(m), generated by maps. Here a united approach is taken, for both discrete and continuous time, and the dissipativity assumption is relaxed. Sufficient conditions are given for compact subsets of an invariant part of the boundary of R(m+) to be robust uniform weak repellers. These conditions require Lyapunov exponents be positive on such sets. It is shown how this leads to robust uniform persistence. The results apply to the investigation of robust uniform persistence of the disease in host populations, as shown in an application.
Robust control of a class of chaotic and hyperchaotic driven systems
Indian Academy of Sciences (India)
2016-12-05
Dec 5, 2016 ... are recently devoted to generate chaos and hyper- chaos dynamics by proposing new PWL systems [6,7]. However, very few results are published on chaos synchronization for such complex systems [8–10]. Over the past ten years, robust chaos synchroniza- tion via state feedback control has been widely ...
Directory of Open Access Journals (Sweden)
Bingyong Yan
2015-01-01
Full Text Available A robust fault detection scheme for a class of nonlinear systems with uncertainty is proposed. The proposed approach utilizes robust control theory and parameter optimization algorithm to design the gain matrix of fault tracking approximator (FTA for fault detection. The gain matrix of FTA is designed to minimize the effects of system uncertainty on residual signals while maximizing the effects of system faults on residual signals. The design of the gain matrix of FTA takes into account the robustness of residual signals to system uncertainty and sensitivity of residual signals to system faults simultaneously, which leads to a multiobjective optimization problem. Then, the detectability of system faults is rigorously analyzed by investigating the threshold of residual signals. Finally, simulation results are provided to show the validity and applicability of the proposed approach.
Doubly Robust Estimation of Optimal Dynamic Treatment Regimes
DEFF Research Database (Denmark)
Barrett, Jessica K; Henderson, Robin; Rosthøj, Susanne
2014-01-01
We compare methods for estimating optimal dynamic decision rules from observational data, with particular focus on estimating the regret functions defined by Murphy (in J. R. Stat. Soc., Ser. B, Stat. Methodol. 65:331-355, 2003). We formulate a doubly robust version of the regret-regression appro......We compare methods for estimating optimal dynamic decision rules from observational data, with particular focus on estimating the regret functions defined by Murphy (in J. R. Stat. Soc., Ser. B, Stat. Methodol. 65:331-355, 2003). We formulate a doubly robust version of the regret......-regression approach of Almirall et al. (in Biometrics 66:131-139, 2010) and Henderson et al. (in Biometrics 66:1192-1201, 2010) and demonstrate that it is equivalent to a reduced form of Robins' efficient g-estimation procedure (Robins, in Proceedings of the Second Symposium on Biostatistics. Springer, New York, pp....... 189-326, 2004). Simulation studies suggest that while the regret-regression approach is most efficient when there is no model misspecification, in the presence of misspecification the efficient g-estimation procedure is more robust. The g-estimation method can be difficult to apply in complex...
Robust dynamical decoupling for quantum computing and quantum memory.
Souza, Alexandre M; Alvarez, Gonzalo A; Suter, Dieter
2011-06-17
Dynamical decoupling (DD) is a popular technique for protecting qubits from the environment. However, unless special care is taken, experimental errors in the control pulses used in this technique can destroy the quantum information instead of preserving it. Here, we investigate techniques for making DD sequences robust against different types of experimental errors while retaining good decoupling efficiency in a fluctuating environment. We present experimental data from solid-state nuclear spin qubits and introduce a new DD sequence that is suitable for quantum computing and quantum memory.
Uncertain Dynamics, Correlation Effects, and Robust Investment Decisions
DEFF Research Database (Denmark)
Flor, Christian Riis; Hesel, Søren
2015-01-01
We analyze a firm's investment problem when the dynamics of project value and investment cost are uncertain. We provide an explicit solution using a robust method for an ambiguity averse firm taking this into account. Ambiguity aversion regarding a common risk factor impacts differently than...... ambiguity aversion regarding investment cost residual risk. Correlation between project value and investment cost matters; ambiguity aversion regarding common risk can decrease the investment probability only if correlation is positive. Ambiguity aversion regarding residual risk always increases...... the investment probability. When only project value is risky, volatility can monotonically decrease the investment threshold; this does not hold with the multiple prior method....
Robustness and Vulnerability of Networks with Dynamical Dependency Groups.
Bai, Ya-Nan; Huang, Ning; Wang, Lei; Wu, Zhi-Xi
2016-11-28
The dependency property and self-recovery of failure nodes both have great effects on the robustness of networks during the cascading process. Existing investigations focused mainly on the failure mechanism of static dependency groups without considering the time-dependency of interdependent nodes and the recovery mechanism in reality. In this study, we present an evolving network model consisting of failure mechanisms and a recovery mechanism to explore network robustness, where the dependency relations among nodes vary over time. Based on generating function techniques, we provide an analytical framework for random networks with arbitrary degree distribution. In particular, we theoretically find that an abrupt percolation transition exists corresponding to the dynamical dependency groups for a wide range of topologies after initial random removal. Moreover, when the abrupt transition point is above the failure threshold of dependency groups, the evolving network with the larger dependency groups is more vulnerable; when below it, the larger dependency groups make the network more robust. Numerical simulations employing the Erdős-Rényi network and Barabási-Albert scale free network are performed to validate our theoretical results.
Robust fault-sensitive synchronization of a class of nonlinear systems
International Nuclear Information System (INIS)
Xu Shi-Yun; Tang Yong; Sun Hua-Dong; Yang Ying; Liu Xian
2011-01-01
Aiming at enhancing the quality as well as the reliability of synchronization, this paper is concerned with the fault detection issue within the synchronization process for a class of nonlinear systems in the existence of external disturbances. To handle such problems, the concept of robust fault-sensitive (RFS) synchronization is proposed, and a method of determining such a kind of synchronization is developed. Under the framework of RFS synchronization, the master and the slave systems are robustly synchronized, and at the same time, sensitive to possible faults based on a mixed H − /H ∞ performance. The design of desired output feedback controller is realized by solving a linear matrix inequality, and the fault sensitivity H − index can be optimized via a convex optimization algorithm. A master-slave configuration composed of identical Chua's circuits is adopted as a numerical example to demonstrate the effectiveness and applicability of the analytical results. (general)
Robust FDI for a Class of Nonlinear Networked Systems with ROQs
Directory of Open Access Journals (Sweden)
An-quan Sun
2014-01-01
Full Text Available This paper considers the robust fault detection and isolation (FDI problem for a class of nonlinear networked systems (NSs with randomly occurring quantisations (ROQs. After vector augmentation, Lyapunov function is introduced to ensure the asymptotically mean-square stability of fault detection system. By transforming the quantisation effects into sector-bounded parameter uncertainties, sufficient conditions ensuring the existence of fault detection filter are proposed, which can reduce the difference between output residuals and fault signals as small as possible under H∞ framework. Finally, an example linearized from a vehicle system is introduced to show the efficiency of the proposed fault detection filter.
Robust exponential stability and domains of attraction in a class of interval neural networks
International Nuclear Information System (INIS)
Yang Xiaofan; Liao Xiaofeng; Bai Sen; Evans, David J
2005-01-01
This paper addresses robust exponential stability as well as domains of attraction in a class of interval neural networks. A sufficient condition for an equilibrium point to be exponentially stable is established. And an estimate on the domains of attraction of exponentially stable equilibrium points is presented. Both the condition and the estimate are formulated in terms of the parameter intervals, the neurons' activation functions and the equilibrium point. Hence, they are easily checkable. In addition, our results neither depend on monotonicity of the activation functions nor on coupling conditions between the neurons. Consequently, these results are of practical importance in evaluating the performance of interval associative memory networks
DEFF Research Database (Denmark)
2017-01-01
‘Robust – Reflections on Resilient Architecture’, is a scientific publication following the conference of the same name in November of 2017. Researches and PhD-Fellows, associated with the Masters programme: Cultural Heritage, Transformation and Restoration (Transformation), at The Royal Danish...
Robust Dynamics and Control of a Partially Observed Markov Chain
International Nuclear Information System (INIS)
Elliott, R. J.; Malcolm, W. P.; Moore, J. P.
2007-01-01
In a seminal paper, Martin Clark (Communications Systems and Random Process Theory, Darlington, 1977, pp. 721-734, 1978) showed how the filtered dynamics giving the optimal estimate of a Markov chain observed in Gaussian noise can be expressed using an ordinary differential equation. These results offer substantial benefits in filtering and in control, often simplifying the analysis and an in some settings providing numerical benefits, see, for example Malcolm et al. (J. Appl. Math. Stoch. Anal., 2007, to appear).Clark's method uses a gauge transformation and, in effect, solves the Wonham-Zakai equation using variation of constants. In this article, we consider the optimal control of a partially observed Markov chain. This problem is discussed in Elliott et al. (Hidden Markov Models Estimation and Control, Applications of Mathematics Series, vol. 29, 1995). The innovation in our results is that the robust dynamics of Clark are used to compute forward in time dynamics for a simplified adjoint process. A stochastic minimum principle is established
Unsteady Sail Dynamics in Olympic Class Sailboats
Williamson, Charles; Schutt, Riley
2016-11-01
Unsteady sailing techniques have evolved in competitive sailboat fleets, in cases where the relative weight of the sailor is sufficient to impart unsteady motions to the boat and sails. We will discuss three types of motion that are used by athletes to propel their boats on an Olympic race course faster than using the wind alone. In all of our cases, body weight movements induce unsteady sail motion, increasing driving force and speed through the water. In this research, we explore the dynamics of an Olympic class Laser sailboat equipped with a GPS, IMU, wind sensor, and a 6-GoPro camera array. We shall briefly discuss "sail flicking", whereby the helmsman periodically rolls the sail into the apparent wind, at an angle which is distinct from classical heave (in our case, the oscillations are not normal to the apparent flow). We also demonstrate "roll tacking", where there are considerable advantages to rolling the boat during such a maneuver, especially in light wind. In both of the above examples from on-the-water studies, corresponding experiments using a towing tank exhibit increases in the driving force, associated with the formation of strong vortex pairs into the flow. Finally, we focus on a technique known as "S-curving" in the case where the boat sails downwind. In contrast to the previous cases, it is drag force rather than lift force that the sailor is trying to maximise as the boat follows a zig-zag trajectory. The augmented apparent wind strength due to the oscillatory sail motion, and the growth of strong synchronised low-pressure wake vortices on the low-pressure side of the sail, contribute to the increase in driving force, and velocity-made-good downwind.
Robust Fault Tolerant Control for a Class of Time-Delay Systems with Multiple Disturbances
Directory of Open Access Journals (Sweden)
Songyin Cao
2013-01-01
Full Text Available A robust fault tolerant control (FTC approach is addressed for a class of nonlinear systems with time delay, actuator faults, and multiple disturbances. The first part of the multiple disturbances is supposed to be an uncertain modeled disturbance and the second one represents a norm-bounded variable. First, a composite observer is designed to estimate the uncertain modeled disturbance and actuator fault simultaneously. Then, an FTC strategy consisting of disturbance observer based control (DOBC, fault accommodation, and a mixed H2/H∞ controller is constructed to reconfigure the considered systems with disturbance rejection and attenuation performance. Finally, simulations for a flight control system are given to show the efficiency of the proposed approach.
Step Detection Robust against the Dynamics of Smartphones
Lee, Hwan-hee; Choi, Suji; Lee, Myeong-jin
2015-01-01
A novel algorithm is proposed for robust step detection irrespective of step mode and device pose in smartphone usage environments. The dynamics of smartphones are decoupled into a peak-valley relationship with adaptive magnitude and temporal thresholds. For extracted peaks and valleys in the magnitude of acceleration, a step is defined as consisting of a peak and its adjacent valley. Adaptive magnitude thresholds consisting of step average and step deviation are applied to suppress pseudo peaks or valleys that mostly occur during the transition among step modes or device poses. Adaptive temporal thresholds are applied to time intervals between peaks or valleys to consider the time-varying pace of human walking or running for the correct selection of peaks or valleys. From the experimental results, it can be seen that the proposed step detection algorithm shows more than 98.6% average accuracy for any combination of step mode and device pose and outperforms state-of-the-art algorithms. PMID:26516857
Maleszewski, Joseph; Lu, Jie; Fox-Talbot, Karen; Halushka, Marc K
2007-06-01
Despite the common use of immunohistochemistry in autopsy tissues, the stability of most proteins over extended time periods is unknown. The robustness of signal for 16 proteins (MMP1, MMP2, MMP3, MMP9, TIMP1, TIMP2, TIMP3, AGER, MSR, SCARB1, OLR1, CD36, LTF, LGALS3, LYZ, and DDOST) and two measures of advanced glycation end products (AGE, CML) was evaluated. Two formalin-fixed, paraffin-embedded human tissue arrays containing 16 tissues each were created to evaluate 48 hr of autolysis in a warm or cold environment. For these classes of proteins, matrix metalloproteinases and their inhibitors, scavenger receptors, and advanced glycation end product receptors, we saw no systematic diminution of signal intensity during a period of 24 hr. Analysis was performed by two independent observers and confirmed for a subset of proteins by digital analysis and Western blotting. We conclude that these classes of proteins degrade slowly and faithfully maintain their immunohistochemistry characteristics over at least a 24-hr time interval in devitalized tissues. This study supports the use of autopsy tissues with short postmortem intervals for immunohistochemical studies for diseases such as diabetic vascular disease, cancer, Alzheimer's disease, atherosclerosis, and other pathological states. This manuscript contains online supplemental material at http://www.jhc.org. Please visit this article online to view these materials.
Word class and context affect alpha-band oscillatory dynamics in an older population
Directory of Open Access Journals (Sweden)
Monika eMellem
2012-04-01
Full Text Available Differences in the oscillatory EEG dynamics of reading open class and closed class words have previously been found (Bastiaansen et al., 2005 and are thought to reflect differences in lexical-semantic content between these word classes. In particular, the theta band (4–7 Hz seems to play a prominent role in lexical-semantic retrieval. We tested whether this theta effect is robust in an older population of subjects. Additionally, we examined how the context of a word can modulate the oscillatory dynamics underlying retrieval for the two different classes of words. Older participants (mean age 55 read words presented in either syntactically-correct sentences or in a scrambled order (scrambled sentence while their EEG was recorded. We performed time-frequency analysis to examine how power varied based on the context or class of the word. We observed larger power decreases in the alpha (8–12Hz band between 200–700 ms for the open class compared to closed class words, but this was true only for the scrambled sentence context. We did not observe differences in theta power between these conditions. Context exerted an effect on the alpha and low beta (13–18 Hz bands between 0–700 ms. These results suggest that the previously observed word class effects on theta power changes in a younger participant sample do not seem to be a robust effect in this older population. Though this is an indirect comparison between studies, it may suggest the existence of aging effects on word retrieval dynamics for different populations. Additionally, the interaction between word class and context suggests that word retrieval mechanisms interact with sentence-level comprehension mechanisms in the alpha band.
Optimizing Dynamic Class Composition in a Statically Typed Language
DEFF Research Database (Denmark)
Nielsen, Anders Bach; Ernst, Erik
2008-01-01
-enable a type safe treatment of classifiers and their associated types and instances, even in the case where classifiers are created dynamically. This opens the opportunity to make dynamic class computations available as an integrated part of the language semantics. The language gbeta is an example where...... this is achieved based on mixins and linearization. In this paper we focus on the virtual machine related challenges of supporting dynamic class composition. In particular we present some core algorithms used for creating new classes, as well as some performance enhancements in these algorithms....
Class of reconstructed discontinuous Galerkin methods in computational fluid dynamics
International Nuclear Information System (INIS)
Luo, Hong; Xia, Yidong; Nourgaliev, Robert
2011-01-01
A class of reconstructed discontinuous Galerkin (DG) methods is presented to solve compressible flow problems on arbitrary grids. The idea is to combine the efficiency of the reconstruction methods in finite volume methods and the accuracy of the DG methods to obtain a better numerical algorithm in computational fluid dynamics. The beauty of the resulting reconstructed discontinuous Galerkin (RDG) methods is that they provide a unified formulation for both finite volume and DG methods, and contain both classical finite volume and standard DG methods as two special cases of the RDG methods, and thus allow for a direct efficiency comparison. Both Green-Gauss and least-squares reconstruction methods and a least-squares recovery method are presented to obtain a quadratic polynomial representation of the underlying linear discontinuous Galerkin solution on each cell via a so-called in-cell reconstruction process. The devised in-cell reconstruction is aimed to augment the accuracy of the discontinuous Galerkin method by increasing the order of the underlying polynomial solution. These three reconstructed discontinuous Galerkin methods are used to compute a variety of compressible flow problems on arbitrary meshes to assess their accuracy. The numerical experiments demonstrate that all three reconstructed discontinuous Galerkin methods can significantly improve the accuracy of the underlying second-order DG method, although the least-squares reconstructed DG method provides the best performance in terms of both accuracy, efficiency, and robustness. (author)
Runtime Support for Type-Safe Dynamic Java Classes
National Research Council Canada - National Science Library
Malabarba, Scott; Pandey, Raju; Gragg, Jeff; Barr, Earl; Barnes, J. F
2000-01-01
.... In this paper we present an approach for supporting dynamic evolution of Java programs. In this approach, Java programs can evolve by changing their components, namely classes, during their execution...
Barnett, William A.; Duzhak, Evgeniya Aleksandrovna
2008-06-01
Grandmont [J.M. Grandmont, On endogenous competitive business cycles, Econometrica 53 (1985) 995-1045] found that the parameter space of the most classical dynamic models is stratified into an infinite number of subsets supporting an infinite number of different kinds of dynamics, from monotonic stability at one extreme to chaos at the other extreme, and with many forms of multiperiodic dynamics in between. The econometric implications of Grandmont’s findings are particularly important, if bifurcation boundaries cross the confidence regions surrounding parameter estimates in policy-relevant models. Stratification of a confidence region into bifurcated subsets seriously damages robustness of dynamical inferences. Recently, interest in policy in some circles has moved to New-Keynesian models. As a result, in this paper we explore bifurcation within the class of New-Keynesian models. We develop the econometric theory needed to locate bifurcation boundaries in log-linearized New-Keynesian models with Taylor policy rules or inflation-targeting policy rules. Central results needed in this research are our theorems on the existence and location of Hopf bifurcation boundaries in each of the cases that we consider.
Vilas, Carlos; Balsa-Canto, Eva; García, Maria-Sonia G; Banga, Julio R; Alonso, Antonio A
2012-07-02
Systems biology allows the analysis of biological systems behavior under different conditions through in silico experimentation. The possibility of perturbing biological systems in different manners calls for the design of perturbations to achieve particular goals. Examples would include, the design of a chemical stimulation to maximize the amplitude of a given cellular signal or to achieve a desired pattern in pattern formation systems, etc. Such design problems can be mathematically formulated as dynamic optimization problems which are particularly challenging when the system is described by partial differential equations.This work addresses the numerical solution of such dynamic optimization problems for spatially distributed biological systems. The usual nonlinear and large scale nature of the mathematical models related to this class of systems and the presence of constraints on the optimization problems, impose a number of difficulties, such as the presence of suboptimal solutions, which call for robust and efficient numerical techniques. Here, the use of a control vector parameterization approach combined with efficient and robust hybrid global optimization methods and a reduced order model methodology is proposed. The capabilities of this strategy are illustrated considering the solution of a two challenging problems: bacterial chemotaxis and the FitzHugh-Nagumo model. In the process of chemotaxis the objective was to efficiently compute the time-varying optimal concentration of chemotractant in one of the spatial boundaries in order to achieve predefined cell distribution profiles. Results are in agreement with those previously published in the literature. The FitzHugh-Nagumo problem is also efficiently solved and it illustrates very well how dynamic optimization may be used to force a system to evolve from an undesired to a desired pattern with a reduced number of actuators. The presented methodology can be used for the efficient dynamic optimization of
Energy Technology Data Exchange (ETDEWEB)
Weerakkody, Sean [Carnegie Mellon Univ., Pittsburgh, PA (United States); Liu, Xiaofei [Carnegie Mellon Univ., Pittsburgh, PA (United States); Sinopoli, Bruno [Carnegie Mellon Univ., Pittsburgh, PA (United States)
2017-12-12
We consider the design and analysis of robust distributed control systems (DCSs) to ensure the detection of integrity attacks. DCSs are often managed by independent agents and are implemented using a diverse set of sensors and controllers. However, the heterogeneous nature of DCSs along with their scale leave such systems vulnerable to adversarial behavior. To mitigate this reality, we provide tools that allow operators to prevent zero dynamics attacks when as many as p agents and sensors are corrupted. Such a design ensures attack detectability in deterministic systems while removing the threat of a class of stealthy attacks in stochastic systems. To achieve this goal, we use graph theory to obtain necessary and sufficient conditions for the presence of zero dynamics attacks in terms of the structural interactions between agents and sensors. We then formulate and solve optimization problems which minimize communication networks while also ensuring a resource limited adversary cannot perform a zero dynamics attacks. Polynomial time algorithms for design and analysis are provided.
Dynamical Scheduling and Robust Control in Uncertain Environments with Petri Nets for DESs
Directory of Open Access Journals (Sweden)
Dimitri Lefebvre
2017-10-01
Full Text Available This paper is about the incremental computation of control sequences for discrete event systems in uncertain environments where uncontrollable events may occur. Timed Petri nets are used for this purpose. The aim is to drive the marking of the net from an initial value to a reference one, in minimal or near-minimal time, by avoiding forbidden markings, deadlocks, and dead branches. The approach is similar to model predictive control with a finite set of control actions. At each step only a small area of the reachability graph is explored: this leads to a reasonable computational complexity. The robustness of the resulting trajectory is also evaluated according to a risk probability. A sufficient condition is provided to compute robust trajectories. The proposed results are applicable to a large class of discrete event systems, in particular in the domains of flexible manufacturing. However, they are also applicable to other domains as communication, computer science, transportation, and traffic as long as the considered systems admit Petri Nets (PNs models. They are suitable for dynamical deadlock-free scheduling and reconfiguration problems in uncertain environments.
Energy Technology Data Exchange (ETDEWEB)
Melintescu, A.; Galeriu, D. [' Horia Hulubei' National Institute for Physics and Nuclear Engineering, Bucharest-Magurele (Romania); Diabate, S.; Strack, S. [Institute of Toxicology and Genetics, Karlsruhe Institute of Technology - KIT, Eggenstein-Leopoldshafen (Germany)
2015-03-15
The processes involved in tritium transfer in crops are complex and regulated by many feedback mechanisms. A full mechanistic model is difficult to develop due to the complexity of the processes involved in tritium transfer and environmental conditions. First, a review of existing models (ORYZA2000, CROPTRIT and WOFOST) presenting their features and limits, is made. Secondly, the preparatory steps for a robust model are discussed, considering the role of dry matter and photosynthesis contribution to the OBT (Organically Bound Tritium) dynamics in crops.
Robust Estimation and Moment Selection in Dynamic Fixed-effects Panel Data Models
Cizek, P.; Aquaro, M.
2015-01-01
This paper extends an existing outlier-robust estimator of linear dynamic panel data models with fixed effects, which is based on the median ratio of two consecutive pairs of first-differenced data. To improve its precision and robust properties, a general procedure based on many pairwise
Dynamical class of a two-dimensional plasmonic Dirac system.
Silva, Érica de Mello
2015-10-01
A current goal in plasmonic science and technology is to figure out how to manage the relaxational dynamics of surface plasmons in graphene since its damping constitutes a hinder for the realization of graphene-based plasmonic devices. In this sense we believe it might be of interest to enlarge the knowledge on the dynamical class of two-dimensional plasmonic Dirac systems. According to the recurrence relations method, different systems are said to be dynamically equivalent if they have identical relaxation functions at all times, and such commonality may lead to deep connections between seemingly unrelated physical systems. We employ the recurrence relations approach to obtain relaxation and memory functions of density fluctuations and show that a two-dimensional plasmonic Dirac system at long wavelength and zero temperature belongs to the same dynamical class of standard two-dimensional electron gas and classical harmonic oscillator chain with an impurity mass.
A Robust FLOM Based Spectrum Sensing Scheme under Middleton Class A Noise in IoT
Directory of Open Access Journals (Sweden)
Enwei Xu
2017-01-01
Full Text Available Accessibility to remote users in dynamic environment, high spectrum utilization, and no spectrum purchase make Cognitive Radio (CR a feasible solution of wireless communications in the Internet of Things (IoT. Reliable spectrum sensing becomes the prerequisite for the establishment of communication between IoT-capable objects. Considering the application environment, spectrum sensing not only has to cope with man-made impulsive noises but also needs to overcome noise fluctuations. In this paper, we study the Fractional Lower Order Moments (FLOM based spectrum sensing method under Middleton Class A noise and incorporate a Noise Power Estimation (NPE module into the sensing system to deal with the issue of noise uncertainty. Moreover, the NPE process does not need noise-only samples. The analytical expressions of the probabilities of detection and the probability of false alarm are derived. The impact on sensing performance of the parameters of the NPE module is also analyzed. The theoretical analysis and simulation results show that our proposed sensing method achieves a satisfactory performance at low SNR.
Collective modes in multiband superfluids and superconductors: Multiple dynamical classes
International Nuclear Information System (INIS)
Ota, Yukihiro; Machida, Masahiko; Koyama, Tomio; Aoki, Hideo
2011-01-01
One important way to characterize the states having a gauge symmetry spontaneously broken over multibands is to look at their collective excitation modes. We find that a three-band system has multiple Leggett modes with significantly different masses, which can be classified into different dynamical classes according to whether multiple interband Josephson currents add or cancel. This provides a way to dynamically characterize multiband superconductivity while the pairing symmetry is a static property.
Fuzzy Counter Propagation Neural Network Control for a Class of Nonlinear Dynamical Systems.
Sakhre, Vandana; Jain, Sanjeev; Sapkal, Vilas S; Agarwal, Dev P
2015-01-01
Fuzzy Counter Propagation Neural Network (FCPN) controller design is developed, for a class of nonlinear dynamical systems. In this process, the weight connecting between the instar and outstar, that is, input-hidden and hidden-output layer, respectively, is adjusted by using Fuzzy Competitive Learning (FCL). FCL paradigm adopts the principle of learning, which is used to calculate Best Matched Node (BMN) which is proposed. This strategy offers a robust control of nonlinear dynamical systems. FCPN is compared with the existing network like Dynamic Network (DN) and Back Propagation Network (BPN) on the basis of Mean Absolute Error (MAE), Mean Square Error (MSE), Best Fit Rate (BFR), and so forth. It envisages that the proposed FCPN gives better results than DN and BPN. The effectiveness of the proposed FCPN algorithms is demonstrated through simulations of four nonlinear dynamical systems and multiple input and single output (MISO) and a single input and single output (SISO) gas furnace Box-Jenkins time series data.
Optimal interdependence enhances the dynamical robustness of complex systems
Singh, Rishu Kumar; Sinha, Sitabhra
2017-08-01
Although interdependent systems have usually been associated with increased fragility, we show that strengthening the interdependence between dynamical processes on different networks can make them more likely to survive over long times. By coupling the dynamics of networks that in isolation exhibit catastrophic collapse with extinction of nodal activity, we demonstrate system-wide persistence of activity for an optimal range of interdependence between the networks. This is related to the appearance of attractors of the global dynamics comprising disjoint sets ("islands") of stable activity.
A New Class of Particle Filters for Random Dynamic Systems with Unknown Statistics
Directory of Open Access Journals (Sweden)
Joaquín Míguez
2004-11-01
Full Text Available In recent years, particle filtering has become a powerful tool for tracking signals and time-varying parameters of random dynamic systems. These methods require a mathematical representation of the dynamics of the system evolution, together with assumptions of probabilistic models. In this paper, we present a new class of particle filtering methods that do not assume explicit mathematical forms of the probability distributions of the noise in the system. As a consequence, the proposed techniques are simpler, more robust, and more flexible than standard particle filters. Apart from the theoretical development of specific methods in the new class, we provide computer simulation results that demonstrate the performance of the algorithms in the problem of autonomous positioning of a vehicle in a 2-dimensional space.
Dynamic Written Corrective Feedback in Developmental Multilingual Writing Classes
Kurzer, Kendon
2018-01-01
This study investigated the role of dynamic written corrective feedback (DWCF; Evans, Hartshorn, McCollum, & Wolfersberger, 2010; Hartshorn & Evans, 2015; Hartshorn et al., 2010), a mode of providing specific, targeted, and individualized grammar feedback in developmental English as a second language (ESL) writing classes (pre-first year…
Li, Zhaoying; Zhou, Wenjie; Liu, Hao
2016-09-01
This paper addresses the nonlinear robust tracking controller design problem for hypersonic vehicles. This problem is challenging due to strong coupling between the aerodynamics and the propulsion system, and the uncertainties involved in the vehicle dynamics including parametric uncertainties, unmodeled model uncertainties, and external disturbances. By utilizing the feedback linearization technique, a linear tracking error system is established with prescribed references. For the linear model, a robust controller is proposed based on the signal compensation theory to guarantee that the tracking error dynamics is robustly stable. Numerical simulation results are given to show the advantages of the proposed nonlinear robust control method, compared to the robust loop-shaping control approach. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.
Robust Throughput Boosting for Low Latency Dynamic Partial Reconfiguration
DEFF Research Database (Denmark)
Nannarelli, Alberto; Re, M.; Cardarilli, Gian Carlo
2017-01-01
Reducing the configuration time of portions of an FPGA at run time is crucial in contemporary FPGA-based accelerators. In this work, we propose a method to increase the throughput for FPGA dynamic partial reconfiguration by using standard IP blocks. The throughput is increased by over-clocking th......Reducing the configuration time of portions of an FPGA at run time is crucial in contemporary FPGA-based accelerators. In this work, we propose a method to increase the throughput for FPGA dynamic partial reconfiguration by using standard IP blocks. The throughput is increased by over...
Robust Design of SAW Gas Sensors by Taguchi Dynamic Method
Directory of Open Access Journals (Sweden)
Hsun-Heng Tsai
2009-02-01
Full Text Available This paper adopts Taguchi’s signal-to-noise ratio analysis to optimize the dynamic characteristics of a SAW gas sensor system whose output response is linearly related to the input signal. The goal of the present dynamic characteristics study is to increase the sensitivity of the measurement system while simultaneously reducing its variability. A time- and cost-efficient finite element analysis method is utilized to investigate the effects of the deposited mass upon the resonant frequency output of the SAW biosensor. The results show that the proposed methodology not only reduces the design cost but also promotes the performance of the sensors.
Robust dynamical effects in traffic and chaotic maps on trees
Indian Academy of Sciences (India)
Discrete-time diffusion processes on complex networks are modeled by a dynam- ... Scale-free tree of N = 1000 nodes used in the simulations. Shown .... defined as the time interval ∆t between two successive events at the same node.
Directory of Open Access Journals (Sweden)
Shehzad Khalid
2014-01-01
Full Text Available We have presented a classification framework that combines multiple heterogeneous classifiers in the presence of class label noise. An extension of m-Mediods based modeling is presented that generates model of various classes whilst identifying and filtering noisy training data. This noise free data is further used to learn model for other classifiers such as GMM and SVM. A weight learning method is then introduced to learn weights on each class for different classifiers to construct an ensemble. For this purpose, we applied genetic algorithm to search for an optimal weight vector on which classifier ensemble is expected to give the best accuracy. The proposed approach is evaluated on variety of real life datasets. It is also compared with existing standard ensemble techniques such as Adaboost, Bagging, and Random Subspace Methods. Experimental results show the superiority of proposed ensemble method as compared to its competitors, especially in the presence of class label noise and imbalance classes.
Robust dynamical pattern formation from a multifunctional minimal genetic circuit
Directory of Open Access Journals (Sweden)
Carrera Javier
2010-04-01
Full Text Available Abstract Background A practical problem during the analysis of natural networks is their complexity, thus the use of synthetic circuits would allow to unveil the natural mechanisms of operation. Autocatalytic gene regulatory networks play an important role in shaping the development of multicellular organisms, whereas oscillatory circuits are used to control gene expression under variable environments such as the light-dark cycle. Results We propose a new mechanism to generate developmental patterns and oscillations using a minimal number of genes. For this, we design a synthetic gene circuit with an antagonistic self-regulation to study the spatio-temporal control of protein expression. Here, we show that our minimal system can behave as a biological clock or memory, and it exhibites an inherent robustness due to a quorum sensing mechanism. We analyze this property by accounting for molecular noise in an heterogeneous population. We also show how the period of the oscillations is tunable by environmental signals, and we study the bifurcations of the system by constructing different phase diagrams. Conclusions As this minimal circuit is based on a single transcriptional unit, it provides a new mechanism based on post-translational interactions to generate targeted spatio-temporal behavior.
Adaptive Fuzzy Robust Control for a Class of Nonlinear Systems via Small Gain Theorem
Directory of Open Access Journals (Sweden)
Xingjian Wang
2013-01-01
Full Text Available Practical nonlinear systems can usually be represented by partly linearizable models with unknown nonlinearities and external disturbances. Based on this consideration, we propose a novel adaptive fuzzy robust control (AFRC algorithm for such systems. The AFRC effectively combines techniques of adaptive control and fuzzy control, and it improves the performance by retaining the advantages of both methods. The linearizable part will be linearly parameterized with unknown but constant parameters, and the discontinuous-projection-based adaptive control law is used to compensate these parts. The Takagi-Sugeno fuzzy logic systems are used to approximate unknown nonlinearities. Robust control law ensures the robustness of closed-loop control system. A systematic design procedure of the AFRC algorithm by combining the backstepping technique and small-gain approach is presented. Then the closed-loop stability is studied by using small gain theorem, and the result indicates that the closed-loop system is semiglobally uniformly ultimately bounded.
Robust function projective synchronization of a class of uncertain chaotic systems
International Nuclear Information System (INIS)
Shen Liqun; Liu Wanyu; Ma Jianwei
2009-01-01
In this paper, the function projective synchronization problem of chaotic systems is investigated, where parameter mismatch exists between the drive system and the response system. Based on Lyapunov stability theory, a novel robust function projective synchronization scheme is proposed. And the parameter mismatch problem is also solved. Simulation results of Lorenz system and Chen system verify the effectiveness of the proposed control scheme.
A robust control strategy for a class of distributed network with transmission delays
DEFF Research Database (Denmark)
Vahid Naghavi, S.; A. Safavi, A.; Khooban, Mohammad Hassan
2016-01-01
Purpose The purpose of this paper is to concern the design of a robust model predictive controller for distributed networked systems with transmission delays. Design/methodology/approach The overall system is composed of a number of interconnected nonlinear subsystems with time-varying transmission...... as an optimization problem of a “worst-case” objective function over an infinite moving horizon. Findings The aim is to propose control synthesis approach that depends on nonlinearity and time varying delay characteristics. The MPC problem is represented in a time varying delayed state feedback structure....... Then the synthesis sufficient condition is provided in the form of a linear matrix inequality (LMI) optimization and is solved online at each time instant. In the rest, an LMI-based decentralized observer-based robust model predictive control strategy is proposed. Originality/value The authors develop RMPC...
PCBDDC: A Class of Robust Dual-Primal Methods in PETSc
Zampini, Stefano
2016-01-01
A class of preconditioners based on balancing domain decomposition by constraints methods is introduced in the Portable, Extensible Toolkit for Scientific Computation (PETSc). The algorithm and the underlying nonoverlapping domain decomposition framework are described with a specific focus on their current implementation in the library. Available user customizations are also presented, together with an experimental interface to the finite element tearing and interconnecting dual-primal methods within PETSc. Large-scale parallel numerical results are provided for the latest version of the code, which is able to tackle symmetric positive definite problems with highly heterogeneous distributions of the coefficients. Current limitations and future extensions of the preconditioner class are also discussed.
PCBDDC: A Class of Robust Dual-Primal Methods in PETSc
Zampini, Stefano
2016-10-27
A class of preconditioners based on balancing domain decomposition by constraints methods is introduced in the Portable, Extensible Toolkit for Scientific Computation (PETSc). The algorithm and the underlying nonoverlapping domain decomposition framework are described with a specific focus on their current implementation in the library. Available user customizations are also presented, together with an experimental interface to the finite element tearing and interconnecting dual-primal methods within PETSc. Large-scale parallel numerical results are provided for the latest version of the code, which is able to tackle symmetric positive definite problems with highly heterogeneous distributions of the coefficients. Current limitations and future extensions of the preconditioner class are also discussed.
Troudet, T.; Garg, S.; Merrill, W.
1992-01-01
The design of a dynamic neurocontroller with good robustness properties is presented for a multivariable aircraft control problem. The internal dynamics of the neurocontroller are synthesized by a state estimator feedback loop. The neurocontrol is generated by a multilayer feedforward neural network which is trained through backpropagation to minimize an objective function that is a weighted sum of tracking errors, and control input commands and rates. The neurocontroller exhibits good robustness through stability margins in phase and vehicle output gains. By maintaining performance and stability in the presence of sensor failures in the error loops, the structure of the neurocontroller is also consistent with the classical approach of flight control design.
Naïve and Robust: Class-Conditional Independence in Human Classification Learning
Jarecki, Jana B.; Meder, Björn; Nelson, Jonathan D.
2018-01-01
Humans excel in categorization. Yet from a computational standpoint, learning a novel probabilistic classification task involves severe computational challenges. The present paper investigates one way to address these challenges: assuming class-conditional independence of features. This feature independence assumption simplifies the inference…
Designing a Robust Nonlinear Dynamic Inversion Controller for Spacecraft Formation Flying
Directory of Open Access Journals (Sweden)
Inseok Yang
2014-01-01
Full Text Available The robust nonlinear dynamic inversion (RNDI control technique is proposed to keep the relative position of spacecrafts while formation flying. The proposed RNDI control method is based on nonlinear dynamic inversion (NDI. NDI is nonlinear control method that replaces the original dynamics into the user-selected desired dynamics. Because NDI removes nonlinearities in the model by inverting the original dynamics directly, it also eliminates the need of designing suitable controllers for each equilibrium point; that is, NDI works as self-scheduled controller. Removing the original model also provides advantages of ease to satisfy the specific requirements by simply handling desired dynamics. Therefore, NDI is simple and has many similarities to classical control. In real applications, however, it is difficult to achieve perfect cancellation of the original dynamics due to uncertainties that lead to performance degradation and even make the system unstable. This paper proposes robustness assurance method for NDI. The proposed RNDI is designed by combining NDI and sliding mode control (SMC. SMC is inherently robust using high-speed switching inputs. This paper verifies similarities of NDI and SMC, firstly. And then RNDI control method is proposed. The performance of the proposed method is evaluated by simulations applied to spacecraft formation flying problem.
The dynamics of absence behaviour: Interrelations between absence from class and absence in class
DEFF Research Database (Denmark)
Jonasson, Charlotte
2011-01-01
Abstract: Background: Studies of absence in educational settings have primarily been concerned with the causes for and results of student absence. However, recent research has argued that distinguishing between different forms of absence could be important. In consequence, studying the way in whi...... in the social practice of students, teachers and school managers. Evaluations of both absence from class and absence in class are important for understanding how absence behaviour can be identified and prevented....... performance. It is helpful to describe these findings using theoretical frameworks from sociology and psychology: specifically, spill-over theory and symbolic capital theory. Conclusions: This study has demonstrated how different forms of absence become dynamically interrelated through ongoing negotiations...
Dynamic optimization and robust explicit model predictive control of hydrogen storage tank
Panos, C.
2010-09-01
We present a general framework for the optimal design and control of a metal-hydride bed under hydrogen desorption operation. The framework features: (i) a detailed two-dimension dynamic process model, (ii) a design and operational dynamic optimization step, and (iii) an explicit/multi-parametric model predictive controller design step. For the controller design, a reduced order approximate model is obtained, based on which nominal and robust multi-parametric controllers are designed. © 2010 Elsevier Ltd.
Dynamic optimization and robust explicit model predictive control of hydrogen storage tank
Panos, C.; Kouramas, K.I.; Georgiadis, M.C.; Pistikopoulos, E.N.
2010-01-01
We present a general framework for the optimal design and control of a metal-hydride bed under hydrogen desorption operation. The framework features: (i) a detailed two-dimension dynamic process model, (ii) a design and operational dynamic optimization step, and (iii) an explicit/multi-parametric model predictive controller design step. For the controller design, a reduced order approximate model is obtained, based on which nominal and robust multi-parametric controllers are designed. © 2010 Elsevier Ltd.
Directory of Open Access Journals (Sweden)
Chengdong Yang
2015-01-01
Full Text Available This paper addresses the exponential synchronization problem of a class of master-slave distributed parameter systems (DPSs with spatially variable coefficients and spatiotemporally variable nonlinear perturbation, modeled by a couple of semilinear parabolic partial differential equations (PDEs. With a locally Lipschitz constraint, the perturbation is a continuous function of time, space, and system state. Firstly, a sufficient condition for the robust exponential synchronization of the unforced semilinear master-slave PDE systems is investigated for all admissible nonlinear perturbations. Secondly, a robust distributed proportional-spatial derivative (P-sD state feedback controller is desired such that the closed-loop master-slave PDE systems achieve exponential synchronization. Using Lyapunov’s direct method and the technique of integration by parts, the main results of this paper are presented in terms of spatial differential linear matrix inequalities (SDLMIs. Finally, two numerical examples are provided to show the effectiveness of the proposed methods applied to the robust exponential synchronization problem of master-slave PDE systems with nonlinear perturbation.
A robust state-space kinetics-guided framework for dynamic PET image reconstruction
International Nuclear Information System (INIS)
Tong, S; Alessio, A M; Kinahan, P E; Liu, H; Shi, P
2011-01-01
Dynamic PET image reconstruction is a challenging issue due to the low SNR and the large quantity of spatio-temporal data. We propose a robust state-space image reconstruction (SSIR) framework for activity reconstruction in dynamic PET. Unlike statistically-based frame-by-frame methods, tracer kinetic modeling is incorporated to provide physiological guidance for the reconstruction, harnessing the temporal information of the dynamic data. Dynamic reconstruction is formulated in a state-space representation, where a compartmental model describes the kinetic processes in a continuous-time system equation, and the imaging data are expressed in a discrete measurement equation. Tracer activity concentrations are treated as the state variables, and are estimated from the dynamic data. Sampled-data H ∞ filtering is adopted for robust estimation. H ∞ filtering makes no assumptions on the system and measurement statistics, and guarantees bounded estimation error for finite-energy disturbances, leading to robust performance for dynamic data with low SNR and/or errors. This alternative reconstruction approach could help us to deal with unpredictable situations in imaging (e.g. data corruption from failed detector blocks) or inaccurate noise models. Experiments on synthetic phantom and patient PET data are performed to demonstrate feasibility of the SSIR framework, and to explore its potential advantages over frame-by-frame statistical reconstruction approaches.
Robust estimation and moment selection in dynamic fixed-effects panel data models
Cizek, Pavel; Aquaro, Michele
Considering linear dynamic panel data models with fixed effects, existing outlier–robust estimators based on the median ratio of two consecutive pairs of first-differenced data are extended to higher-order differencing. The estimation procedure is thus based on many pairwise differences and their
An Improved Generalized Predictive Control in a Robust Dynamic Partial Least Square Framework
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Jin Xin
2015-01-01
Full Text Available To tackle the sensitivity to outliers in system identification, a new robust dynamic partial least squares (PLS model based on an outliers detection method is proposed in this paper. An improved radial basis function network (RBFN is adopted to construct the predictive model from inputs and outputs dataset, and a hidden Markov model (HMM is applied to detect the outliers. After outliers are removed away, a more robust dynamic PLS model is obtained. In addition, an improved generalized predictive control (GPC with the tuning weights under dynamic PLS framework is proposed to deal with the interaction which is caused by the model mismatch. The results of two simulations demonstrate the effectiveness of proposed method.
Stochastic Mesocortical Dynamics and Robustness of Working Memory during Delay-Period.
Directory of Open Access Journals (Sweden)
Melissa Reneaux
Full Text Available The role of prefronto-mesoprefrontal system in the dopaminergic modulation of working memory during delayed response tasks is well-known. Recently, a dynamical model of the closed-loop mesocortical circuit has been proposed which employs a deterministic framework to elucidate the system's behavior in a qualitative manner. Under natural conditions, noise emanating from various sources affects the circuit's functioning to a great extent. Accordingly in the present study, we reformulate the model into a stochastic framework and investigate its steady state properties in the presence of constant background noise during delay-period. From the steady state distribution, global potential landscape and signal-to-noise ratio are obtained which help in defining robustness of the circuit dynamics. This provides insight into the robustness of working memory during delay-period against its disruption due to background noise. The findings reveal that the global profile of circuit's robustness is predominantly governed by the level of D1 receptor activity and high D1 receptor stimulation favors the working memory-associated sustained-firing state over the spontaneous-activity state of the system. Moreover, the circuit's robustness is further fine-tuned by the levels of excitatory and inhibitory activities in a way such that the robustness of sustained-firing state exhibits an inverted-U shaped profile with respect to D1 receptor stimulation. It is predicted that the most robust working memory is formed possibly at a subtle ratio of the excitatory and inhibitory activities achieved at a critical level of D1 receptor stimulation. The study also paves a way to understand various cognitive deficits observed in old-age, acute stress and schizophrenia and suggests possible mechanistic routes to the working memory impairments based on the circuit's robustness profile.
Stochastic Mesocortical Dynamics and Robustness of Working Memory during Delay-Period.
Reneaux, Melissa; Gupta, Rahul; Karmeshu
2015-01-01
The role of prefronto-mesoprefrontal system in the dopaminergic modulation of working memory during delayed response tasks is well-known. Recently, a dynamical model of the closed-loop mesocortical circuit has been proposed which employs a deterministic framework to elucidate the system's behavior in a qualitative manner. Under natural conditions, noise emanating from various sources affects the circuit's functioning to a great extent. Accordingly in the present study, we reformulate the model into a stochastic framework and investigate its steady state properties in the presence of constant background noise during delay-period. From the steady state distribution, global potential landscape and signal-to-noise ratio are obtained which help in defining robustness of the circuit dynamics. This provides insight into the robustness of working memory during delay-period against its disruption due to background noise. The findings reveal that the global profile of circuit's robustness is predominantly governed by the level of D1 receptor activity and high D1 receptor stimulation favors the working memory-associated sustained-firing state over the spontaneous-activity state of the system. Moreover, the circuit's robustness is further fine-tuned by the levels of excitatory and inhibitory activities in a way such that the robustness of sustained-firing state exhibits an inverted-U shaped profile with respect to D1 receptor stimulation. It is predicted that the most robust working memory is formed possibly at a subtle ratio of the excitatory and inhibitory activities achieved at a critical level of D1 receptor stimulation. The study also paves a way to understand various cognitive deficits observed in old-age, acute stress and schizophrenia and suggests possible mechanistic routes to the working memory impairments based on the circuit's robustness profile.
Synchronization dynamics in a small pacemaker neuronal ensemble via a robust adaptive controller
International Nuclear Information System (INIS)
Cornejo-Pérez, O.; Solis-Perales, G.C.; Arenas-Prado, J.A.
2012-01-01
The synchronization dynamics of a pacemaker neuronal ensemble under the action of a control command is studied herein. The ensemble corresponds to the pyloric central pattern generator of the stomatogastric ganglion of lobster. The desired dynamics is provided by means of an external master neuron and it is induced via a nonlinear controller. Such a controller is composed of a linearizing-like controller and a high gain observer; the controller is able to counteract uncertainties and external perturbations in the controlled system. Numerical simulations of the robust synchronization dynamics of the master neuron and the pacemaker neuronal ensemble are displayed.
Tejedor, Alejandro; Longjas, Anthony; Zaliapin, Ilya; Ambroj, Samuel; Foufoula-Georgiou, Efi
2017-08-17
Network robustness against attacks has been widely studied in fields as diverse as the Internet, power grids and human societies. But current definition of robustness is only accounting for half of the story: the connectivity of the nodes unaffected by the attack. Here we propose a new framework to assess network robustness, wherein the connectivity of the affected nodes is also taken into consideration, acknowledging that it plays a crucial role in properly evaluating the overall network robustness in terms of its future recovery from the attack. Specifically, we propose a dual perspective approach wherein at any instant in the network evolution under attack, two distinct networks are defined: (i) the Active Network (AN) composed of the unaffected nodes and (ii) the Idle Network (IN) composed of the affected nodes. The proposed robustness metric considers both the efficiency of destroying the AN and that of building-up the IN. We show, via analysis of well-known prototype networks and real world data, that trade-offs between the efficiency of Active and Idle Network dynamics give rise to surprising robustness crossovers and re-rankings, which can have significant implications for decision making.
Dynamic robustness of knowledge collaboration network of open source product development community
Zhou, Hong-Li; Zhang, Xiao-Dong
2018-01-01
As an emergent innovative design style, open source product development communities are characterized by a self-organizing, mass collaborative, networked structure. The robustness of the community is critical to its performance. Using the complex network modeling method, the knowledge collaboration network of the community is formulated, and the robustness of the network is systematically and dynamically studied. The characteristics of the network along the development period determine that its robustness should be studied from three time stages: the start-up, development and mature stages of the network. Five kinds of user-loss pattern are designed, to assess the network's robustness under different situations in each of these three time stages. Two indexes - the largest connected component and the network efficiency - are used to evaluate the robustness of the community. The proposed approach is applied in an existing open source car design community. The results indicate that the knowledge collaboration networks show different levels of robustness in different stages and different user loss patterns. Such analysis can be applied to provide protection strategies for the key users involved in knowledge dissemination and knowledge contribution at different stages of the network, thereby promoting the sustainable and stable development of the open source community.
The optimal filtering of a class of dynamic multiscale systems
Institute of Scientific and Technical Information of China (English)
PAN Quan; ZHANG Lei; CUI Peiling; ZHANG Hongcai
2004-01-01
This paper discusses the optimal filtering of a class of dynamic multiscale systems (DMS), which are observed independently by several sensors distributed at different resolution spaces. The system is subject to known dynamic system model. The resolution and sampling frequencies of the sensors are supposed to decrease by a factor of two. By using the Haar wavelet transform to link the state nodes at each of the scales within a time block, a discrete-time model of this class of multiscale systems is given, and the conditions for applying Kalman filtering are proven. Based on the linear time-invariant system, the controllability and observability of the system and the stability of the Kalman filtering is studied, and a theorem is given. It is proved that the Kalman filter is stable if only the system is controllable and observable at the finest scale. Finally, a constant-velocity process is used to obtain insight into the efficiencies offered by our model and algorithm.
A study of tachyon dynamics for broad classes of potentials
Energy Technology Data Exchange (ETDEWEB)
Quiros, Israel [Division de Ciencias e Ingenieria de la Universidad de Guanajuato, AP 150, 37150, Leon, Guanajuato (Mexico); Gonzalez, Tame [Departamento de Fisica, Universidad Central de Las Villas, 54830 Santa Clara (Cuba); Gonzalez, Dania; Napoles, Yunelsy [Departamento de Matematica, Universidad Central de Las Villas, 54830 Santa Clara (Cuba); GarcIa-Salcedo, Ricardo [Centro de Investigacion en Ciencia Aplicada y Tecnologia Avanzada-Legaria del IPN, Mexico DF (Mexico); Moreno, Claudia, E-mail: iquiros@Fisica.ugto.m, E-mail: tame@uclv.edu.c, E-mail: dgm@uclv.edu.c, E-mail: yna@uclv.edu.c, E-mail: rigarcias@ipn.m, E-mail: claudia.moreno@cucei.udg.m [Departamento de Fisica y Matematicas, Centro Universitario de Ciencias Exactas e IngenierIas, Av. Revolucion 1500 SR, Universidad de Guadalajara, 44430 Guadalajara, Jalisco (Mexico)
2010-11-07
We investigate in detail the asymptotic properties of tachyon cosmology for a broad class of self-interaction potentials. The present approach relies on an appropriate re-definition of the tachyon field, which, in conjunction with a method formerly applied in the bibliography in a different context allows us to generalize the dynamical systems study of tachyon cosmology to a wider class of self-interaction potentials beyond the (inverse) square-law one. It is revealed that independent of the functional form of the potential, the matter-dominated solution and the ultra-relativistic (also matter-dominated) solution are always associated with equilibrium points in the phase space of the tachyon models. The latter is always the past attractor, while the former is a saddle critical point. For inverse power-law potentials V{proportional_to}{phi}{sup -2{lambda}} the late-time attractor is always the de Sitter solution, while for sinh-like potentials V{proportional_to}sinh {sup -{alpha}}({lambda}{sup {phi}}), depending on the region of parameter space, the late-time attractor can be either the inflationary tachyon-dominated solution or the matter-scaling (also inflationary) phase. In general, for most part of known quintessential potentials, the late-time dynamics will be associated either with de Sitter inflation, or with matter-scaling, or with scalar field-dominated solutions.
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.
Wang, Ziyin; Liu, Mandan; Cheng, Yicheng; Wang, Rubin
2017-06-01
In this paper, a dynamical recurrent artificial neural network (ANN) is proposed and studied. Inspired from a recent research in neuroscience, we introduced nonsynaptic coupling to form a dynamical component of the network. We mathematically proved that, with adequate neurons provided, this dynamical ANN model is capable of approximating any continuous dynamic system with an arbitrarily small error in a limited time interval. Its extreme concise Jacobian matrix makes the local stability easy to control. We designed this ANN for fitting and forecasting dynamic data and obtained satisfied results in simulation. The fitting performance is also compared with those of both the classic dynamic ANN and the state-of-the-art models. Sufficient trials and the statistical results indicated that our model is superior to those have been compared. Moreover, we proposed a robust approximation problem, which asking the ANN to approximate a cluster of input-output data pairs in large ranges and to forecast the output of the system under previously unseen input. Our model and learning scheme proposed in this paper have successfully solved this problem, and through this, the approximation becomes much more robust and adaptive to noise, perturbation, and low-order harmonic wave. This approach is actually an efficient method for compressing massive external data of a dynamic system into the weight of the ANN.
International Nuclear Information System (INIS)
Iskander, Boulaabi; Faycal, Ben Hmida; Moncef, Gossa; Anis, Sellami
2009-01-01
This paper presents a design method of a Sliding Mode Observer (SMO) for robust sensor faults reconstruction of systems with matched uncertainty. This class of uncertainty requires a known upper bound. The basic idea is to use the H ∞ concept to design the observer, which minimizes the effect of the uncertainty on the reconstruction of the sensor faults. Specifically, we applied the equivalent output error injection concept from previous work in Fault Detection and Isolation (FDI) scheme. Then, these two problems of design and reconstruction can be expressed and numerically formulate via Linear Matrix Inequalities (LMIs) optimization. Finally, a numerical example is given to illustrate the validity and the applicability of the proposed approach.
Robust control of uncertain dynamic systems a linear state space approach
Yedavalli, Rama K
2014-01-01
This textbook aims to provide a clear understanding of the various tools of analysis and design for robust stability and performance of uncertain dynamic systems. In model-based control design and analysis, mathematical models can never completely represent the “real world” system that is being modeled, and thus it is imperative to incorporate and accommodate a level of uncertainty into the models. This book directly addresses these issues from a deterministic uncertainty viewpoint and focuses on the interval parameter characterization of uncertain systems. Various tools of analysis and design are presented in a consolidated manner. This volume fills a current gap in published works by explicitly addressing the subject of control of dynamic systems from linear state space framework, namely using a time-domain, matrix-theory based approach. This book also: Presents and formulates the robustness problem in a linear state space model framework Illustrates various systems level methodologies with examples and...
Fuzzy Counter Propagation Neural Network Control for a Class of Nonlinear Dynamical Systems
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Vandana Sakhre
2015-01-01
Full Text Available Fuzzy Counter Propagation Neural Network (FCPN controller design is developed, for a class of nonlinear dynamical systems. In this process, the weight connecting between the instar and outstar, that is, input-hidden and hidden-output layer, respectively, is adjusted by using Fuzzy Competitive Learning (FCL. FCL paradigm adopts the principle of learning, which is used to calculate Best Matched Node (BMN which is proposed. This strategy offers a robust control of nonlinear dynamical systems. FCPN is compared with the existing network like Dynamic Network (DN and Back Propagation Network (BPN on the basis of Mean Absolute Error (MAE, Mean Square Error (MSE, Best Fit Rate (BFR, and so forth. It envisages that the proposed FCPN gives better results than DN and BPN. The effectiveness of the proposed FCPN algorithms is demonstrated through simulations of four nonlinear dynamical systems and multiple input and single output (MISO and a single input and single output (SISO gas furnace Box-Jenkins time series data.
Increasing the Robustness of Biometric Templates for Dynamic Signature Biometric Systems
Tolosana Moranchel, Rubén; Vera-Rodríguez, Rubén; Ortega-García, Javier; Fiérrez, Julián
2015-01-01
Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. R. Tolosana, R. Vera-Rodriguez, J. Ortega-Garcia and J. Fierrez, "Increasing the robustness of biometric templates for dynamic...
Senkel, Luise
2016-01-01
This edited book aims at presenting current research activities in the field of robust variable-structure systems. The scope equally comprises highlighting novel methodological aspects as well as presenting the use of variable-structure techniques in industrial applications including their efficient implementation on hardware for real-time control. The target audience primarily comprises research experts in the field of control theory and nonlinear dynamics but the book may also be beneficial for graduate students.
Dynamic Surface Adaptive Robust Control of Unmanned Marine Vehicles with Disturbance Observer
Directory of Open Access Journals (Sweden)
Pengchao Zhang
2018-01-01
Full Text Available This paper presents a dynamic surface adaptive robust control method with disturbance observer for unmanned marine vehicles (UMV. It uses adaptive law to estimate and compensate the disturbance observer error. Dynamic surface is introduced to solve the “differential explosion” caused by the virtual control derivation in traditional backstepping method. The final controlled system is proved to be globally uniformly bounded based on Lyapunov stability theory. Simulation results illustrate the effectiveness of the proposed controller, which can realize the three-dimensional trajectory tracking for UMV with the systematic uncertainty and time-varying disturbances.
Designing Dynamic Adaptive Policy Pathways using Many-Objective Robust Decision Making
Kwakkel, Jan; Haasnoot, Marjolijn
2017-04-01
Dealing with climate risks in water management requires confronting a wide variety of deeply uncertain factors, while navigating a many dimensional space of trade-offs amongst objectives. There is an emerging body of literature on supporting this type of decision problem, under the label of decision making under deep uncertainty. Two approaches within this literature are Many-Objective Robust Decision Making, and Dynamic Adaptive Policy Pathways. In recent work, these approaches have been compared. One of the main conclusions of this comparison was that they are highly complementary. Many-Objective Robust Decision Making is a model based decision support approach, while Dynamic Adaptive Policy Pathways is primarily a conceptual framework for the design of flexible strategies that can be adapted over time in response to how the future is actually unfolding. In this research we explore this complementarity in more detail. Specifically, we demonstrate how Many-Objective Robust Decision Making can be used to design adaptation pathways. We demonstrate this combined approach using a water management problem, in the Netherlands. The water level of Lake IJselmeer, the main fresh water resource of the Netherlands, is currently managed through discharge by gravity. Due to climate change, this won't be possible in the future, unless water levels are changed. Changing the water level has undesirable flood risk and spatial planning consequences. The challenge is to find promising adaptation pathways that balance objectives related to fresh water supply, flood risk, and spatial issues, while accounting for uncertain climatic and land use change. We conclude that the combination of Many-Objective Robust Decision Making and Dynamic Adaptive Policy Pathways is particularly suited for dealing with deeply uncertain climate risks.
Cellular population dynamics control the robustness of the stem cell niche
Directory of Open Access Journals (Sweden)
Adam L. MacLean
2015-11-01
Full Text Available Within populations of cells, fate decisions are controlled by an indeterminate combination of cell-intrinsic and cell-extrinsic factors. In the case of stem cells, the stem cell niche is believed to maintain ‘stemness’ through communication and interactions between the stem cells and one or more other cell-types that contribute to the niche conditions. To investigate the robustness of cell fate decisions in the stem cell hierarchy and the role that the niche plays, we introduce simple mathematical models of stem and progenitor cells, their progeny and their interplay in the niche. These models capture the fundamental processes of proliferation and differentiation and allow us to consider alternative possibilities regarding how niche-mediated signalling feedback regulates the niche dynamics. Generalised stability analysis of these stem cell niche systems enables us to describe the stability properties of each model. We find that although the number of feasible states depends on the model, their probabilities of stability in general do not: stem cell–niche models are stable across a wide range of parameters. We demonstrate that niche-mediated feedback increases the number of stable steady states, and show how distinct cell states have distinct branching characteristics. The ecological feedback and interactions mediated by the stem cell niche thus lend (surprisingly high levels of robustness to the stem and progenitor cell population dynamics. Furthermore, cell–cell interactions are sufficient for populations of stem cells and their progeny to achieve stability and maintain homeostasis. We show that the robustness of the niche – and hence of the stem cell pool in the niche – depends only weakly, if at all, on the complexity of the niche make-up: simple as well as complicated niche systems are capable of supporting robust and stable stem cell dynamics.
Position-Invariant Robust Features for Long-Term Recognition of Dynamic Outdoor Scenes
Kawewong, Aram; Tangruamsub, Sirinart; Hasegawa, Osamu
A novel Position-Invariant Robust Feature, designated as PIRF, is presented to address the problem of highly dynamic scene recognition. The PIRF is obtained by identifying existing local features (i.e. SIFT) that have a wide baseline visibility within a place (one place contains more than one sequential images). These wide-baseline visible features are then represented as a single PIRF, which is computed as an average of all descriptors associated with the PIRF. Particularly, PIRFs are robust against highly dynamical changes in scene: a single PIRF can be matched correctly against many features from many dynamical images. This paper also describes an approach to using these features for scene recognition. Recognition proceeds by matching an individual PIRF to a set of features from test images, with subsequent majority voting to identify a place with the highest matched PIRF. The PIRF system is trained and tested on 2000+ outdoor omnidirectional images and on COLD datasets. Despite its simplicity, PIRF offers a markedly better rate of recognition for dynamic outdoor scenes (ca. 90%) than the use of other features. Additionally, a robot navigation system based on PIRF (PIRF-Nav) can outperform other incremental topological mapping methods in terms of time (70% less) and memory. The number of PIRFs can be reduced further to reduce the time while retaining high accuracy, which makes it suitable for long-term recognition and localization.
Directory of Open Access Journals (Sweden)
M. De la Sen
2017-01-01
Full Text Available This paper formulates an “ad hoc” robust version under parametrical disturbances of the discrete version of the Kalman-Yakubovich-Popov Lemma for a class of positive hybrid dynamic linear systems which consist of a continuous-time system coupled with a discrete-time or a digital one. An extended discrete system, whose state vector contains both the digital one and the discretization of the continuous-time one at sampling instants, is a key analysis element in the formulation. The hyperstability and asymptotic hyperstability properties of the studied class of positive hybrid systems under feedback from any member of a nonlinear (and, eventually, time-varying class of controllers, which satisfies a Popov’s-type inequality, are also investigated as linked to the positive realness of the associated transfer matrices.
Unaldi, Numan; Asari, Vijayan K.; Rahman, Zia-ur
2009-05-01
Recently we proposed a wavelet-based dynamic range compression algorithm to improve the visual quality of digital images captured from high dynamic range scenes with non-uniform lighting conditions. The fast image enhancement algorithm that provides dynamic range compression, while preserving the local contrast and tonal rendition, is also a good candidate for real time video processing applications. Although the colors of the enhanced images produced by the proposed algorithm are consistent with the colors of the original image, the proposed algorithm fails to produce color constant results for some "pathological" scenes that have very strong spectral characteristics in a single band. The linear color restoration process is the main reason for this drawback. Hence, a different approach is required for the final color restoration process. In this paper the latest version of the proposed algorithm, which deals with this issue is presented. The results obtained by applying the algorithm to numerous natural images show strong robustness and high image quality.
Robust H∞ Control of Neutral System with Time-Delay for Dynamic Positioning Ships
Directory of Open Access Journals (Sweden)
Dawei Zhao
2015-01-01
Full Text Available Due to the input time-delay existing in most thrust systems of the ships, the robust H∞ controller is designed for the ship dynamic positioning (DP system with time-delay. The input delay system is turned to a neutral time-delay system by a state-derivative control law. The less conservative result is derived for the neutral system with state-derivative feedback by the delay-decomposition approach and linear matrix inequality (LMI. Finally, the numerical simulations demonstrate the asymptotic stability and robustness of the controller and verify that the designed DP controller is effective in the varying environment disturbances of wind, waves, and ocean currents.
Imura, Jun-ichi; Ueta, Tetsushi
2015-01-01
This book is the first to report on theoretical breakthroughs on control of complex dynamical systems developed by collaborative researchers in the two fields of dynamical systems theory and control theory. As well, its basic point of view is of three kinds of complexity: bifurcation phenomena subject to model uncertainty, complex behavior including periodic/quasi-periodic orbits as well as chaotic orbits, and network complexity emerging from dynamical interactions between subsystems. Analysis and Control of Complex Dynamical Systems offers a valuable resource for mathematicians, physicists, and biophysicists, as well as for researchers in nonlinear science and control engineering, allowing them to develop a better fundamental understanding of the analysis and control synthesis of such complex systems.
Robust and efficient parameter estimation in dynamic models of biological systems.
Gábor, Attila; Banga, Julio R
2015-10-29
Dynamic modelling provides a systematic framework to understand function in biological systems. Parameter estimation in nonlinear dynamic models remains a very challenging inverse problem due to its nonconvexity and ill-conditioning. Associated issues like overfitting and local solutions are usually not properly addressed in the systems biology literature despite their importance. Here we present a method for robust and efficient parameter estimation which uses two main strategies to surmount the aforementioned difficulties: (i) efficient global optimization to deal with nonconvexity, and (ii) proper regularization methods to handle ill-conditioning. In the case of regularization, we present a detailed critical comparison of methods and guidelines for properly tuning them. Further, we show how regularized estimations ensure the best trade-offs between bias and variance, reducing overfitting, and allowing the incorporation of prior knowledge in a systematic way. We illustrate the performance of the presented method with seven case studies of different nature and increasing complexity, considering several scenarios of data availability, measurement noise and prior knowledge. We show how our method ensures improved estimations with faster and more stable convergence. We also show how the calibrated models are more generalizable. Finally, we give a set of simple guidelines to apply this strategy to a wide variety of calibration problems. Here we provide a parameter estimation strategy which combines efficient global optimization with a regularization scheme. This method is able to calibrate dynamic models in an efficient and robust way, effectively fighting overfitting and allowing the incorporation of prior information.
Adaptive dynamic inversion robust control for BTT missile based on wavelet neural network
Li, Chuanfeng; Wang, Yongji; Deng, Zhixiang; Wu, Hao
2009-10-01
A new nonlinear control strategy incorporated the dynamic inversion method with wavelet neural networks is presented for the nonlinear coupling system of Bank-to-Turn(BTT) missile in reentry phase. The basic control law is designed by using the dynamic inversion feedback linearization method, and the online learning wavelet neural network is used to compensate the inversion error due to aerodynamic parameter errors, modeling imprecise and external disturbance in view of the time-frequency localization properties of wavelet transform. Weights adjusting laws are derived according to Lyapunov stability theory, which can guarantee the boundedness of all signals in the whole system. Furthermore, robust stability of the closed-loop system under this tracking law is proved. Finally, the six degree-of-freedom(6DOF) simulation results have shown that the attitude angles can track the anticipant command precisely under the circumstances of existing external disturbance and in the presence of parameter uncertainty. It means that the dependence on model by dynamic inversion method is reduced and the robustness of control system is enhanced by using wavelet neural network(WNN) to reconstruct inversion error on-line.
Dynamic Programming Used to Align Protein Structures with a Spectrum Is Robust
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Allen Holder
2013-11-01
Full Text Available Several efficient algorithms to conduct pairwise comparisons among large databases of protein structures have emerged in the recent literature. The central theme is the design of a measure between the Cα atoms of two protein chains, from which dynamic programming is used to compute an alignment. The efficiency and efficacy of these algorithms allows large-scale computational studies that would have been previously impractical. The computational study herein shows that the structural alignment algorithm eigen-decomposition alignment with the spectrum (EIGAs is robust against both parametric and structural variation.
Constrained dynamical systems: separation of constraints into first and second classes
International Nuclear Information System (INIS)
Chitaya, N.P.; Gogilidze, S.A.; Surovtsev, Yu.S.
1996-01-01
In the Dirac approach to the generalized Hamiltonian formalism, dynamical systems with first- and second-class constraints are investigated. The classification and separation of constraints into the first- and second-class ones are presented with the help of passing to an equivalent canonical set of constraints. The general structure of second-class constraints is clarified. 14 refs
A Robust and Efficient Numerical Method for RNA-Mediated Viral Dynamics
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Vladimir Reinharz
2017-10-01
Full Text Available The multiscale model of hepatitis C virus (HCV dynamics, which includes intracellular viral RNA (vRNA replication, has been formulated in recent years in order to provide a new conceptual framework for understanding the mechanism of action of a variety of agents for the treatment of HCV. We present a robust and efficient numerical method that belongs to the family of adaptive stepsize methods and is implicit, a Rosenbrock type method that is highly suited to solve this problem. We provide a Graphical User Interface that applies this method and is useful for simulating viral dynamics during treatment with anti-HCV agents that act against HCV on the molecular level.
Robust image registration for multiple exposure high dynamic range image synthesis
Yao, Susu
2011-03-01
Image registration is an important preprocessing technique in high dynamic range (HDR) image synthesis. This paper proposed a robust image registration method for aligning a group of low dynamic range images (LDR) that are captured with different exposure times. Illumination change and photometric distortion between two images would result in inaccurate registration. We propose to transform intensity image data into phase congruency to eliminate the effect of the changes in image brightness and use phase cross correlation in the Fourier transform domain to perform image registration. Considering the presence of non-overlapped regions due to photometric distortion, evolutionary programming is applied to search for the accurate translation parameters so that the accuracy of registration is able to be achieved at a hundredth of a pixel level. The proposed algorithm works well for under and over-exposed image registration. It has been applied to align LDR images for synthesizing high quality HDR images..
Performance-Driven Robust Identification and Control of Uncertain Dynamical Systems
Energy Technology Data Exchange (ETDEWEB)
Basar, Tamer
2001-10-29
The grant DEFG02-97ER13939 from the Department of Energy has supported our research program on robust identification and control of uncertain dynamical systems, initially for the three-year period June 15, 1997-June 14, 2000, which was then extended on a no-cost basis for another year until June 14, 2001. This final report provides an overview of our research conducted during this period, along with a complete list of publications supported by the Grant. Within the scope of this project, we have studied fundamental issues that arise in modeling, identification, filtering, control, stabilization, control-based model reduction, decomposition and aggregation, and optimization of uncertain systems. The mathematical framework we have worked in has allowed the system dynamics to be only partially known (with the uncertainties being of both parametric or structural nature), and further the dynamics to be perturbed by unknown dynamic disturbances. Our research over these four years has generated a substantial body of new knowledge, and has led to new major developments in theory, applications, and computational algorithms. These have all been documented in various journal articles and book chapters, and have been presented at leading conferences, as to be described. A brief description of the results we have obtained within the scope of this project can be found in Section 3. To set the stage for the material of that section, we first provide in the next section (Section 2) a brief description of the issues that arise in the control of uncertain systems, and introduce several criteria under which optimality will lead to robustness and stability. Section 4 contains a list of references cited in these two sections. A list of our publications supported by the DOE Grant (covering the period June 15, 1997-June 14, 2001) comprises Section 5 of the report.
Mutual Information Based Dynamic Integration of Multiple Feature Streams for Robust Real-Time LVCSR
Sato, Shoei; Kobayashi, Akio; Onoe, Kazuo; Homma, Shinichi; Imai, Toru; Takagi, Tohru; Kobayashi, Tetsunori
We present a novel method of integrating the likelihoods of multiple feature streams, representing different acoustic aspects, for robust speech recognition. The integration algorithm dynamically calculates a frame-wise stream weight so that a higher weight is given to a stream that is robust to a variety of noisy environments or speaking styles. Such a robust stream is expected to show discriminative ability. A conventional method proposed for the recognition of spoken digits calculates the weights front the entropy of the whole set of HMM states. This paper extends the dynamic weighting to a real-time large-vocabulary continuous speech recognition (LVCSR) system. The proposed weight is calculated in real-time from mutual information between an input stream and active HMM states in a searchs pace without an additional likelihood calculation. Furthermore, the mutual information takes the width of the search space into account by calculating the marginal entropy from the number of active states. In this paper, we integrate three features that are extracted through auditory filters by taking into account the human auditory system's ability to extract amplitude and frequency modulations. Due to this, features representing energy, amplitude drift, and resonant frequency drifts, are integrated. These features are expected to provide complementary clues for speech recognition. Speech recognition experiments on field reports and spontaneous commentary from Japanese broadcast news showed that the proposed method reduced error words by 9.2% in field reports and 4.7% in spontaneous commentaries relative to the best result obtained from a single stream.
A rapid and robust gradient measurement technique using dynamic single-point imaging.
Jang, Hyungseok; McMillan, Alan B
2017-09-01
We propose a new gradient measurement technique based on dynamic single-point imaging (SPI), which allows simple, rapid, and robust measurement of k-space trajectory. To enable gradient measurement, we utilize the variable field-of-view (FOV) property of dynamic SPI, which is dependent on gradient shape. First, one-dimensional (1D) dynamic SPI data are acquired from a targeted gradient axis, and then relative FOV scaling factors between 1D images or k-spaces at varying encoding times are found. These relative scaling factors are the relative k-space position that can be used for image reconstruction. The gradient measurement technique also can be used to estimate the gradient impulse response function for reproducible gradient estimation as a linear time invariant system. The proposed measurement technique was used to improve reconstructed image quality in 3D ultrashort echo, 2D spiral, and multi-echo bipolar gradient-echo imaging. In multi-echo bipolar gradient-echo imaging, measurement of the k-space trajectory allowed the use of a ramp-sampled trajectory for improved acquisition speed (approximately 30%) and more accurate quantitative fat and water separation in a phantom. The proposed dynamic SPI-based method allows fast k-space trajectory measurement with a simple implementation and no additional hardware for improved image quality. Magn Reson Med 78:950-962, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.
Robust filtering for dynamic compensation of self-powered neutron detectors
International Nuclear Information System (INIS)
Peng, Xingjie; Li, Qing; Zhao, Wenbo; Gong, Helin; Wang, Kan
2014-01-01
Highlights: • Three dynamic compensation methods based on robust filtering theory are proposed. • Filter design problems are converted into linear matrix inequality problems. • Rhodium and Vanadium self-powered neutron detectors are used to validate the use of these three dynamic compensation methods. • The numerical simulation results show that all three methods can provide a reasonable balance between response speed and noise suppression. - Abstract: Self-powered neutron detectors (SPNDs), which are widely used in nuclear reactors to obtain core neutron flux distribution, are accurate at steady state but respond slowly to changes in neutron flux. Dynamic compensation methods are required to improve the response speed of the SPNDs and make it possible to apply the SPNDs for core monitoring and surveillance. In this paper, three digital dynamic compensation methods are proposed. All the three methods are based on the convex optimization framework using linear matrix inequalities (LMIs). The simulation results show that all three methods can provide a reasonable balance between response speed and noise suppression
Directory of Open Access Journals (Sweden)
Xubin Ping
2016-01-01
Full Text Available For quasi-linear parameter varying (quasi-LPV systems with bounded disturbance, a synthesis approach of dynamic output feedback robust model predictive control (OFRMPC with the consideration of input saturation is investigated. The saturated dynamic output feedback controller is represented by a convex hull involving the actual dynamic output controller and an introduced auxiliary controller. By taking both the actual output feedback controller and the auxiliary controller with a parameter-dependent form, the main optimization problem can be formulated as convex optimization. The consideration of input saturation in the main optimization problem reduces the conservatism of dynamic output feedback controller design. The estimation error set and bounded disturbance are represented by zonotopes and refreshed by zonotopic set-membership estimation. Compared with the previous results, the proposed algorithm can not only guarantee the recursive feasibility of the optimization problem, but also improve the control performance at the cost of higher computational burden. A nonlinear continuous stirred tank reactor (CSTR example is given to illustrate the effectiveness of the approach.
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Jean Chamberlain Chedjou
2015-01-01
Full Text Available This paper develops a flexible analytical concept for robust shortest path detection in dynamically reconfigurable graphs. The concept is expressed by a mathematical model representing the shortest path problem solver. The proposed mathematical model is characterized by three fundamental parameters expressing (a the graph topology (through the “incidence matrix”, (b the edge weights (with dynamic external weights’ setting capability, and (c the dynamic reconfigurability through external input(s of the source-destination nodes pair. In order to demonstrate the universality of the developed concept, a general algorithm is proposed to determine the three fundamental parameters (of the mathematical model developed for all types of graphs regardless of their topology, magnitude, and size. It is demonstrated that the main advantage of the developed concept is that arc costs, the origin-destination pair setting, and the graph topology are dynamically provided by external commands, which are inputs of the shortest path solver model. This enables high flexibility and full reconfigurability of the developed concept, without any retraining need. To validate the concept developed, benchmarking is performed leading to a comparison of its performance with the performances of two well-known concepts based on neural networks.
Robust fault detection of wind energy conversion systems based on dynamic neural networks.
Talebi, Nasser; Sadrnia, Mohammad Ali; Darabi, Ahmad
2014-01-01
Occurrence of faults in wind energy conversion systems (WECSs) is inevitable. In order to detect the occurred faults at the appropriate time, avoid heavy economic losses, ensure safe system operation, prevent damage to adjacent relevant systems, and facilitate timely repair of failed components; a fault detection system (FDS) is required. Recurrent neural networks (RNNs) have gained a noticeable position in FDSs and they have been widely used for modeling of complex dynamical systems. One method for designing an FDS is to prepare a dynamic neural model emulating the normal system behavior. By comparing the outputs of the real system and neural model, incidence of the faults can be identified. In this paper, by utilizing a comprehensive dynamic model which contains both mechanical and electrical components of the WECS, an FDS is suggested using dynamic RNNs. The presented FDS detects faults of the generator's angular velocity sensor, pitch angle sensors, and pitch actuators. Robustness of the FDS is achieved by employing an adaptive threshold. Simulation results show that the proposed scheme is capable to detect the faults shortly and it has very low false and missed alarms rate.
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Ritwik K Niyogi
Full Text Available Behavioural and neurophysiological studies in primates have increasingly shown the involvement of urgency signals during the temporal integration of sensory evidence in perceptual decision-making. Neuronal correlates of such signals have been found in the parietal cortex, and in separate studies, demonstrated attention-induced gain modulation of both excitatory and inhibitory neurons. Although previous computational models of decision-making have incorporated gain modulation, their abstract forms do not permit an understanding of the contribution of inhibitory gain modulation. Thus, the effects of co-modulating both excitatory and inhibitory neuronal gains on decision-making dynamics and behavioural performance remain unclear. In this work, we incorporate time-dependent co-modulation of the gains of both excitatory and inhibitory neurons into our previous biologically based decision circuit model. We base our computational study in the context of two classic motion-discrimination tasks performed in animals. Our model shows that by simultaneously increasing the gains of both excitatory and inhibitory neurons, a variety of the observed dynamic neuronal firing activities can be replicated. In particular, the model can exhibit winner-take-all decision-making behaviour with higher firing rates and within a significantly more robust model parameter range. It also exhibits short-tailed reaction time distributions even when operating near a dynamical bifurcation point. The model further shows that neuronal gain modulation can compensate for weaker recurrent excitation in a decision neural circuit, and support decision formation and storage. Higher neuronal gain is also suggested in the more cognitively demanding reaction time than in the fixed delay version of the task. Using the exact temporal delays from the animal experiments, fast recruitment of gain co-modulation is shown to maximize reward rate, with a timescale that is surprisingly near the
Robust control and linear parameter varying approaches application to vehicle dynamics
Gaspar, Peter; Bokor, József
2013-01-01
Vehicles are complex systems (non-linear, multi-variable) where the abundance of embedded controllers should ensure better security. This book aims at emphasizing the interest and potential of Linear Parameter Varying methods within the framework of vehicle dynamics, e.g. · proposed control-oriented model, complex enough to handle some system non linearities but still simple for control or observer design, · take into account the adaptability of the vehicle's response to driving situations, to the driver request and/or to the road sollicitations, · manage interactions between various actuators to optimize the dynamic behavior of vehicles. This book results from the 32th International Summer School in Automatic that held in Grenoble, France, in September 2011, where recent methods (based on robust control and LPV technics), then applied to the control of vehicle dynamics, have been presented. After some theoretical background and a view on so...
RSMDP-based Robust Q-learning for Optimal Path Planning in a Dynamic Environment
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Yunfei Zhang
2014-07-01
Full Text Available This paper presents arobust Q-learning method for path planningin a dynamic environment. The method consists of three steps: first, a regime-switching Markov decision process (RSMDP is formed to present the dynamic environment; second a probabilistic roadmap (PRM is constructed, integrated with the RSMDP and stored as a graph whose nodes correspond to a collision-free world state for the robot; and third, an onlineQ-learning method with dynamic stepsize, which facilitates robust convergence of the Q-value iteration, is integrated with the PRM to determine an optimal path for reaching the goal. In this manner, the robot is able to use past experience for improving its performance in avoiding not only static obstacles but also moving obstacles, without knowing the nature of the obstacle motion. The use ofregime switching in the avoidance of obstacles with unknown motion is particularly innovative. The developed approach is applied to a homecare robot in computer simulation. The results show that the online path planner with Q-learning is able torapidly and successfully converge to the correct path.
Robust Takagi-Sugeno Fuzzy Dynamic Regulator for Trajectory Tracking of a Pendulum-Cart System
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Miguel A. Llama
2015-01-01
Full Text Available Starting from a nonlinear model for a pendulum-cart system, on which viscous friction is considered, a Takagi-Sugeno (T-S fuzzy augmented model (TSFAM as well as a TSFAM with uncertainty (TSFAMwU is proposed. Since the design of a T-S fuzzy controller is based on the T-S fuzzy model of the nonlinear system, then, to address the trajectory tracking problem of the pendulum-cart system, three T-S fuzzy controllers are proposed via parallel distributed compensation: (1 a T-S fuzzy servo controller (TSFSC designed from the TSFAM; (2 a robust TSFSC (RTSFSC designed from the TSFAMwU; and (3 a robust T-S fuzzy dynamic regulator (RTSFDR designed from the RTSFSC with the addition of a T-S fuzzy observer, which estimates cart and pendulum velocities. Both TSFAM and TSFAMwU are comprised of two fuzzy rules and designed via local approximation in fuzzy partition spaces technique. Feedback gains for the three fuzzy controllers are obtained via linear matrix inequalities approach. A swing-up controller is developed to swing the pendulum up from its pendant position to its upright position. Real-time experiments validate the effectiveness of the proposed schemes, keeping the pendulum in its upright position while the cart follows a reference signal, standing out the RTSFDR.
CREATE-NL+: A robust control-oriented free boundary dynamic plasma equilibrium solver
Energy Technology Data Exchange (ETDEWEB)
Albanese, R. [Ass. EURATOM/ENEA/CREATE, Universita’ di Napoli “Federico II”, Naples (Italy); Ambrosino, R. [Ass. EURATOM/ENEA/CREATE, Universita’ di Napoli “Parthenope”, Naples (Italy); Mattei, M., E-mail: massimiliano.mattei@unina2.it [Ass. EURATOM/ENEA/CREATE, Seconda Universita’ di Napoli, Naples (Italy)
2015-10-15
CREATE-NL+ is a FEM (Finite Elements Method) solver of the free boundary dynamic plasma equilibrium problem, i.e. the MHD (Magneto Hydro Dynamics) time evolution of 2D axisymmetric plasmas in toroidal nuclear fusion devices, including eddy currents in the passive structures, and feedback control laws for current, position and shape control. This is an improved version of the CREATE-NL code developed in 2002 which was validated on JET and used for the design of the XSC (eXtreme Shape Controller), and for simulation studies on many existing and future tokamaks. A significant improvement was the use of a robust numerical scheme for the calculation of the Jacobian matrix within the Newton based scheme for the solution of the FEM nonlinear algebraic equations. The improved capability of interfacing with other codes, and a general decrease of the computational burden for the simulation of long pulses with small time steps makes this code a flexible tool for the design and testing of magnetic control in a tokamak.
CREATE-NL+: A robust control-oriented free boundary dynamic plasma equilibrium solver
International Nuclear Information System (INIS)
Albanese, R.; Ambrosino, R.; Mattei, M.
2015-01-01
CREATE-NL+ is a FEM (Finite Elements Method) solver of the free boundary dynamic plasma equilibrium problem, i.e. the MHD (Magneto Hydro Dynamics) time evolution of 2D axisymmetric plasmas in toroidal nuclear fusion devices, including eddy currents in the passive structures, and feedback control laws for current, position and shape control. This is an improved version of the CREATE-NL code developed in 2002 which was validated on JET and used for the design of the XSC (eXtreme Shape Controller), and for simulation studies on many existing and future tokamaks. A significant improvement was the use of a robust numerical scheme for the calculation of the Jacobian matrix within the Newton based scheme for the solution of the FEM nonlinear algebraic equations. The improved capability of interfacing with other codes, and a general decrease of the computational burden for the simulation of long pulses with small time steps makes this code a flexible tool for the design and testing of magnetic control in a tokamak.
Design and implementation of an e-class about continuous dynamical systems
Heck, A.; Houwing, H.; Val, J.; Ekimova, L.; Papageorgiou, G.
2009-01-01
In 2008, a small team of university and secondary school teachers in the Netherlands jointly developed an e-class for students in their final pre-university year (age: 17-18 yrs) about continuous dynamical systems. The e-class is an innovative way of teaching and learning mathematics and science by
GCS of a class of chaotic dynamic systems
International Nuclear Information System (INIS)
Park, Ju H.
2005-01-01
This article studies a guaranteed cost synchronization (GCS) problem for a class of chaotic systems. Attention is focused on the design of state feedback controllers such that the resulting closed-loop error system is asymptotically stable and an adequate level of performance is also guaranteed. Using the Lyapunov method and LMI (linear matrix inequality) technique, two criteria for the existence of the controller for GCS are derived in terms of LMIs. To show the effectiveness of the proposed method, GCS problem of Genesio system verified by a numerical example
Stability properties of a general class of nonlinear dynamical systems
Gléria, I. M.; Figueiredo, A.; Rocha Filho, T. M.
2001-05-01
We establish sufficient conditions for the boundedness of the trajectories and the stability of the fixed points in a class of general nonlinear systems, the so-called quasi-polynomial vector fields, with the help of a natural embedding of such systems in a family of generalized Lotka-Volterra (LV) equations. A purely algebraic procedure is developed to determine such conditions. We apply our method to obtain new results for LV systems, by a reparametrization in time variable, and to study general nonlinear vector fields, originally far from the LV format.
Stability properties of a general class of nonlinear dynamical systems
Energy Technology Data Exchange (ETDEWEB)
Gleria, I.M. [Filho Instituto de Fisica, Universidade de Brasilia, Campus Universitario Darcy Ribeiro, Brasilia (Brazil). E-mail: iram@ucb.br; Figueiredo, A. [Filho Instituto de Fisica, Universidade de Brasilia, Campus Universitario Darcy Ribeiro, Brasilia (Brazil). E-mail: annibal@helium.fis.unb.br; Rocha, T.M. [Filho Instituto de Fisica, Universidade de Brasilia, Campus Universitario Darcy Ribeiro, Brasilia (Brazil). E-mail: marciano@helium.fis.unb.br
2001-05-04
We establish sufficient conditions for the boundedness of the trajectories and the stability of the fixed points in a class of general nonlinear systems, the so-called quasi-polynomial vector fields, with the help of a natural embedding of such systems in a family of generalized Lotka-Volterra (LV) equations. A purely algebraic procedure is developed to determine such conditions. We apply our method to obtain new results for LV systems, by a reparametrization in time variable, and to study general nonlinear vector fields, originally far from the LV format. (author)
Paas, L.J.; Bijmolt, T.H.A.; Vermunt, J.K.
2004-01-01
A recent development in marketing research concerns the incorporation of dynamics in consumer segmentation.This paper extends the latent class Markov model, a suitable technique for conducting dynamic segmentation, in order to facilitate lead generation.We demonstrate the application of the latent
On the Context-Aware, Dynamic Spectrum Access for Robust Intraplatoon Communications
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Michał Sybis
2018-01-01
Full Text Available Vehicle platooning is a promising technology that allows to improve the traffic efficiency and passengers safety. Platoons that use cooperative adaptive cruise control, however, require a reliable radio link between platoon members to ensure a required distance between the cars within the platoon, thus maintaining platoon safety. Nowadays, the communication can be realized with the use of 802.11p or cellular vehicle-to-vehicle (C-V2V, but none of this technology is able to provide a reliable link especially in the presence of high traffic or urban scenarios. Therefore, in this paper, we propose a dynamic spectrum management mechanism in V2V communications for platooning purposes. A management system architecture is proposed that comprises the use of context-aware databases, sensing nodes, and spectrum allocation entity. The proposed robust system design aims to keep only the minimum necessary information transmitted over the conventional intelligent transportation system (ITS channel, while moving the remaining data (nonsafety, service-aided, or infotainment to an alternative channel that is selected from the available pool of spectrum white spaces. The initial analysis indicates that the proposed system may significantly improve the performance of wireless communications for the purpose of vehicle platooning.
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Jiajia Song
2017-10-01
Full Text Available Dynamic accurate heart-rate (HR estimation using a photoplethysmogram (PPG during intense physical activities is always challenging due to corruption by motion artifacts (MAs. It is difficult to reconstruct a clean signal and extract HR from contaminated PPG. This paper proposes a robust HR-estimation algorithm framework that uses one-channel PPG and tri-axis acceleration data to reconstruct the PPG and calculate the HR based on features of the PPG and spectral analysis. Firstly, the signal is judged by the presence of MAs. Then, the spectral peaks corresponding to acceleration data are filtered from the periodogram of the PPG when MAs exist. Different signal-processing methods are applied based on the amount of remaining PPG spectral peaks. The main MA-removal algorithm (NFEEMD includes the repeated single-notch filter and ensemble empirical mode decomposition. Finally, HR calibration is designed to ensure the accuracy of HR tracking. The NFEEMD algorithm was performed on the 23 datasets from the 2015 IEEE Signal Processing Cup Database. The average estimation errors were 1.12 BPM (12 training datasets, 2.63 BPM (10 testing datasets and 1.87 BPM (all 23 datasets, respectively. The Pearson correlation was 0.992. The experiment results illustrate that the proposed algorithm is not only suitable for HR estimation during continuous activities, like slow running (13 training datasets, but also for intense physical activities with acceleration, like arm exercise (10 testing datasets.
Dynamics of a Novel Class of Polymers: Polymerized Sulfur
Masser, Kevin; Kim, Jenny; Oleshko, Vladimir; Griebel, Jared; Chung, Woo; Simmons, Adam; Pyun, Jeff; Soles, Christopher
2013-03-01
In this study we investigate the dynamics of a new type of polymer, consisting mainly of sulfur. Room-temperature stable polymerized sulfur samples were prepared by crosslinking the well-known living sulfur polymers formed at elevated temperatures by the addition of a crosslinking agent. This reverse vulcanization process was used to create a series of samples with different amounts of crosslinking agent. These polymers show great promise for use in advanced batteries as cathode materials. Each system exhibits a glassy-state beta relaxation, with the intensity of this relaxation proportional to the crosslinking content. A dynamic glass transition is also observed for each system, and the glass transition temperature/segmental relaxation moves to higher temperatures with increased crosslink content as is typically observed in crosslinked systems. As is typical of polymers, ion motion in these systems is closely coupled to the backbone motion of the host polymer. National Research Council Postdoctoral Fellowship
Hwang, Chih-Lyang; Jan, Chau
2016-02-01
At the beginning, an approximate nonlinear autoregressive moving average (NARMA) model is employed to represent a class of multivariable nonlinear dynamic systems with time-varying delay. It is known that the disadvantages of robust control for the NARMA model are as follows: 1) suitable control parameters for larger time delay are more sensitive to achieving desirable performance; 2) it only deals with bounded uncertainty; and 3) the nominal NARMA model must be learned in advance. Due to the dynamic feature of the NARMA model, a recurrent neural network (RNN) is online applied to learn it. However, the system performance becomes deteriorated due to the poor learning of the larger variation of system vector functions. In this situation, a simple network is employed to compensate the upper bound of the residue caused by the linear parameterization of the approximation error of RNN. An e -modification learning law with a projection for weight matrix is applied to guarantee its boundedness without persistent excitation. Under suitable conditions, the semiglobally ultimately bounded tracking with the boundedness of estimated weight matrix is obtained by the proposed RNN-based multivariable adaptive control. Finally, simulations are presented to verify the effectiveness and robustness of the proposed control.
Directory of Open Access Journals (Sweden)
Sergio Parini
2009-01-01
Full Text Available In this paper, we present, with particular focus on the adopted processing and identification chain and protocol-related solutions, a whole self-paced brain-computer interface system based on a 4-class steady-state visual evoked potentials (SSVEPs paradigm. The proposed system incorporates an automated spatial filtering technique centred on the common spatial patterns (CSPs method, an autoscaled and effective signal features extraction which is used for providing an unsupervised biofeedback, and a robust self-paced classifier based on the discriminant analysis theory. The adopted operating protocol is structured in a screening, training, and testing phase aimed at collecting user-specific information regarding best stimulation frequencies, optimal sources identification, and overall system processing chain calibration in only a few minutes. The system, validated on 11 healthy/pathologic subjects, has proven to be reliable in terms of achievable communication speed (up to 70 bit/min and very robust to false positive identifications.
Effect of interaction strength on robustness of controlling edge dynamics in complex networks
Pang, Shao-Peng; Hao, Fei
2018-05-01
Robustness plays a critical role in the controllability of complex networks to withstand failures and perturbations. Recent advances in the edge controllability show that the interaction strength among edges plays a more important role than network structure. Therefore, we focus on the effect of interaction strength on the robustness of edge controllability. Using three categories of all edges to quantify the robustness, we develop a universal framework to evaluate and analyze the robustness in complex networks with arbitrary structures and interaction strengths. Applying our framework to a large number of model and real-world networks, we find that the interaction strength is a dominant factor for the robustness in undirected networks. Meanwhile, the strongest robustness and the optimal edge controllability in undirected networks can be achieved simultaneously. Different from the case of undirected networks, the robustness in directed networks is determined jointly by the interaction strength and the network's degree distribution. Moreover, a stronger robustness is usually associated with a larger number of driver nodes required to maintain full control in directed networks. This prompts us to provide an optimization method by adjusting the interaction strength to optimize the robustness of edge controllability.
Directory of Open Access Journals (Sweden)
S. Alonso-Quesada
2010-01-01
Full Text Available This paper presents a strategy for designing a robust discrete-time adaptive controller for stabilizing linear time-invariant (LTI continuous-time dynamic systems. Such systems may be unstable and noninversely stable in the worst case. A reduced-order model is considered to design the adaptive controller. The control design is based on the discretization of the system with the use of a multirate sampling device with fast-sampled control signal. A suitable on-line adaptation of the multirate gains guarantees the stability of the inverse of the discretized estimated model, which is used to parameterize the adaptive controller. A dead zone is included in the parameters estimation algorithm for robustness purposes under the presence of unmodeled dynamics in the controlled dynamic system. The adaptive controller guarantees the boundedness of the system measured signal for all time. Some examples illustrate the efficacy of this control strategy.
Quantum critical dynamics for a prototype class of insulating antiferromagnets
Wu, Jianda; Yang, Wang; Wu, Congjun; Si, Qimiao
2018-06-01
Quantum criticality is a fundamental organizing principle for studying strongly correlated systems. Nevertheless, understanding quantum critical dynamics at nonzero temperatures is a major challenge of condensed-matter physics due to the intricate interplay between quantum and thermal fluctuations. The recent experiments with the quantum spin dimer material TlCuCl3 provide an unprecedented opportunity to test the theories of quantum criticality. We investigate the nonzero-temperature quantum critical spin dynamics by employing an effective O (N ) field theory. The on-shell mass and the damping rate of quantum critical spin excitations as functions of temperature are calculated based on the renormalized coupling strength and are in excellent agreement with experiment observations. Their T lnT dependence is predicted to be dominant at very low temperatures, which will be tested in future experiments. Our work provides confidence that quantum criticality as a theoretical framework, which is being considered in so many different contexts of condensed-matter physics and beyond, is indeed grounded in materials and experiments accurately. It is also expected to motivate further experimental investigations on the applicability of the field theory to related quantum critical systems.
Koponen, Ismo T.; Kokkonen, Tommi; Nousiainen, Maiji
2017-01-01
We discuss here conceptual change and the formation of robust learning outcomes from the viewpoint of complex dynamic systems (CDS). The CDS view considers students' conceptions as context dependent and multifaceted structures which depend on the context of their application. In the CDS view the conceptual patterns (i.e. intuitive conceptions…
Modeling self-consistent multi-class dynamic traffic flow
Cho, Hsun-Jung; Lo, Shih-Ching
2002-09-01
In this study, we present a systematic self-consistent multiclass multilane traffic model derived from the vehicular Boltzmann equation and the traffic dispersion model. The multilane domain is considered as a two-dimensional space and the interaction among vehicles in the domain is described by a dispersion model. The reason we consider a multilane domain as a two-dimensional space is that the driving behavior of road users may not be restricted by lanes, especially motorcyclists. The dispersion model, which is a nonlinear Poisson equation, is derived from the car-following theory and the equilibrium assumption. Under the concept that all kinds of users share the finite section, the density is distributed on a road by the dispersion model. In addition, the dynamic evolution of the traffic flow is determined by the systematic gas-kinetic model derived from the Boltzmann equation. Multiplying Boltzmann equation by the zeroth, first- and second-order moment functions, integrating both side of the equation and using chain rules, we can derive continuity, motion and variance equation, respectively. However, the second-order moment function, which is the square of the individual velocity, is employed by previous researches does not have physical meaning in traffic flow. Although the second-order expansion results in the velocity variance equation, additional terms may be generated. The velocity variance equation we propose is derived from multiplying Boltzmann equation by the individual velocity variance. It modifies the previous model and presents a new gas-kinetic traffic flow model. By coupling the gas-kinetic model and the dispersion model, a self-consistent system is presented.
Dynamic analysis of a hepatitis B model with three-age-classes
Zhang, Suxia; Zhou, Yicang
2014-07-01
Based on the fact that the likelihood of becoming chronically infected is dependent on age at primary infection Kane (1995) [2], Edmunds et al. (1993) [3], Medley et al. (2001) [4], and Ganem and Prince (2004) [6], we formulate a hepatitis B transmission model with three age classes. The reproduction number, R0 is defined and the dynamical behavior of the model is analyzed. It is proved that the disease-free equilibrium is globally stable if R01. The unique endemic equilibrium and its global stability is obtained in a special case. Simulations are also conducted to compare the dynamical behavior of the model with and without age classes.
Robustness of Visual Place Cells in Dynamic Indoor and Outdoor Environment
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C. Giovannangeli
2006-06-01
Full Text Available In this paper, a model of visual place cells (PCs based on precise neurobiological data is presented. The robustness of the model in real indoor and outdoor environments is tested. Results show that the interplay between neurobiological modelling and robotic experiments can promote the understanding of the neural structures and the achievement of robust robot navigation algorithms. Short Term Memory (STM, soft competition and sparse coding are important for both landmark identification and computation of PC activities. The extension of the paradigm to outdoor environments has confirmed the robustness of the vision-based model and pointed to improvements in order to further foster its performance.
International Nuclear Information System (INIS)
Smith, Kyle K. G.; Poulsen, Jens Aage; Nyman, Gunnar; Rossky, Peter J.
2015-01-01
We develop two classes of quasi-classical dynamics that are shown to conserve the initial quantum ensemble when used in combination with the Feynman-Kleinert approximation of the density operator. These dynamics are used to improve the Feynman-Kleinert implementation of the classical Wigner approximation for the evaluation of quantum time correlation functions known as Feynman-Kleinert linearized path-integral. As shown, both classes of dynamics are able to recover the exact classical and high temperature limits of the quantum time correlation function, while a subset is able to recover the exact harmonic limit. A comparison of the approximate quantum time correlation functions obtained from both classes of dynamics is made with the exact results for the challenging model problems of the quartic and double-well potentials. It is found that these dynamics provide a great improvement over the classical Wigner approximation, in which purely classical dynamics are used. In a special case, our first method becomes identical to centroid molecular dynamics
Sieberling, S.; Chu, Q.P.; Mulder, J.A.
2010-01-01
This paper presents a flight control strategy based on nonlinear dynamic inversion. The approach presented, called incremental nonlinear dynamic inversion, uses properties of general mechanical systems and nonlinear dynamic inversion by feeding back angular accelerations. Theoretically, feedback of
On existence of control for a class of uncertain dynamical systems ...
African Journals Online (AJOL)
In this paper we prove the existence of control for input bounded uncertain dynamical system, modeled on Euclidean spaces of dimensions n and m. We apply the Conjugate Gradient Method (C.G.M) in generating algorithms to compute control signals for the class of problem under consideration. Keywords: Control ...
Teunter, Ruud H.; Haneveld, Willem K. Klein
2008-01-01
We study inventory systems with two demand classes (critical and non-critical), Poisson demand and backordering. We analyze dynamic rationing strategies where the number of items reserved for critical demand depends on the remaining time until the next order arrives. Different from results in the
Pérez Aparicio, Jesús; Toledano Medina, M Angeles; Lafuente Rosales, Victoria
2007-07-09
Free-choice profile (FCP), developed in the 1980s, is a sensory analysis method that can be carried out by untrained panels. The participants need only to be able to use a scale and be consumers of the product under evaluation. The data are analysed by sophisticated statistical methodologies like Generalized Procrustean Analysis (GPA) or STATIS. To facilitate a wider use of the free-choice profiling procedure, different authors have advocated simpler methods based on principal components analysis (PCA) of merged data sets. The purpose of this work was to apply another easy procedure to this type of data by means of a robust PCA. The most important characteristic of the proposed method is that quality responsible managers could use this methodology without any scale evaluation. Only the free terms generated by the assessors are necessary to apply the script, thus avoiding the error associated with scale utilization by inexpert assessors. Also, it is possible to use the application with missing data and with differences in the assessors' attendance at sessions. An example was performed to generate the descriptors from different orange juice types. The results were compared with the STATIS method and with the PCA on the merged data sets. The samples evaluated were fresh orange juices with differences in storage days and pasteurized, concentrated and orange nectar drinks from different brands. Eighteen assessors with a low-level training program were used in a six-session free-choice profile framework. The results proved that this script could be of use in marketing decisions and product quality program development.
Gurzadyan, V. G.; Kocharyan, A. A.
2015-07-01
The recently developed method (Paper 1) enabling one to investigate the evolution of dynamical systems with an accuracy not dependent on time is developed further. The classes of dynamical systems which can be studied by that method are much extended, now including systems that are: (1) non-Hamiltonian, conservative; (2) Hamiltonian with time-dependent perturbation; (3) non-conservative (with dissipation). These systems cover various types of N-body gravitating systems of astrophysical and cosmological interest, such as the orbital evolution of planets, minor planets, artificial satellites due to tidal, non-tidal perturbations and thermal thrust, evolving close binary stellar systems, and the dynamics of accretion disks.
Directory of Open Access Journals (Sweden)
Kaibo Shi
2014-01-01
Full Text Available This paper is concerned with the problem of delay-dependent robust stability analysis for a class of uncertain neutral type Lur’e systems with mixed time-varying delays. The system has not only time-varying uncertainties and sector-bounded nonlinearity, but also discrete and distributed delays, which has never been discussed in the previous literature. Firstly, by employing one effective mathematical technique, some less conservative delay-dependent stability results are established without employing the bounding technique and the mode transformation approach. Secondly, by constructing an appropriate new type of Lyapunov-Krasovskii functional with triple terms, improved delay-dependent stability criteria in terms of linear matrix inequalities (LMIs derived in this paper are much brief and valid. Furthermore, both nonlinearities located in finite sector and infinite one have been also fully taken into account. Finally, three numerical examples are presented to illustrate lesser conservatism and the advantage of the proposed main results.
Directory of Open Access Journals (Sweden)
Hiwa Farughi
2016-05-01
Full Text Available In this paper, robust optimization of a bi-objective mathematical model in a dynamic cell formation problem considering labor utilization with uncertain data is carried out. The robust approach is used to reduce the effects of fluctuations of the uncertain parameters with regards to all the possible future scenarios. In this research, cost parameters of the cell formation and demand fluctuations are subject to uncertainty and a mixed-integer programming (MIP model is developed to formulate the related robust dynamic cell formation problem. Then the problem is transformed into a bi-objective linear one. The first objective function seeks to minimize relevant costs of the problem including machine procurement and relocation costs, machine variable cost, inter-cell movement and intra-cell movement costs, overtime cost and labor shifting cost between cells, machine maintenance cost, inventory, holding part cost. The second objective function seeks to minimize total man-hour deviations between cells or indeed labor utilization of the modeled.
International Nuclear Information System (INIS)
Logsdon, W.A.; Begley, J.A.; Gottshall, C.L.
1978-03-01
The ASME Boiler and Pressure Vessel Code, Section III, Article G-2000, requires that dynamic fracture toughness data be developed for materials with specified minimum yield strengths greater than 50 ksi to provide verification and utilization of the ASME specified minimum reference toughness K/sub IR/ curve. In order to qualify ASME SA508 Class 2a and ASME SA533 Grade A Class 2 pressure vessel steels (minimum yield strengths equal 65 kip/in. 2 and 70 kip/in. 2 , respectively) per this requirement, dynamic fracture toughness tests were performed on these materials. All dynamic fracture toughness values of SA508 Class 2a base and HAZ material, SA533 Grade A Class 2 base and HAZ material, and applicable weld metals exceeded the ASME specified minimum reference toughness K/sub IR/ curve
Luo, Jianjun; Wei, Caisheng; Dai, Honghua; Yuan, Jianping
2018-03-01
This paper focuses on robust adaptive control for a class of uncertain nonlinear systems subject to input saturation and external disturbance with guaranteed predefined tracking performance. To reduce the limitations of classical predefined performance control method in the presence of unknown initial tracking errors, a novel predefined performance function with time-varying design parameters is first proposed. Then, aiming at reducing the complexity of nonlinear approximations, only two least-square-support-vector-machine-based (LS-SVM-based) approximators with two design parameters are required through norm form transformation of the original system. Further, a novel LS-SVM-based adaptive constrained control scheme is developed under the time-vary predefined performance using backstepping technique. Wherein, to avoid the tedious analysis and repeated differentiations of virtual control laws in the backstepping technique, a simple and robust finite-time-convergent differentiator is devised to only extract its first-order derivative at each step in the presence of external disturbance. In this sense, the inherent demerit of backstepping technique-;explosion of terms; brought by the recursive virtual controller design is conquered. Moreover, an auxiliary system is designed to compensate the control saturation. Finally, three groups of numerical simulations are employed to validate the effectiveness of the newly developed differentiator and the proposed adaptive constrained control scheme.
DEFF Research Database (Denmark)
Ghoreishi, Maryam
2018-01-01
Many models within the field of optimal dynamic pricing and lot-sizing models for deteriorating items assume everything is deterministic and develop a differential equation as the core of analysis. Two prominent examples are the papers by Rajan et al. (Manag Sci 38:240–262, 1992) and Abad (Manag......, we will try to expose the model by Abad (1996) and Rajan et al. (1992) to stochastic inputs; however, designing these stochastic inputs such that they as closely as possible are aligned with the assumptions of those papers. We do our investigation through a numerical test where we test the robustness...... of the numerical results reported in Rajan et al. (1992) and Abad (1996) in a simulation model. Our numerical results seem to confirm that the results stated in these papers are indeed robust when being imposed to stochastic inputs....
Belmiloudi, Aziz
2006-01-01
We formulate and study robust control problems for a two-dimensional time-dependent Ginzburg-Landau model with Robin boundary conditions on phase-field parameter, which describes the phase transitions taking place in superconductor films with variable thickness. The objective of such study is to control the motion of vortices in the superconductor films by taking into account the influence of noises in data. Firstly, we introduce the perturbation problem of the nonlinear ...
Motion robust high resolution 3D free-breathing pulmonary MRI using dynamic 3D image self-navigator.
Jiang, Wenwen; Ong, Frank; Johnson, Kevin M; Nagle, Scott K; Hope, Thomas A; Lustig, Michael; Larson, Peder E Z
2018-06-01
To achieve motion robust high resolution 3D free-breathing pulmonary MRI utilizing a novel dynamic 3D image navigator derived directly from imaging data. Five-minute free-breathing scans were acquired with a 3D ultrashort echo time (UTE) sequence with 1.25 mm isotropic resolution. From this data, dynamic 3D self-navigating images were reconstructed under locally low rank (LLR) constraints and used for motion compensation with one of two methods: a soft-gating technique to penalize the respiratory motion induced data inconsistency, and a respiratory motion-resolved technique to provide images of all respiratory motion states. Respiratory motion estimation derived from the proposed dynamic 3D self-navigator of 7.5 mm isotropic reconstruction resolution and a temporal resolution of 300 ms was successful for estimating complex respiratory motion patterns. This estimation improved image quality compared to respiratory belt and DC-based navigators. Respiratory motion compensation with soft-gating and respiratory motion-resolved techniques provided good image quality from highly undersampled data in volunteers and clinical patients. An optimized 3D UTE sequence combined with the proposed reconstruction methods can provide high-resolution motion robust pulmonary MRI. Feasibility was shown in patients who had irregular breathing patterns in which our approach could depict clinically relevant pulmonary pathologies. Magn Reson Med 79:2954-2967, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.
Model predictive control of hybrid systems : stability and robustness
Lazar, M.
2006-01-01
This thesis considers the stabilization and the robust stabilization of certain classes of hybrid systems using model predictive control. Hybrid systems represent a broad class of dynamical systems in which discrete behavior (usually described by a finite state machine) and continuous behavior
Robust control of drag and lateral dynamic response for road vehicles exposed to cross-wind gusts
Pfeiffer, Jens; King, Rudibert
2018-03-01
A robust closed-loop active flow control strategy for road vehicles under unsteady cross-wind conditions is presented. It is designed based on black-box models identified from experimental data for a 3D bluff body equipped with Coanda actuators along the rear edges. The controller adjusts the blowing rates of the actuators individually, achieving a drag reduction of about 15% while simultaneously improving cross-wind sensitivity. Hereby, the lateral vehicle dynamics and driver behavior are taken into account and replicated in the wind tunnel via a novel model support system. The effectiveness of the control strategy is demonstrated via cross-wind gust experiments.
Robust Adaptive Dynamic Programming of Two-Player Zero-Sum Games for Continuous-Time Linear Systems.
Fu, Yue; Fu, Jun; Chai, Tianyou
2015-12-01
In this brief, an online robust adaptive dynamic programming algorithm is proposed for two-player zero-sum games of continuous-time unknown linear systems with matched uncertainties, which are functions of system outputs and states of a completely unknown exosystem. The online algorithm is developed using the policy iteration (PI) scheme with only one iteration loop. A new analytical method is proposed for convergence proof of the PI scheme. The sufficient conditions are given to guarantee globally asymptotic stability and suboptimal property of the closed-loop system. Simulation studies are conducted to illustrate the effectiveness of the proposed method.
Directory of Open Access Journals (Sweden)
Xubin Ping
2015-01-01
Full Text Available For the quasi-linear parameter varying (quasi-LPV system with bounded disturbance, a synthesis approach of dynamic output feedback robust model predictive control (OFRMPC is investigated. The estimation error set is represented by a zonotope and refreshed by the zonotopic set-membership estimation method. By properly refreshing the estimation error set online, the bounds of true state at the next sampling time can be obtained. Furthermore, the feasibility of the main optimization problem at the next sampling time can be determined at the current time. A numerical example is given to illustrate the effectiveness of the approach.
Miao, Yinglong; Yi, Zheng; Glass, Dennis C; Hong, Liang; Tyagi, Madhusudan; Baudry, Jerome; Jain, Nitin; Smith, Jeremy C
2012-12-05
The temperature dependences of the nanosecond dynamics of different chemical classes of amino acid residue have been analyzed by combining elastic incoherent neutron scattering experiments with molecular dynamics simulations on cytochrome P450cam. At T = 100-160 K, anharmonic motion in hydrophobic and aromatic residues is activated, whereas hydrophilic residue motions are suppressed because of hydrogen-bonding interactions. In contrast, at T = 180-220 K, water-activated jumps of hydrophilic side chains, which are strongly coupled to the relaxation rates of the hydrogen bonds they form with hydration water, become apparent. Thus, with increasing temperature, first the hydrophobic core awakens, followed by the hydrophilic surface.
Some fundamental considerations on the dynamics of class B laser threshold crossing
Puccioni, G. P.; Wang, T.; Lippi, G. L.
2016-01-01
With the help of a simple rate equation model, we analyze the intrinsic dynamics of threshold crossing for Class B lasers. A thorough discussion of the characteristics and the limitations of this very commonly employed model, which provides excellent qualitative predictions on the laser behaviour, is offered. Approximate solutions for the population inversion and for the field intensity, up to the point where the latter reaches macroscopic levels, are found and discussed, together with the as...
Robust Structured Control Design via LMI Optimization
DEFF Research Database (Denmark)
Adegas, Fabiano Daher; Stoustrup, Jakob
2011-01-01
This paper presents a new procedure for discrete-time robust structured control design. Parameter-dependent nonconvex conditions for stabilizable and induced L2-norm performance controllers are solved by an iterative linear matrix inequalities (LMI) optimization. A wide class of controller...... structures including decentralized of any order, ﬁxed-order dynamic output feedback, static output feedback can be designed robust to polytopic uncertainties. Stability is proven by a parameter-dependent Lyapunov function. Numerical examples on robust stability margins shows that the proposed procedure can...
RECOVERY ACT - Robust Optimization for Connectivity and Flows in Dynamic Complex Networks
Energy Technology Data Exchange (ETDEWEB)
Balasundaram, Balabhaskar [Oklahoma State Univ., Stillwater, OK (United States); Butenko, Sergiy [Texas A & M Univ., College Station, TX (United States); Boginski, Vladimir [Univ. of Florida, Gainesville, FL (United States); Uryasev, Stan [Univ. of Florida, Gainesville, FL (United States)
2013-12-25
The goal of this project was to study robust connectivity and flow patterns of complex multi-scale systems modeled as networks. Networks provide effective ways to study global, system level properties, as well as local, multi-scale interactions at a component level. Numerous applications from power systems, telecommunication, transportation, biology, social science, and other areas have benefited from novel network-based models and their analysis. Modeling and optimization techniques that employ appropriate measures of risk for identifying robust clusters and resilient network designs in networks subject to uncertain failures were investigated in this collaborative multi-university project. In many practical situations one has to deal with uncertainties associated with possible failures of network components, thereby affecting the overall efficiency and performance of the system (e.g., every node/connection has a probability of partial or complete failure). Some extreme examples include power grid component failures, airline hub failures due to weather, or freeway closures due to emergencies. These are also situations in which people, materials, or other resources need to be managed efficiently. Important practical examples include rerouting flow through power grids, adjusting flight plans, and identifying routes for emergency services and supplies, in the event network elements fail unexpectedly. Solutions that are robust under uncertainty, in addition to being economically efficient, are needed. This project has led to the development of novel models and methodologies that can tackle the optimization problems arising in such situations. A number of new concepts, which have not been previously applied in this setting, were investigated in the framework of the project. The results can potentially help decision-makers to better control and identify robust or risk-averse decisions in such situations. Formulations and optimal solutions of the considered problems need
A Study on Efficient Robust Speech Recognition with Stochastic Dynamic Time Warping
孫, 喜浩
2014-01-01
In recent years, great progress has been made in automatic speech recognition (ASR) system. The hidden Markov model (HMM) and dynamic time warping (DTW) are the two main algorithms which have been widely applied to ASR system. Although, HMM technique achieves higher recognition accuracy in clear speech environment and noisy environment. It needs large-set of words and realizes the algorithm more complexly.Thus, more and more researchers have focused on DTW-based ASR system.Dynamic time warpin...
Yan, Zheng; Wang, Jun
2014-03-01
This paper presents a neural network approach to robust model predictive control (MPC) for constrained discrete-time nonlinear systems with unmodeled dynamics affected by bounded uncertainties. The exact nonlinear model of underlying process is not precisely known, but a partially known nominal model is available. This partially known nonlinear model is first decomposed to an affine term plus an unknown high-order term via Jacobian linearization. The linearization residue combined with unmodeled dynamics is then modeled using an extreme learning machine via supervised learning. The minimax methodology is exploited to deal with bounded uncertainties. The minimax optimization problem is reformulated as a convex minimization problem and is iteratively solved by a two-layer recurrent neural network. The proposed neurodynamic approach to nonlinear MPC improves the computational efficiency and sheds a light for real-time implementability of MPC technology. Simulation results are provided to substantiate the effectiveness and characteristics of the proposed approach.
Lu, Tao
2016-01-01
The gene regulation network (GRN) evaluates the interactions between genes and look for models to describe the gene expression behavior. These models have many applications; for instance, by characterizing the gene expression mechanisms that cause certain disorders, it would be possible to target those genes to block the progress of the disease. Many biological processes are driven by nonlinear dynamic GRN. In this article, we propose a nonparametric differential equation (ODE) to model the nonlinear dynamic GRN. Specially, we address following questions simultaneously: (i) extract information from noisy time course gene expression data; (ii) model the nonlinear ODE through a nonparametric smoothing function; (iii) identify the important regulatory gene(s) through a group smoothly clipped absolute deviation (SCAD) approach; (iv) test the robustness of the model against possible shortening of experimental duration. We illustrate the usefulness of the model and associated statistical methods through a simulation and a real application examples.
Yang, Xinxin; Ge, Shuzhi Sam; He, Wei
2018-04-01
In this paper, both the closed-form dynamics and adaptive robust tracking control of a space robot with two-link flexible manipulators under unknown disturbances are developed. The dynamic model of the system is described with assumed modes approach and Lagrangian method. The flexible manipulators are represented as Euler-Bernoulli beams. Based on singular perturbation technique, the displacements/joint angles and flexible modes are modelled as slow and fast variables, respectively. A sliding mode control is designed for trajectories tracking of the slow subsystem under unknown but bounded disturbances, and an adaptive sliding mode control is derived for slow subsystem under unknown slowly time-varying disturbances. An optimal linear quadratic regulator method is proposed for the fast subsystem to damp out the vibrations of the flexible manipulators. Theoretical analysis validates the stability of the proposed composite controller. Numerical simulation results demonstrate the performance of the closed-loop flexible space robot system.
Attractive ellipsoids in robust control
Poznyak, Alexander; Azhmyakov, Vadim
2014-01-01
This monograph introduces a newly developed robust-control design technique for a wide class of continuous-time dynamical systems called the “attractive ellipsoid method.” Along with a coherent introduction to the proposed control design and related topics, the monograph studies nonlinear affine control systems in the presence of uncertainty and presents a constructive and easily implementable control strategy that guarantees certain stability properties. The authors discuss linear-style feedback control synthesis in the context of the above-mentioned systems. The development and physical implementation of high-performance robust-feedback controllers that work in the absence of complete information is addressed, with numerous examples to illustrate how to apply the attractive ellipsoid method to mechanical and electromechanical systems. While theorems are proved systematically, the emphasis is on understanding and applying the theory to real-world situations. Attractive Ellipsoids in Robust Control will a...
Che-Castaldo, Christian; Jenouvrier, Stephanie; Youngflesh, Casey; Shoemaker, Kevin T; Humphries, Grant; McDowall, Philip; Landrum, Laura; Holland, Marika M; Li, Yun; Ji, Rubao; Lynch, Heather J
2017-10-10
Colonially-breeding seabirds have long served as indicator species for the health of the oceans on which they depend. Abundance and breeding data are repeatedly collected at fixed study sites in the hopes that changes in abundance and productivity may be useful for adaptive management of marine resources, but their suitability for this purpose is often unknown. To address this, we fit a Bayesian population dynamics model that includes process and observation error to all known Adélie penguin abundance data (1982-2015) in the Antarctic, covering >95% of their population globally. We find that process error exceeds observation error in this system, and that continent-wide "year effects" strongly influence population growth rates. Our findings have important implications for the use of Adélie penguins in Southern Ocean feedback management, and suggest that aggregating abundance across space provides the fastest reliable signal of true population change for species whose dynamics are driven by stochastic processes.Adélie penguins are a key Antarctic indicator species, but data patchiness has challenged efforts to link population dynamics to key drivers. Che-Castaldo et al. resolve this issue using a pan-Antarctic Bayesian model to infer missing data, and show that spatial aggregation leads to more robust inference regarding dynamics.
A Multi-Pathfinder for Developing Adaptive Robust Policies in System Dynamics
Hamarat, C.; Pruyt, E.; Loonen, E.T.
2013-01-01
Adaptivity is essential for dynamically complex and uncertain systems. Adaptive policymaking is an approach to design policies that can be adapted over time to how the future unfolds. It is crucial for adaptive policymaking to specify under what conditions and how to adapt the policy. The
Accurate and Robust Numerical Methods for the Dynamic Portfolio Management Problem
F. Cong (Fei); C.W. Oosterlee (Cornelis)
2017-01-01
textabstractThis paper enhances a well-known dynamic portfolio management algorithm, the BGSS algorithm, proposed by Brandt et al. (Review of Financial Studies, 18(3):831–873, 2005). We equip this algorithm with the components from a recently developed method, the Stochastic Grid Bundling Method
Accurate and Robust Numerical Methods for the Dynamic Portfolio Management Problem
Cong, F.; Oosterlee, C.W.
2016-01-01
This paper enhances a well-known dynamic portfolio management algorithm, the BGSS algorithm, proposed by Brandt et al. (Review of Financial Studies, 18(3):831–873, 2005). We equip this algorithm with the components from a recently developed method, the Stochastic Grid Bundling Method (SGBM), for
Accurate and Robust Numerical Methods for the Dynamic Portfolio Management Problem
Cong, F.; Oosterlee, C.W.
2016-01-01
This paper enhances a well-known dynamic portfolio management algorithm, the BGSS algorithm, proposed by Brandt et al. (Review of Financial Studies, 18(3):831–873, 2005). We equip this algorithm with the components from a recently developed method, the Stochastic Grid Bundling Method (SGBM), for
Chien, Yi-Hsing; Wang, Wei-Yen; Leu, Yih-Guang; Lee, Tsu-Tian
2011-04-01
This paper proposes a novel method of online modeling and control via the Takagi-Sugeno (T-S) fuzzy-neural model for a class of uncertain nonlinear systems with some kinds of outputs. Although studies about adaptive T-S fuzzy-neural controllers have been made on some nonaffine nonlinear systems, little is known about the more complicated uncertain nonlinear systems. Because the nonlinear functions of the systems are uncertain, traditional T-S fuzzy control methods can model and control them only with great difficulty, if at all. Instead of modeling these uncertain functions directly, we propose that a T-S fuzzy-neural model approximates a so-called virtual linearized system (VLS) of the system, which includes modeling errors and external disturbances. We also propose an online identification algorithm for the VLS and put significant emphasis on robust tracking controller design using an adaptive scheme for the uncertain systems. Moreover, the stability of the closed-loop systems is proven by using strictly positive real Lyapunov theory. The proposed overall scheme guarantees that the outputs of the closed-loop systems asymptotically track the desired output trajectories. To illustrate the effectiveness and applicability of the proposed method, simulation results are given in this paper.
Dynamical systems with first- and second-class constraints. II. Local-symmetry transformations
International Nuclear Information System (INIS)
Chitaia, N.P.; Gogilidze, S.A.; Surovtsev, Y.S.
1997-01-01
In the framework of the generalized Hamiltonian formalism by Dirac, local symmetries of dynamical systems with first- and second-class constraints are investigated. The method of constructing the generator of local-symmetry transformations is presented both for theories with an algebra of constraints of a special form (a majority of the physically interesting theories) and in the general case without restrictions on the algebra of constraints. It is proven that second-class constraints do not contribute to the transformation law of the local symmetry entirely stipulated by all the first-class constraints. A mechanism of the occurrence of higher derivatives of coordinates and group parameters in the symmetry transformation law in Noether close-quote s second theorem is elucidated. In the latter case it is shown that the obtained transformations of symmetry are canonical in the extended (by Ostrogradsky) phase space. It is thereby shown that in the general case the degeneracy of theories with first- and second-class constraints is due to their invariance under local-symmetry transformations. copyright 1997 The American Physical Society
International Nuclear Information System (INIS)
Han, Sung Hyun
1993-01-01
This paper proposes a new approach to the design of multivariable control schemes for assembly robot manipulator to achieve accuracy trajectory tracking by joint angles. The proposed control scheme consists of a multivariable feedforward controller and a feedback controller. In this control scheme, the feedback controller is proportional integral-derivative type and is designed to achieve the pole placement. The feedforward controller is the inverse of the linealized model of robot manipulator dynamics. The feedback controller ensures that each joint tracks any reference trajectory. The proposed robot controller scheme has a computationally efficient schemes for either offline gain scheduling or online gain computation to account for variations in the linealized robot dynamic model due to changes in operating point. The simulation results demonstrate that the proposed control schemesperporms remarkably well for parameter uncertainties and load variations. (Author)
Robust handling of dynamics and multiple failures in a diagnostic event analyzer
International Nuclear Information System (INIS)
Finch, F.E.; Kramer, M.A.
1991-01-01
MIDAS diagnoses malfunctions in continuous chemical and refinery processes using a plant-independent strategy based on qualitative and quantitative process models. MIDAS specifically addresses problems not treated in past systems, including: process dynamics with control system responses, multiple faults and induced failures, and out-of-order and false alarms. This paper discusses both the structure of the process models and the diagnostic reasoning strategies employed by MIDAS
How Robust is Your System Resilience?
Homayounfar, M.; Muneepeerakul, R.
2017-12-01
Robustness and resilience are concepts in system thinking that have grown in importance and popularity. For many complex social-ecological systems, however, robustness and resilience are difficult to quantify and the connections and trade-offs between them difficult to study. Most studies have either focused on qualitative approaches to discuss their connections or considered only one of them under particular classes of disturbances. In this study, we present an analytical framework to address the linkage between robustness and resilience more systematically. Our analysis is based on a stylized dynamical model that operationalizes a widely used concept framework for social-ecological systems. The model enables us to rigorously define robustness and resilience and consequently investigate their connections. The results reveal the tradeoffs among performance, robustness, and resilience. They also show how the nature of the such tradeoffs varies with the choices of certain policies (e.g., taxation and investment in public infrastructure), internal stresses and external disturbances.
Identification of the dynamic operating envelope of HCCI engines using class imbalance learning.
Janakiraman, Vijay Manikandan; Nguyen, XuanLong; Sterniak, Jeff; Assanis, Dennis
2015-01-01
Homogeneous charge compression ignition (HCCI) is a futuristic automotive engine technology that can significantly improve fuel economy and reduce emissions. HCCI engine operation is constrained by combustion instabilities, such as knock, ringing, misfires, high-variability combustion, and so on, and it becomes important to identify the operating envelope defined by these constraints for use in engine diagnostics and controller design. HCCI combustion is dominated by complex nonlinear dynamics, and a first-principle-based dynamic modeling of the operating envelope becomes intractable. In this paper, a machine learning approach is presented to identify the stable operating envelope of HCCI combustion, by learning directly from the experimental data. Stability is defined using thresholds on combustion features obtained from engine in-cylinder pressure measurements. This paper considers instabilities arising from engine misfire and high-variability combustion. A gasoline HCCI engine is used for generating stable and unstable data observations. Owing to an imbalance in class proportions in the data set, the models are developed both based on resampling the data set (by undersampling and oversampling) and based on a cost-sensitive learning method (by overweighting the minority class relative to the majority class observations). Support vector machines (SVMs) and recently developed extreme learning machines (ELM) are utilized for developing dynamic classifiers. The results compared against linear classification methods show that cost-sensitive nonlinear ELM and SVM classification algorithms are well suited for the problem. However, the SVM envelope model requires about 80% more parameters for an accuracy improvement of 3% compared with the ELM envelope model indicating that ELM models may be computationally suitable for the engine application. The proposed modeling approach shows that HCCI engine misfires and high-variability combustion can be predicted ahead of time
Dynamics, integrability and topology for some classes of Kolmogorov Hamiltonian systems in R+4
Llibre, Jaume; Xiao, Dongmei
2017-02-01
In this paper we first give the sufficient and necessary conditions in order that two classes of polynomial Kolmogorov systems in R+4 are Hamiltonian systems. Then we study the integrability of these Hamiltonian systems in the Liouville sense. Finally, we investigate the global dynamics of the completely integrable Lotka-Volterra Hamiltonian systems in R+4. As an application of the invariant subsets of these systems, we obtain topological classifications of the 3-submanifolds in R+4 defined by the hypersurfaces axy + bzw + cx2 y + dxy2 + ez2 w + fzw2 = h, where a , b , c , d , e , f , w and h are real constants.
On the Dynamic Robustness of a Non-Endoreversible Engine Working in Different Operation Regimes
Directory of Open Access Journals (Sweden)
Florencio Guzman-Aguilar
2011-02-01
Full Text Available In this work, we focused mainly in the analysis of stability of a non-endoreversible Curzon-Ahlborn engine working in an ecological regime. For comparison purposes we also include the Maximum Efficient Power (MEP regime taking into account the engine time delays. When the system’s dynamic stability is compared with its thermodynamics properties (efficiency and power output, we find that the temperature ratio τ = T1/T2 represents a trade-off between stability and energetic properties. When we take the non-endoreversible case, τ can increases to values greater than R (where R is the non-endoreversible parameter but not greater than one. We reformulate an important difference between this case and the other two, Maximum Power (MP and MEP regime, in which τ = R. Finally, we demonstrated that the total time delay does not destabilize the steady state of system. It does not seem to play a role in the dynamic thermodynamic property trade-off.
Wholesale energy market in a smart grid. Dynamic modeling, stability, and robustness
Energy Technology Data Exchange (ETDEWEB)
Kiani Bejestani, Arman
2013-01-24
The recent paradigm shift in the architecture of the smart grid is driven by the need to integrate Renewable Energy Resources (RER), the availability of information through communication networks, and an emerging policy of demand that is intertwined with pricing. A major component of this architecture is the design of electricity markets, which pertains to the optimal scheduling of power generation and reserve requirements. The challenge is to carry out this scheduling with a high level of integration of renewable generation sources, a formidable task due to intermittency and uncertainty. Introducing huge intermittency and uncertainty in the smart grid will demand a dynamic framework for addressing the operation, scheduling and financial settlements in the uncertain environment. The temporal components in scheduling generation are necessary due to increasing penetration of renewable sources, and increasing potential of adjustable demand via Demand Response (DR). The former brings issues of strong intermittency and uncertainty, and the latter brings a feedback structure, where demand can be modulated over a range of time-scales. Both of these components are dictating a new look at market mechanisms, with a controls viewpoint enabling a novel framework for analysis and synthesis. This dissertation provides static and dynamic models that capture the various aspects of electrical power systems, including the dynamics of market participants, the physical and technical constraints of power systems, and the uncertainty of RER. The proposed models shed new light on wholesale electricity market design, allowing an understanding to be gained of how to create markets, which enhance the stability of price profiles, and efficiency of the power systems, in the presence of uncertain demand and intermittent resources. The notion of market equilibrium in the presence of RER and DR is presented. The effects of uncertainties due to forecast errors in RER and variations due to DR on
DEFF Research Database (Denmark)
Di Canio, Giuliano; Larsen, Jørgen Christian; Wörgötter, Florentin
2016-01-01
Robotic systems inspired from humans have always been lightening up the curiosity of engineers and scientists. Of many challenges, human locomotion is a very difficult one where a number of different systems needs to interact in order to generate a correct and balanced pattern. To simulate...... the interaction of these systems, implementations with reflexbased or central pattern generator (CPG)-based controllers have been tested on bipedal robot systems. In this paper we will combine the two controller types, into a controller that works with both reflex and CPG signals. We use a reflex-based neural...... network to generate basic walking patterns of a dynamic bipedal walking robot (DACBOT) and then a CPG-based neural network to ensure robust walking behavior...
Directory of Open Access Journals (Sweden)
Tore Bakka
2012-01-01
Full Text Available The problem of robust ℋ∞ dynamic output feedback control design with pole placement constraints is studied for a linear parameter-varying model of a floating wind turbine. A nonlinear model is obtained and linearized using the FAST software developed for wind turbines. The main contributions of this paper are threefold. Firstly, a family of linear models are represented based on an affine parameter-varying model structure for a wind turbine system. Secondly, the bounded parameter-varying parameters are removed using upper bounded inequalities in the control design process. Thirdly, the control problem is formulated in terms of linear matrix inequalities (LMIs. The simulation results show a comparison between controller design based on a constant linear model and a controller design for the linear parameter-varying model. The results show the effectiveness of our proposed design technique.
Ceyhun Şahin, Fatma; Schiffmann, Jürg
2018-02-01
A single-hole probe was designed to measure steady and periodic flows with high fluctuation amplitudes and with minimal flow intrusion. Because of its high aspect ratio, estimations showed that the probe resonates at a frequency two orders of magnitude lower than the fast response sensor cut-off frequencies. The high fluctuation amplitudes cause a non-linear behavior of the probe and available models are neither adequate for a quantitative estimation of the resonating frequencies nor for predicting the system damping. Instead, a non-linear data correction procedure based on individual transfer functions defined for each harmonic contribution is introduced for pneumatic probes that allows to extend their operating range beyond the resonating frequencies and linear dynamics. This data correction procedure was assessed on a miniature single-hole probe of 0.35 mm inner diameter which was designed to measure flow speed and direction. For the reliable use of such a probe in periodic flows, its frequency response was reproduced with a siren disk, which allows exciting the probe up to 10 kHz with peak-to-peak amplitudes ranging between 20%-170% of the absolute mean pressure. The effect of the probe interior design on the phase lag and amplitude distortion in periodic flow measurements was investigated on probes with similar inner diameters and different lengths or similar aspect ratios (L/D) and different total interior volumes. The results suggest that while the tube length consistently sets the resonance frequency, the internal total volume affects the non-linear dynamic response in terms of varying gain functions. A detailed analysis of the introduced calibration methodology shows that the goodness of the reconstructed data compared to the reference data is above 75% for fundamental frequencies up to twice the probe resonance frequency. The results clearly suggest that the introduced procedure is adequate to capture non-linear pneumatic probe dynamics and to
Romanowicz, B. A.; Jiménez-Pérez, H.; Adourian, S.; Karaoglu, H.; French, S.
2016-12-01
Existing global 3D shear wave velocity models of the earth's mantle generally rely on simple ray theoretical assumptions regarding seismic wave propagation through a heterogeneous medium, and/or consider a limited number of seismic observables, such as surface wave dispersion and/or travel times of body waves (such as P or S) that are well separated on seismograms. While these assumptions are appropriate for resolving long wavelength structure, as evidenced from the good agreement at low degrees between models published in the last 10 years, it is well established that the assumption of ray theory limits the resolution of smaller scale low velocity structures. We recently developed a global radially anisotropic shear wave velocity model (SEMUCB_WM1, French and Romanowicz, 2014, 2015) based on time domain full waveform inversion of 3-component seismograms, including surface waves and overtones down to 60s period, as well as body waveforms down to 30s. At each iteration, the forward wavefield is calculated using the Spectral Element Method (SEM), which ensures the accurate computation of the misfit function. Inversion is performed using a fast converging Gauss-Newton formalism. The use of information from the entire seismogram, weighted according to energy arrivals, provides a unique illumination of the deep mantle, compensating for the uneven distribution of sources and stations. The most striking features of this model are the broad, vertically oriented plume-like conduits that extend from the core-mantle boundary to at least 1000 km depth in the vicinity of some 20 major hotspots located over the large low shear velocity provinces under the Pacific and Africa. We here present the results of various tests aimed at evaluating the robustness of these features. These include starting from a different initial model, to evaluate the effects of non-linearity in the inversion, as well as synthetic tests aimed at evaluating the recovery of plumes located in the middle of
Babaee, Hessam; Choi, Minseok; Sapsis, Themistoklis P.; Karniadakis, George Em
2017-09-01
We develop a new robust methodology for the stochastic Navier-Stokes equations based on the dynamically-orthogonal (DO) and bi-orthogonal (BO) methods [1-3]. Both approaches are variants of a generalized Karhunen-Loève (KL) expansion in which both the stochastic coefficients and the spatial basis evolve according to system dynamics, hence, capturing the low-dimensional structure of the solution. The DO and BO formulations are mathematically equivalent [3], but they exhibit computationally complimentary properties. Specifically, the BO formulation may fail due to crossing of the eigenvalues of the covariance matrix, while both BO and DO become unstable when there is a high condition number of the covariance matrix or zero eigenvalues. To this end, we combine the two methods into a robust hybrid framework and in addition we employ a pseudo-inverse technique to invert the covariance matrix. The robustness of the proposed method stems from addressing the following issues in the DO/BO formulation: (i) eigenvalue crossing: we resolve the issue of eigenvalue crossing in the BO formulation by switching to the DO near eigenvalue crossing using the equivalence theorem and switching back to BO when the distance between eigenvalues is larger than a threshold value; (ii) ill-conditioned covariance matrix: we utilize a pseudo-inverse strategy to invert the covariance matrix; (iii) adaptivity: we utilize an adaptive strategy to add/remove modes to resolve the covariance matrix up to a threshold value. In particular, we introduce a soft-threshold criterion to allow the system to adapt to the newly added/removed mode and therefore avoid repetitive and unnecessary mode addition/removal. When the total variance approaches zero, we show that the DO/BO formulation becomes equivalent to the evolution equation of the Optimally Time-Dependent modes [4]. We demonstrate the capability of the proposed methodology with several numerical examples, namely (i) stochastic Burgers equation: we
Gul, Ahmet; Erman, Burak
2018-03-01
Prediction of peptide binding on specific human leukocyte antigens (HLA) has long been studied with successful results. We herein describe the effects of entropy and dynamics by investigating the binding stabilities of 10 nanopeptides on various HLA Class I alleles using a theoretical model based on molecular dynamics simulations. The fluctuational entropies of the peptides are estimated over a temperature range of 310-460 K. The estimated entropies correlate well with experimental binding affinities of the peptides: peptides that have higher binding affinities have lower entropies compared to non-binders, which have significantly larger entropies. The computation of the entropies is based on a simple model that requires short molecular dynamics trajectories and allows for approximate but rapid determination. The paper draws attention to the long neglected dynamic aspects of peptide binding, and provides a fast computation scheme that allows for rapid scanning of large numbers of peptides on selected HLA antigens, which may be useful in defining the right peptides for personal immunotherapy.
The dynamics of student learning within a high school virtual reality design class
Morales, Teresa M.
This mixed method study investigated knowledge and skill development of high school students in a project-based VR design class, in which 3-D projects were developed within a student-centered, student-directed environment. This investigation focused on student content learning, and problem solving. Additionally the social dynamics of the class and the role of peer mentoring were examined to determine how these factors influenced student behavior and learning. Finally, parent and teachers perceptions of the influence of the class were examined. The participants included freshmen through senior students, parents, teachers and the high school principal. Student interviews and classroom observations were used to collect data from students, while teachers and parents completed surveys. The results of this study suggested that this application of virtual reality (VR) learning environment promoted the development of; meaningful cognitive experiences, creativity, leadership, global socialization, problem solving and a deeper understanding of academic content. Further theoretical implications for 3-D virtual reality technology are exceedingly promising, and warrant additional research and development as an instructional tool for practical use.
Sharma, Natasha; Verma, Atul Kumar; Gupta, Arvind Kumar
2018-05-01
Macroscopic and microscopic long-distance bidirectional transfer depends on connections between entrances and exits of various transport mediums. Persuaded by the associations, we introduce a small system module of Totally Asymmetric Simple Exclusion Process including oppositely directed species of particles moving on two parallel channels with constrained entrances. The dynamical rules which characterize the system obey symmetry between the two species and are identical for both the channels. The model displays a rich steady-state behavior, including symmetry breaking phenomenon. The phase diagram is analyzed theoretically within the mean-field approximation and substantiated with Monte Carlo simulations. Relevant mean-field calculations are also presented. We further compared the phase segregation with those observed in previous works, and it is examined that the structure of phase separation in proposed model is distinguished from earlier ones. Interestingly, for phases with broken symmetry, symmetry with respect to channels has been observed as the distinct particles behave differently while the similar type of particles exhibits the same conduct in the system. For symmetric phases, significant properties including currents and densities in the channels are identical for both types of particles. The effect of symmetry breaking occurrence on the Monte Carlo simulation results has also been examined based on particle density histograms. Finally, phase properties of the system having strong size dependency have been explored based on simulations findings.
Directory of Open Access Journals (Sweden)
Shuhuan Wen
2012-01-01
Full Text Available Recently, there is an emerging trend of addressing “energy efficiency” aspect of wireless communications. It has been shown that cooperating users relay each other's information to improve data rates. The energy is limited in the wireless cellular network, but the mobile users refuse to relay. This paper presents an approach that encourages user cooperation in order to improve the energy efficiency. The game theory is an efficient method to solve such conflicts. We present a cellular framework in which two mobile users, who desire to communicate with a common base station, may cooperate via decode-and-forward relaying. In the case of imperfect information assumption, cooperative Nash dynamic game is used between the two users' cooperation to tackle the decision making problems: whether to cooperate and how to cooperate in wireless networks. The scheme based on “cooperative game theory” can achieve general pareto-optimal performance for cooperative games, and thus, maximize the entire system payoff while maintaining fairness.
SOS based robust H(∞) fuzzy dynamic output feedback control of nonlinear networked control systems.
Chae, Seunghwan; Nguang, Sing Kiong
2014-07-01
In this paper, a methodology for designing a fuzzy dynamic output feedback controller for discrete-time nonlinear networked control systems is presented where the nonlinear plant is modelled by a Takagi-Sugeno fuzzy model and the network-induced delays by a finite state Markov process. The transition probability matrix for the Markov process is allowed to be partially known, providing a more practical consideration of the real world. Furthermore, the fuzzy controller's membership functions and premise variables are not assumed to be the same as the plant's membership functions and premise variables, that is, the proposed approach can handle the case, when the premise of the plant are not measurable or delayed. The membership functions of the plant and the controller are approximated as polynomial functions, then incorporated into the controller design. Sufficient conditions for the existence of the controller are derived in terms of sum of square inequalities, which are then solved by YALMIP. Finally, a numerical example is used to demonstrate the validity of the proposed methodology.
Chen, Longquan
2010-09-01
Superhydrophobic nano-flower surfaces were fabricated using MEMS technology and microwave plasma-enhanced chemical vapor deposition (MPCVD) of carbon nanotubes on silicon micro-post array surfaces. The nano-flower structures can be readily formed within 1-2 min on the micro-post arrays with the spacing ranging from 25 to 30 μm. The petals of the nano-flowers consisted of clusters of multi-wall carbon nanotubes. Patterned nano-flower structures were characterized using various microscopy techniques. After MPCVD, the apparent contact angle (160 ± 0.2°), abbreviated as ACA (defined as the measured angle between the apparent solid surface and the tangent to the liquid-fluid interface), of the nano-flower surfaces increased by 139% compared with that of the silicon micro-post arrays. The measured ACA of the nano-flower surface is consistent with the predicted ACA from a modified Cassie-Baxter equation. A high-speed CCD camera was used to study droplet impact dynamics on various micro/nanostructured surfaces. Both static testing (ACA and sliding angle) and droplet impact dynamics demonstrated that, among seven different micro/nanostructured surfaces, the nano-flower surfaces are the most robust superhydrophobic surfaces. © 2010 IOP Publishing Ltd.
Pan, Leyun; Cheng, Caixia; Haberkorn, Uwe; Dimitrakopoulou-Strauss, Antonia
2017-05-07
A variety of compartment models are used for the quantitative analysis of dynamic positron emission tomography (PET) data. Traditionally, these models use an iterative fitting (IF) method to find the least squares between the measured and calculated values over time, which may encounter some problems such as the overfitting of model parameters and a lack of reproducibility, especially when handling noisy data or error data. In this paper, a machine learning (ML) based kinetic modeling method is introduced, which can fully utilize a historical reference database to build a moderate kinetic model directly dealing with noisy data but not trying to smooth the noise in the image. Also, due to the database, the presented method is capable of automatically adjusting the models using a multi-thread grid parameter searching technique. Furthermore, a candidate competition concept is proposed to combine the advantages of the ML and IF modeling methods, which could find a balance between fitting to historical data and to the unseen target curve. The machine learning based method provides a robust and reproducible solution that is user-independent for VOI-based and pixel-wise quantitative analysis of dynamic PET data.
Chen, Longquan; Xiao, Zhiyong; Chan, Philip C H; Lee, Yi-Kuen
2010-01-01
Superhydrophobic nano-flower surfaces were fabricated using MEMS technology and microwave plasma-enhanced chemical vapor deposition (MPCVD) of carbon nanotubes on silicon micro-post array surfaces. The nano-flower structures can be readily formed within 1-2 min on the micro-post arrays with the spacing ranging from 25 to 30 μm. The petals of the nano-flowers consisted of clusters of multi-wall carbon nanotubes. Patterned nano-flower structures were characterized using various microscopy techniques. After MPCVD, the apparent contact angle (160 ± 0.2°), abbreviated as ACA (defined as the measured angle between the apparent solid surface and the tangent to the liquid-fluid interface), of the nano-flower surfaces increased by 139% compared with that of the silicon micro-post arrays. The measured ACA of the nano-flower surface is consistent with the predicted ACA from a modified Cassie-Baxter equation. A high-speed CCD camera was used to study droplet impact dynamics on various micro/nanostructured surfaces. Both static testing (ACA and sliding angle) and droplet impact dynamics demonstrated that, among seven different micro/nanostructured surfaces, the nano-flower surfaces are the most robust superhydrophobic surfaces. © 2010 IOP Publishing Ltd.
Pan, Leyun; Cheng, Caixia; Haberkorn, Uwe; Dimitrakopoulou-Strauss, Antonia
2017-05-01
A variety of compartment models are used for the quantitative analysis of dynamic positron emission tomography (PET) data. Traditionally, these models use an iterative fitting (IF) method to find the least squares between the measured and calculated values over time, which may encounter some problems such as the overfitting of model parameters and a lack of reproducibility, especially when handling noisy data or error data. In this paper, a machine learning (ML) based kinetic modeling method is introduced, which can fully utilize a historical reference database to build a moderate kinetic model directly dealing with noisy data but not trying to smooth the noise in the image. Also, due to the database, the presented method is capable of automatically adjusting the models using a multi-thread grid parameter searching technique. Furthermore, a candidate competition concept is proposed to combine the advantages of the ML and IF modeling methods, which could find a balance between fitting to historical data and to the unseen target curve. The machine learning based method provides a robust and reproducible solution that is user-independent for VOI-based and pixel-wise quantitative analysis of dynamic PET data.
Oh, W. S.; Yu, D. J.; Davis, T.; Hillis, V.; Waring, T. M.
2017-12-01
One ongoing challenge to socio-hydrology is the problem of generalization: to what extent do common human-water co-evolutions exist across distinct cases and what are underlying mechanisms of these co-evolutions. This problem stems in part from a lack of unifying theories in socio-hydrology, which hinders the explanation and generalization of results between cases in different regions. Theories help an analyst to make assumptions that are necessary to diagnose a specific phenomenon, to explain the general mechanisms of causation, and, thus, to predict future outcomes. To help address the issue, this study introduces two theories that are increasingly used in the fields of sustainability science and social-ecological systems research: robustness-fragility tradeoff (RFTO) and cultural multi-level selection (CMLS). We apply each of these theories to two distinct cases (water management issues in southwest Bangladesh and the Kissimmee River Basin, Florida) and interpret the phenomena of the levee and adaptation effects. CMLS and RFTO focus on complementary aspects of socio-hydrological phenomena. The theory of RFTO, which is mostly about inherent tradeoffs associated with infrastructure improvements, explains how efforts to increase system robustness can generate hidden endogenous risks. CMLS theory, rooted in the broader theory of cultural evolution, concerns how human cultural dynamics can act as an endogenous driver of system change across multiple levels of social organizations. Using the applied examples, we demonstrate that these two theories can provide an effective way to study social-hydrological systems and to overcome the generalization problem. Our work shows that multiple theories can be synthesized to give a richer understanding of diverse socio-hydrological patterns.
Using a Virtual Class to Demonstrate Computer-Mediated Group Dynamics Concepts
Franz, Timothy M.; Vicker, Lauren A.
2010-01-01
We report about an active learning demonstration designed to use a virtual class to present computer-mediated group communication course concepts to show that students can learn about these concepts in a virtual class. We designated 1 class period as a virtual rather than face-to-face class, when class members "attended" virtually using…
Discovery and dynamical characterization of the Amor-class asteroid 2012 XH16
Wlodarczyk, I.; Cernis, K.; Boyle, R. P.; Laugalys, V.
2014-03-01
The near-Earth asteroid belt is continuously replenished with material originally moving in Amor-class orbits. Here, the orbit of the dynamically interesting Amor-class asteroid 2012 XH16 is analysed. This asteroid was discovered with the Vatican Advanced Technology Telescope (VATT) at the Mt Graham International Observatory as part of an ongoing asteroid survey focused on astrometry and photometry. The orbit of the asteroid was computed using 66 observations (57 obtained with VATT and 9 from the Lunar and Planetary Laboratory-Spacewatch II project) to give a = 1.63 au, e = 0.36, i = 3.76°. The absolute magnitude of the asteroid is 22.3 which translates into a diameter in the range 104-231 m, assuming the average albedos of S-type and C-type asteroids, respectively. We have used the current orbit to study the future dynamical evolution of the asteroid under the perturbations of the planets and the Moon, relativistic effects, and the Yarkovsky force. Asteroid 2012 XH16 is locked close to the strong 1:2 mean motion resonance with the Earth. The object shows stable evolution and could survive in near-resonance for a relatively long period of time despite experiencing frequent close encounters with Mars. Moreover, results of our computations show that the asteroid 2012 XH16 can survive in the Amor region at most for about 200-400 Myr. The evolution is highly chaotic with a characteristic Lyapunov time of 245 yr. Jupiter is the main perturber but the effects of Saturn, Mars and the Earth-Moon system are also important. In particular, secular resonances with Saturn are significant.
Directory of Open Access Journals (Sweden)
Sunil Kumar
2013-01-01
Full Text Available Node mobility in mobile ad hoc networks (MANETs causes frequent route breakages and intermittent link stability. In this paper, we introduce a robust routing scheme, known as ad hoc on-demand multipath distance vector with dynamic path update (AOMDV-DPU, for delay-sensitive data transmission over MANET. The proposed scheme improves the AOMDV scheme by incorporating the following features: (i a routing metric based on the combination of minimum hops and received signal strength indicator (RSSI for discovery of reliable routes; (ii a local path update mechanism which strengthens the route, reduces the route breakage frequency, and increases the route longevity; (iii a keep alive mechanism for secondary route maintenance which enables smooth switching between routes and reduces the route discovery frequency; (iv a packet salvaging scheme to improve packet delivery in the event of a route breakage; and (v low HELLO packet overhead. The simulations are carried out in ns-2 for varying node speeds, number of sources, and traffic load conditions. Our AOMDV-DPU scheme achieves significantly higher throughput, lower delay, routing overhead, and route discovery frequency and latency compared to AOMDV. For H.264 compressed video traffic, AOMDV-DPU scheme achieves 3 dB or higher PSNR gain over AOMDV at both low and high node speeds.
Liang, Ji; Yuan, Xiaohui; Yuan, Yanbin; Chen, Zhihuan; Li, Yuanzheng
2017-02-01
The safety and stability of hydraulic turbine regulating system (HTRS) in hydropower plants become increasingly important since the rapid development and the broad application of hydro energy technology. In this paper, a novel mathematical model of Francis hydraulic turbine regulating system with a straight-tube surge tank based on a few state-space equations is introduced to study the dynamic behaviors of the HTRS system, where the existence of possible unstable oscillations of this model is studied extensively and presented in the forms of the bifurcation diagram, time waveform plot, phase trajectories, and power spectrum. To eliminate these undesirable behaviors, a specified fuzzy sliding mode controller is designed. In this hybrid controller, the sliding mode control law makes full use of the proposed model to guarantee the robust control in the presence of system uncertainties, while the fuzzy system is applied to approximate the proper gains of the switching control in sliding mode technique to reduce the chattering effect, and particle swarm optimization is developed to search the optimal gains of the controller. Numerical simulations are presented to verify the effectiveness of the designed controller, and the results show that the performances of the nonlinear HTRS system assisted with the proposed controller is much better than that with the commonly used optimal PID controller.
Le, T Hoang Ngan; Luu, Khoa; Savvides, Marios
2013-08-01
Robust facial hair detection and segmentation is a highly valued soft biometric attribute for carrying out forensic facial analysis. In this paper, we propose a novel and fully automatic system, called SparCLeS, for beard/moustache detection and segmentation in challenging facial images. SparCLeS uses the multiscale self-quotient (MSQ) algorithm to preprocess facial images and deal with illumination variation. Histogram of oriented gradients (HOG) features are extracted from the preprocessed images and a dynamic sparse classifier is built using these features to classify a facial region as either containing skin or facial hair. A level set based approach, which makes use of the advantages of both global and local information, is then used to segment the regions of a face containing facial hair. Experimental results demonstrate the effectiveness of our proposed system in detecting and segmenting facial hair regions in images drawn from three databases, i.e., the NIST Multiple Biometric Grand Challenge (MBGC) still face database, the NIST Color Facial Recognition Technology FERET database, and the Labeled Faces in the Wild (LFW) database.
Robust Dynamic Cooperative Games
Bauso, D.; Timmer, Judith B.
2006-01-01
Classical cooperative game theory is no longer a suitable tool for those situations where the values of coalitions are not known with certainty. Recent works address situations where the values of coalitions are modelled by random variables. In this work we still consider the values of coalitions as
Chen, Xiangyong; Zhang, Ancai
2014-01-01
For the particularity of warfare hybrid dynamic process, a class of warfare hybrid dynamic systems is established based on Lanchester equation in a (n,1) battle, where a heterogeneous force of n different troop types faces a homogeneous force. This model can be characterized by the interaction of continuous-time models (governed by Lanchester equation), and discrete event systems (described by variable tactics). Furthermore, an expository discussion is presented on an optimal variable tact...
Vajuvalli, Nithin N.; Chikkemenahally, Dharmendra Kumar K.; Nayak, Krupa N.; Bhosale, Manoj G.; Geethanath, Sairam
2016-12-01
Dynamic contrast enhancement magnetic resonance imaging (DCE-MRI) is a well-established method for non-invasive detection and therapeutic monitoring of pathologies through administration of intravenous contrast agent. Quantification of pharmacokinetic (PK) maps can be achieved through application of compartmental models relevant to the pathophysiology of the tissue under interrogation. The determination of PK parameters involves fitting of time-concentration data to these models. In this work, the Tofts model in frequency domain (TM-FD) is applied to a weakly vascularized tissue such as the breast. It is derived as a convolution-free model from the conventional Tofts model in the time domain (TM-TD). This reduces the dimensionality of the curve-fitting problem from two to one. The approaches of TM-FD and TM-TD were applied to two kinds of in silico phantoms and six in vivo breast DCE data sets with and without the addition of noise. The results showed that computational time taken to estimate PK maps using TM-FD was 16-25% less than with TM-TD. Normalized root mean square error (NRMSE) calculation and Pearson correlation analyses were performed to validate robustness and accuracy of the TM-FD and TM-TD approaches. These compared with ground truth values in the case of phantom studies for four different temporal resolutions. Results showed that NRMSE values for TM-FD were significantly lower than those of TM-TD as validated by a paired t-test along with reduced computational time. This approach therefore enables online evaluation of PK maps by radiologists in a clinical setting, aiding in the evaluation of 3D and/or increased coverage of the tissue of interest.
Directory of Open Access Journals (Sweden)
Yongchang Wei
2015-01-01
uncertain environment. The impact of network structure and collaboration on the dynamics and robustness of supply chain network, however, remains to be explored. In this paper, a unified state space model for a two-layer supply chain network composed of multiple distributors and multiple retailers is developed. A robust control algorithm is advocated to reduce both order and demand fluctuations for unknown demand. Numerical simulations demonstrate that the robust control approach has the advantage to reduce both inventory and order fluctuations. In the simulation experiment, it is interesting to notice that complex network structure and collaborations might contribute to the reduction of inventory and order oscillations. This paper yields new insights into the overestimated bullwhip effect problem and helps us understand the complexities of supply chain networks.
Energy Technology Data Exchange (ETDEWEB)
Howlander, Abdul Motin [Faculty of Engineering, Univ. of the Ryukyus, Okinawa (Japan); Urasaki, Naomitsu [Faculty of Engineering, Univ. of the Ryukyus, Okinawa (Japan); Yona, Atsushi [Faculty of Engineering, Univ. of the Ryukyus, Okinawa (Japan); Senjyu, Tomonobu [Faculty of Engineering, Univ. of the Ryukyus, Okinawa (Japan); Saber, Ahmed Yousuf [Operation Technology, Irvine, CA (United States)
2013-04-15
A digital H{sub {infinity}}controller for a permanent magnet synchronous generator (PMSG) based wind energy conversion system (WECS) is presented. Wind energy is an uncertain fluctuating resource which requires a tight control management. So, it is still an exigent task for the control design engineers. The conventional proportional-integral (PI) control is not ideal during high turbulence wind velocities, and the nonlinear behavior of the power converters. These are raising interest towards the robust control concepts. The robust design is to find a controller, for a given system, such that the closed-loop system becomes robust that assurance high-integrity and fault tolerant control system, robust H{sub {infinity}}control theory has befallen a standard design method of choice over the past two decades in industrial control applications. The robust H{sub {infinity}}control theory is also gaining eminence in the WECS. Due to the implementation complexity for the continuous H{sub {infinity}}controller, and availability of the high speedy micro-controllers, the design of a sample-data or a digital H{sub {infinity}}controller is very important for the realistic implementation. But there isn’t a single research to evaluate the performance of the digital H{sub {infinity}}controller for the WECS. In this paper, the proposed digital H{sub {infinity}}controller schemes comprise for the both generator and grid interactive power converters, and the control performances are compared with the conventional PI controller and the fuzzy controller. Simulation results confirm the efficacy of the proposed method Energies 2013, 6 2085 which are ensured the WECS stabilities, mitigate shaft stress, and improving the DC-link voltage and output power qualities.
Directory of Open Access Journals (Sweden)
Tomonobu Senjyu
2013-04-01
Full Text Available A digital H∞ controller for a permanent magnet synchronous generator (PMSG based wind energy conversion system (WECS is presented. Wind energy is an uncertain fluctuating resource which requires a tight control management. So, it is still an exigent task for the control design engineers. The conventional proportional-integral (PI control is not ideal during high turbulence wind velocities, and the nonlinear behavior of the power converters. These are raising interest towards the robust control concepts. The robust design is to find a controller, for a given system, such that the closed-loop system becomes robust that assurance high-integrity and fault tolerant control system, robust H∞ control theory has befallen a standard design method of choice over the past two decades in industrial control applications. The robust H∞ control theory is also gaining eminence in the WECS. Due to the implementation complexity for the continuous H∞ controller, and availability of the high speedy micro-controllers, the design of a sample-data or a digital H∞ controller is very important for the realistic implementation. But there isn’t a single research to evaluate the performance of the digital H∞ controller for the WECS. In this paper, the proposed digital H∞ controller schemes comprise for the both generator and grid interactive power converters, and the control performances are compared with the conventional PI controller and the fuzzy controller. Simulation results confirm the efficacy of the proposed method Energies 2013, 6 2085 which are ensured the WECS stabilities, mitigate shaft stress, and improving the DC-link voltage and output power qualities.
International Nuclear Information System (INIS)
Antonov, N V; Kapustin, A S
2012-01-01
Critical behaviour of the dynamical Potts model, subjected to vivid turbulent mixing, is studied by means of the renormalization group. The advecting velocity field is modelled by Kraichnan’s rapid-change ensemble: Gaussian statistics with a given pair correlator 〈vv〉∝δ(t − t′) k −d−ξ , where k is the wave number, d is the dimension of space and 0 < ξ < 2 is an arbitrary exponent. The system exhibits different types of infrared scaling behaviour, associated with four infrared attractors of the renormalization group equations. In addition to the known asymptotic regimes (equilibrium Potts model and passive scalar field), the existence of a new, strongly non-equilibrium type of critical behaviour (universality class) is established, where the self-interaction of the order parameter and the turbulent mixing are equally important. The corresponding critical dimensions and the regions of stability for all the regimes are calculated in the leading order of the double expansion in ξ and ε = 6 − d. Special attention is paid to the effects of compressibility of the fluid, because they lead to interesting crossover phenomena. (paper)
Robust Approaches to Forecasting
Jennifer Castle; David Hendry; Michael P. Clements
2014-01-01
We investigate alternative robust approaches to forecasting, using a new class of robust devices, contrasted with equilibrium correction models. Their forecasting properties are derived facing a range of likely empirical problems at the forecast origin, including measurement errors, implulses, omitted variables, unanticipated location shifts and incorrectly included variables that experience a shift. We derive the resulting forecast biases and error variances, and indicate when the methods ar...
Panter, Michaela S; Jain, Ankur; Leonhardt, Ralf M; Ha, Taekjip; Cresswell, Peter
2012-09-07
Although the human peptide-loading complex (PLC) is required for optimal major histocompatibility complex class I (MHC I) antigen presentation, its composition is still incompletely understood. The ratio of the transporter associated with antigen processing (TAP) and MHC I to tapasin, which is responsible for MHC I recruitment and peptide binding optimization, is particularly critical for modeling of the PLC. Here, we characterized the stoichiometry of the human PLC using both biophysical and biochemical approaches. By means of single-molecule pulldown (SiMPull), we determined a TAP/tapasin ratio of 1:2, consistent with previous studies of insect-cell microsomes, rat-human chimeric cells, and HeLa cells expressing truncated TAP subunits. We also report that the tapasin/MHC I ratio varies, with the PLC population comprising both 2:1 and 2:2 complexes, based on mutational and co-precipitation studies. The MHC I-saturated PLC may be particularly prevalent among peptide-selective alleles, such as HLA-C4. Additionally, MHC I association with the PLC increases when its peptide supply is reduced by inhibiting the proteasome or by blocking TAP-mediated peptide transport using viral inhibitors. Taken together, our results indicate that the composition of the human PLC varies under normal conditions and dynamically adapts to alterations in peptide supply that may arise during viral infection. These findings improve our understanding of the quality control of MHC I peptide loading and may aid the structural and functional modeling of the human PLC.
Feedforward/feedback control synthesis for performance and robustness
Wie, Bong; Liu, Qiang
1990-01-01
Both feedforward and feedback control approaches for uncertain dynamical systems are investigated. The control design objective is to achieve a fast settling time (high performance) and robustness (insensitivity) to plant modeling uncertainty. Preshapong of an ideal, time-optimal control input using a 'tapped-delay' filter is shown to provide a rapid maneuver with robust performance. A robust, non-minimum-phase feedback controller is synthesized with particular emphasis on its proper implementation for a non-zero set-point control problem. The proposed feedforward/feedback control approach is robust for a certain class of uncertain dynamical systems, since the control input command computed for a given desired output does not depend on the plant parameters.
H pylori receptor MHC class II contributes to the dynamic gastric epithelial apoptotic response
Bland, David A; Suarez, Giovanni; Beswick, Ellen J; Sierra, Johanna C; Reyes, Victor E
2006-01-01
AIM: To investigate the role of MHC class II in the modulation of gastric epithelial cell apoptosis induced by H pylori infection. METHODS: After stimulating a human gastric epithelial cell line with bacteria or agonist antibodies specific for MHC class II and CD95, the quantitation of apoptotic and anti-apoptotic events, including caspase activation, BCL-2 activation, and FADD recruitment, was performed with a fluorometric assay, a cytometric bead array, and confocal microscopy, respectively. RESULTS: Pretreatment of N87 cells with the anti-MHC class II IgM antibody RFD1 resulted in a reduction in global caspase activation at 24 h of H pylori infection. When caspase 3 activation was specifically measured, crosslinking of MHC class II resulted in a marked reduced caspase activation, while simple ligation of MHC class II did not. Crosslinking of MHC class II also resulted in an increased activation of the anti-apoptosis molecule BCL-2 compared to simple ligation. Confocal microscope analysis demonstrated that the pretreatment of gastric epithelial cells with a crosslinking anti-MHC class II IgM blocked the recruitment of FADD to the cell surface. CONCLUSION: The results presented here demonstrate that the ability of MHC class II to modulate gastric epithelial apoptosis is at least partially dependent on its crosslinking. Furthermore, while previous research has demonstrated that MHC class II signaling can be pro-apoptotic during extended ligation, we have shown that the crosslinking of this molecule has anti-apoptotic effects during the earlier time points of H pylori infection. This effect is possibly mediated by the ability of MHC class II to modulate the activation of the pro-apoptotic receptor Fas by blocking the recruitment of the accessory molecule FADD, and this delay in apoptosis induction could allow for prolonged cytokine secretion by H pylori-infected gastric epithelial cells. PMID:16981259
van der Maas, H.L.J.; Newell, K.; Molenaar, P.C.M.
1998-01-01
Cognitive developmental psychology is faced with new developments in the mathematical theory of nonlinear dynamic systems and in psychometrics. This chapter addresses: the relation between the strategy concept in cognitive developmental psychology and the concept of attractor in nonlinear dynamic
Comparative energetics of the 5 fish classes on the basis of dynamic energy budgets
Kooijman, Sebastiaan A. L. M.; Lika, Konstadia
2014-11-01
The eco-physiology of taxa in an evolutionary context can best be studied by a comparison of parameter values of the energy budget that accounts for the inter-relationships of all endpoints of energy allocation. To this end, the parameters of the standard Dynamic Energy Budget (DEB) model have been estimated for 64 fish species from all 5 fish classes. The values are compared with those of the whole collection of over 300 species from most large animal phyla. The goodness of fit was very high, but the data were rather incomplete, compared with the energy balance for full life cycles. Metabolic acceleration, where maximum specific assimilation and energy conductance increase with length between birth and metabolic metamorphosis, seems to be confined, among fish, to some species of ray-finned fish and seems to have evolved independently several times in this taxon. We introduce a new altriciality index, i.e. the ratio of the maturity levels at puberty and birth, and conclude that ray-finned fish are more altricial, and cartilaginous fish are more precocial than typical animals. Fish allocate more to reproduction than typical animals. Parameter estimates show that 66% of the fish species considered invest less in reproduction than the value that would maximize the reproduction rate of fully grown individuals. By comparison, 85% of all the animal species in the collection do so. Consistent with theoretical expectations, allocation to reproduction and maturity at birth increase with cubed (ultimate structural) length, and reserve capacity with length for non-ray-finned fish, with the consequence that reproduction rate decreases with length. Ray-finned fish, however, have a maturity at birth and a reserve capacity almost independent of length, and a reproduction rate that increases with cubed length. Reserve capacity tends to increase with ultimate length for non-accelerating ray-finned fish, but not for accelerating species. Reproduction rate decreases inter
Hyppolite, Judex; Trivedi, Pravin
2012-06-01
Cross-sectional latent class regression models, also known as switching regressions or hidden Markov models, cannot identify transitions between classes that may occur over time. This limitation can potentially be overcome when panel data are available. For such data, we develop a sequence of models that combine features of the static cross-sectional latent class (finite mixture) models with those of hidden Markov models. We model the probability of movement between categories in terms of a Markovian structure, which links the current state with a previous state, where state may refer to the category of an individual. This article presents a suite of mixture models of varying degree of complexity and flexibility for use in a panel count data setting, beginning with a baseline model which is a two-component mixture of Poisson distribution in which latent classes are fixed and permanent. Sequentially, we extend this framework (i) to allow the mixing proportions to be smoothly varying continuous functions of time-varying covariates, (ii) to add time dependence to the benchmark model by modeling the class-indicator variable as a first-order Markov chain and (iii) to extend item (i) by making it dynamic and introducing covariate dependence in the transition probabilities. We develop and implement estimation algorithms for these models and provide an empirical illustration using 1995-1999 panel data on the number of doctor visits derived from the German Socio-Economic Panel. Copyright © 2012 John Wiley & Sons, Ltd.
DEFF Research Database (Denmark)
Sørensen, John Dalsgaard
2008-01-01
This paper describes the background of the robustness requirements implemented in the Danish Code of Practice for Safety of Structures and in the Danish National Annex to the Eurocode 0, see (DS-INF 146, 2003), (DS 409, 2006), (EN 1990 DK NA, 2007) and (Sørensen and Christensen, 2006). More...... frequent use of advanced types of structures with limited redundancy and serious consequences in case of failure combined with increased requirements to efficiency in design and execution followed by increased risk of human errors has made the need of requirements to robustness of new structures essential....... According to Danish design rules robustness shall be documented for all structures in high consequence class. The design procedure to document sufficient robustness consists of: 1) Review of loads and possible failure modes / scenarios and determination of acceptable collapse extent; 2) Review...
DEFF Research Database (Denmark)
Gottschall, Julia; Courtney, Michael
2015-01-01
on the theory of Langevin processes and their reconstruction, we enlarge on a number of specific practical issues. Special attention is paid to the convergence or robustness of the reconstructed results, and their dependence on different settings for the data analysis scheme is studied. A key issue...... for the procedure that is investigated in this paper is the variability of the wind speed data that may be controlled by applying a specific data filter. It is seen that the necessity for filtering depends both on the time scales present in the wind data in relation to the wind turbine power dynamics and to some...
Cook, G. W.
2012-12-01
At the University of California, San Diego, I teach a quarter-long, introductory Earth Science class titled "Volcanoes," which is, in essence, a functional class in volcanology designed specifically for non-majors. This large-format (enrollment ~ 85), lecture-based class provides students from an assortment of backgrounds an opportunity to acquire much-needed (and sometimes dreaded) area credits in science, while also serving as an introduction to the Earth Science major at UCSD (offered through Scripps Institution of Oceanography). The overall goal of the course is to provide students with a stimulating and exciting general science option that, using an inherently interesting topic, introduces them to the fundamentals of geoscience. A secondary goal is to promote general science and geoscience literacy among the general population of UCSD. Student evaluations of this course unequivocally indicate a high degree of learning and interest in the material. The majority of students in the class (>80%) are non-science majors and very few students (degree-seeking students. In addition, only a handful of students have typically had any form of geology class beyond high school level Earth Science. Consequently, there are challenges associated with teaching the class. Perhaps most significantly, students have very little background—background that is necessary for understanding the processes involved in volcanic eruptions. Second, many non-science students have built-in anxieties with respect to math and science, anxieties that must be considered when designing curriculum and syllabi. It is essential to provide the right balance of technical information while remaining in touch with the audience. My approach to the class involves a dynamic lecture format that incorporates a wide array of multimedia, analogue demonstrations of volcanic processes, and small-group discussions of topics and concepts. In addition to teaching about volcanoes—a fascinating subject in and of
Stability of latent class segments over time
DEFF Research Database (Denmark)
Mueller, Simone
2011-01-01
Dynamic stability, as the degree to which identified segments at a given time remain unchanged over time in terms of number, size and profile, is a desirable segment property which has received limited attention so far. This study addresses the question to what degree latent classes identified from...... logit model suggests significant changes in the price sensitivity and the utility from environmental claims between both experimental waves. A pooled scale adjusted latent class model is estimated jointly over both waves and the relative size of latent classes is compared across waves, resulting...... in significant differences in the size of two out of seven classes. These differences can largely be accounted for by the changes on the aggregated level. The relative size of latent classes is correlated at 0.52, suggesting a fair robustness. An ex-post characterisation of latent classes by behavioural...
International Nuclear Information System (INIS)
Vasconcelos, Geovane Vitor; Melo, Silvio de Barros; Dantas, Carlos Costa; Moreira, Icaro Malta; Johansen, Geira; Maad, Rachid
2013-01-01
The PSIRT (Particle Systems Iterative Reconstructive Technique) is, just like the ART method, an iterative tomographic reconstruction technique with the recommended use in the reconstruction of catalytic density distribution in the refining process of oil in the FCC-type riser. The PSIRT is based upon computer graphics' particle systems, where the reconstructing material is initially represented as composed of particles subject to a force field emanating from the beams, whose intensities are parameterized by the differences between the experimental readings of a given beam trajectory, and the values corresponding to the current amount of particles landed in this trajectory. A dynamical process is set as the beams fields of attracting forces dispute the particles. At the end, with the equilibrium established, the particles are replaced by the corresponding regions of pixels. The High Speed Gamma-ray Tomograph is a 5-source-fan-beam device with a 17-detector deck per source, capable of producing up to a thousand complete sinograms per second. Around 70.000 experimental sinograms from this tomograph were produced simulating the move of gas bubbles in different angular speeds immersed in oil within the vessel, through the use of a two-hole-polypropylene phantom. The sinogram frames were set with several different detector integration times. This article studies and compares the robustness of both ART and PSIRT methods in this heavily noisy scenario, where this noise comes not only from limitations in the dynamical sampling, but also from to the underlying apparatus that produces the counting in the tomograph. These experiments suggest that PSIRT is a more robust method than ART for noisy data. Visual inspection on the resulting images suggests that PSIRT is a more robust method than ART for noisy data, since it almost never presents globally scattered noise. (author)
Caralt, de S.; Uriz, M.J.; Wijffels, R.H.
2008-01-01
The growth dynamics and survival of the sponge Corticium candelabrum (Demospongiae: Homosclerophorida) were surveyed in the northwestern Mediterranean for more than 3 yr. Growth and regeneration rates, fission and fusion events and survival were monitored monthly. Moreover, in situ punctual
Dynamics of a class of cellular neural networks with time-varying delays
International Nuclear Information System (INIS)
Huang Lihong; Huang Chuangxia; Liu Bingwen
2005-01-01
Employing Brouwer's fixed point theorem, matrix theory, a continuation theorem of the coincidence degree and inequality analysis, the authors make a further investigation of a class of cellular neural networks with delays (DCNNs) in this Letter. A family of sufficient conditions are given for checking global exponential stability and the existence of periodic solutions of DCNNs. These results have important leading significance in the design and applications of globally stable DCNNs and periodic oscillatory DCNNs. Our results extend and improve some earlier publications
International Nuclear Information System (INIS)
De Santis, Emilio; Marinelli, Carlo
2007-01-01
We introduce and study a class of infinite-horizon non-zero-sum non-cooperative stochastic games with infinitely many interacting agents using ideas of statistical mechanics. First we show, in the general case of asymmetric interactions, the existence of a strategy that allows any player to eliminate losses after a finite random time. In the special case of symmetric interactions, we also prove that, as time goes to infinity, the game converges to a Nash equilibrium. Moreover, assuming that all agents adopt the same strategy, using arguments related to those leading to perfect simulation algorithms, spatial mixing and ergodicity are proved. In turn, ergodicity allows us to prove 'fixation', i.e. players will adopt a constant strategy after a finite time. The resulting dynamics is related to zero-temperature Glauber dynamics on random graphs of possibly infinite volume
DEFF Research Database (Denmark)
Gorm Hansen, Birgitte
their core i nterests, 2) developing a selfsupply of industry interests by becoming entrepreneurs and thus creating their own compliant industry partner and 3) balancing resources within a larger collective of researchers, thus countering changes in the influx of funding caused by shifts in political...... knowledge", Danish research policy seems to have helped develop politically and economically "robust scientists". Scientific robustness is acquired by way of three strategies: 1) tasting and discriminating between resources so as to avoid funding that erodes academic profiles and push scientists away from...
Well-observed dynamics of flaring and peripheral coronal magnetic loops during an M-class limb flare
International Nuclear Information System (INIS)
Shen, Jinhua; Zhou, Tuanhui; Ji, Haisheng; Feng, Li; Wiegelmann, Thomas; Inhester, Bernd
2014-01-01
In this paper, we present a variety of well-observed dynamic behaviors for the flaring and peripheral magnetic loops of the M6.6 class extreme limb flare that occurred on 2011 February 24 (SOL2011-02-24T07:20) from EUV observations by the Atmospheric Imaging Assembly on the Solar Dynamics Observatory and X-ray observations by RHESSI. The flaring loop motion confirms the earlier contraction-expansion picture. We find that the U-shaped trajectory delineated by the X-ray corona source of the flare roughly follows the direction of a filament eruption associated with the flare. Different temperature structures of the coronal source during the contraction and expansion phases strongly suggest different kinds of magnetic reconnection processes. For some peripheral loops, we discover that their dynamics are closely correlated with the filament eruption. During the slow rising to abrupt, fast rising of the filament, overlying peripheral magnetic loops display different responses. Two magnetic loops on the elbow of the active region had a slow descending motion followed by an abrupt successive fast contraction, while magnetic loops on the top of the filament were pushed outward, slowly being inflated for a while and then erupting as a moving front. We show that the filament activation and eruption play a dominant role in determining the dynamics of the overlying peripheral coronal magnetic loops.
Ganguly, Sujoy; Liang, Xin; Grace, Michael; Lee, Daniel; Howard, Jonathon
The morphology of neurons is diverse and reflects the diversity of neuronal functions, yet the principles that govern neuronal morphogenesis are unclear. In an effort to better understand neuronal morphogenesis we will be focusing on the development of the dendrites of class IV sensory neuron in Drosophila melanogaster. In particular we attempt to determine how the the total length, and the number of branches of dendrites are mathematically related to the dynamics of neurite growth and branching. By imaging class IV neurons during early embryogenesis we are able to measure the change in neurite length l (t) as a function of time v (t) = dl / dt . We found that the distribution of v (t) is well characterized by a hyperbolic secant distribution, and that the addition of new branches per unit time is well described by a Poisson process. Combining these measurements with the assumption that branching occurs with equal probability anywhere along the dendrite we were able to construct a mathematical model that provides reasonable agreement with the observed number of branches, and total length of the dendrites of the class IV sensory neuron.
Wang, Huanqing; Liu, Peter Xiaoping; Li, Shuai; Wang, Ding
2017-08-29
This paper presents the development of an adaptive neural controller for a class of nonlinear systems with unmodeled dynamics and immeasurable states. An observer is designed to estimate system states. The structure consistency of virtual control signals and the variable partition technique are combined to overcome the difficulties appearing in a nonlower triangular form. An adaptive neural output-feedback controller is developed based on the backstepping technique and the universal approximation property of the radial basis function (RBF) neural networks. By using the Lyapunov stability analysis, the semiglobally and uniformly ultimate boundedness of all signals within the closed-loop system is guaranteed. The simulation results show that the controlled system converges quickly, and all the signals are bounded. This paper is novel at least in the two aspects: 1) an output-feedback control strategy is developed for a class of nonlower triangular nonlinear systems with unmodeled dynamics and 2) the nonlinear disturbances and their bounds are the functions of all states, which is in a more general form than existing results.
Institute of Scientific and Technical Information of China (English)
HU Jia-bing; HE Yi-kang
2006-01-01
Doubly-FedInduction Generator (DFIG), with vector control applied, is widely used in Variable-Speed ConstantFrequency (VSCF) windenergy generation system and shows good performance in maximum wind energy capture. But in two traditional vector control schemes, the equivalent stator magnetizing current is considered invariant in order to simplify the rotor current inner-loop controller. The two schemes can perform very well when the grid is in normal condition. However, when grid disturbance such as grid voltage dip or swell fault occurs, the control performance worsens, the rotor over current occurs and the Fault Ride-Through (FRT) capability of the DFIG wind energy generation system gets seriously deteriorated. An accurate DFIG model was used to deeply investigate the deficiency of the traditional vector control. The improved control schemes of two typical traditional vector control schemes used in DFIG were proposed, and simulation study of the proposed and traditional control schemes, with robust rotor current control using Internal Model Control (IMC) method, was carried out. The validity of the proposed modified schemes to control the rotor current and to improve the FRT capability of the DFIG wind energy generation system was proved by the comparison study.
Amenable crossed product Banach algebras associated with a class of C*-dynamical systems
Jeu, de M.F.E.; Elharti, R.; Pinto, P.R.
2017-01-01
We prove that the crossed product Banach algebra ℓ1(G,A;α) that is associated with a C∗-dynamical system (A,G,α) is amenable if G is a discrete amenable group and A is a commutative or finite dimensional C∗-algebra. Perspectives for further developments are indicated.
Comparative energetics of the 5 fish classes on the basis of dynamic energy budgets.
Kooijman, S.A.L.M.; Lika, K.
2014-01-01
The eco-physiology of taxa in an evolutionary context can best be studied by a comparison of parameter values of the energy budget that accounts for the inter-relationships of all endpoints of energy allocation. To this end, the parameters of the standard Dynamic Energy Budget (DEB) model have been
International Nuclear Information System (INIS)
Lakomek, Nils-Alexander; Walter, Korvin F. A.; Fares, Christophe; Lange, Oliver F.; Groot, Bert L. de; Grubmueller, Helmut; Brueschweiler, Rafael; Munk, Axel; Becker, Stefan; Meiler, Jens; Griesinger, Christian
2008-01-01
Residual dipolar couplings (RDCs) provide information about the dynamic average orientation of inter-nuclear vectors and amplitudes of motion up to milliseconds. They complement relaxation methods, especially on a time-scale window that we have called supra-τ c (τ c c rdc > = 0.72 ± 0.02 compared to LS 2 > = 0.778 ± 0.003 for the Lipari-Szabo order parameters, indicating that the inclusion of the supra-τ c window increases the averaged amplitude of mobility observed in the sub-τ c window by about 34%. For the β-strand spanned by residues Lys48 to Leu50, an alternating pattern of backbone NH RDC order parameter S rdc 2 (NH) = (0.59, 0.72, 0.59) was extracted. The backbone of Lys48, whose side chain is known to be involved in the poly-ubiquitylation process that leads to protein degradation, is very mobile on the supra-τ c time scale (S rdc 2 (NH) = 0.59 ± 0.03), while it is inconspicuous (S LS 2 (NH) = 0.82) on the sub-τ c as well as on μs-ms relaxation dispersion time scales. The results of this work differ from previous RDC dynamics studies of ubiquitin in the sense that the results are essentially independent of structural noise providing a much more robust assessment of dynamic effects that underlie the RDC data
DEFF Research Database (Denmark)
Ernst, Erik; Ostermann, Klaus; Cook, William Randall
2006-01-01
Virtual classes are class-valued attributes of objects. Like virtual methods, virtual classes are defined in an object's class and may be redefined within subclasses. They resemble inner classes, which are also defined within a class, but virtual classes are accessed through object instances...... model for virtual classes has been a long-standing open question. This paper presents a virtual class calculus, vc, that captures the essence of virtual classes in these full-fledged programming languages. The key contributions of the paper are a formalization of the dynamic and static semantics of vc...
The Strata-1 Regolith Dynamics Experiment: Class 1E Science on ISS
Fries, Marc; Graham, Lee; John, Kristen
2016-01-01
The Strata-1 experiment studies the evolution of small body regolith through long-duration exposure of simulant materials to the microgravity environment on the International Space Station (ISS). This study will record segregation and mechanical dynamics of regolith simulants in a microgravity and vibration environment similar to that experienced by regolith on small Solar System bodies. Strata-1 will help us understand regolith dynamics and will inform design and procedures for landing and setting anchors, safely sampling and moving material on asteroidal surfaces, processing large volumes of material for in situ resource utilization (ISRU) purposes, and, in general, predicting the behavior of large and small particles on disturbed asteroid surfaces. This experiment is providing new insights into small body surface evolution.
Bai, Weiqi; Dong, Hairong; Yao, Xiuming; Ning, Bin
2018-04-01
This paper proposes a composite fault detection scheme for the dynamics of high-speed train (HST), using an unknown input observer-like (UIO-like) fault detection filter, in the presence of wind gust and operating noises which are modeled as disturbance generated by exogenous system and unknown multi-source disturbance within finite frequency domain. Using system input and system output measurements, the fault detection filter is designed to generate the needed residual signals. In order to decouple disturbance from residual signals without truncating the influence of faults, this paper proposes a method to partition the disturbance into two parts. One subset of the disturbance does not appear in residual dynamics, and the influence of the other subset is constrained by H ∞ performance index in a finite frequency domain. A set of detection subspaces are defined, and every different fault is assigned to its own detection subspace to guarantee the residual signals are diagonally affected promptly by the faults. Simulations are conducted to demonstrate the effectiveness and merits of the proposed method. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.
Analytical solution for a class of network dynamics with mechanical and financial applications
Czech Academy of Sciences Publication Activity Database
Krejčí, Pavel; Lamba, H.; Melnik, S.; Rachinskii, D.
2014-01-01
Roč. 90, č. 3 (2014), 032822 ISSN 1539-3755 R&D Projects: GA ČR GAP201/10/2315 Institutional support: RVO:67985840 Keywords : network dynamics * hysteresis * discontinuous Prandtl-Ishlinskii model Subject RIV: BA - General Mathematics Impact factor: 2.288, year: 2014 http://journals. aps .org/pre/abstract/10.1103/PhysRevE.90.032822
Analytical solution for a class of network dynamics with mechanical and financial applications
Czech Academy of Sciences Publication Activity Database
Krejčí, Pavel; Lamba, H.; Melnik, S.; Rachinskii, D.
2014-01-01
Roč. 90, č. 3 (2014), 032822 ISSN 1539-3755 R&D Projects: GA ČR GAP201/10/2315 Institutional support: RVO:67985840 Keywords : network dynamics * hysteresis * discontinuous Prandtl-Ishlinskii model Subject RIV: BA - General Mathematics Impact factor: 2.288, year: 2014 http://journals.aps.org/pre/abstract/10.1103/PhysRevE.90.032822
Several classes of graphs and their r-dynamic chromatic numbers
Dafik; Meganingtyas, D. E. W.; Dwidja Purnomo, K.; Dicky Tarmidzi, M.; Hesti Agustin, Ika
2017-06-01
Let G be a simple, connected and undirected graph. Let r, k be natural numbers. By a proper k-coloring of a graph G, we mean a map c : V (G) → S, where |S| = k, such that any two adjacent vertices receive different colors. An r-dynamic k-coloring is a proper k-coloring c of G such that |c(N(v))| ≥ min{r, d(v)} for each vertex v in V (G), where N(v) is the neighborhood of v and c(S) = {c(v) : v ∈ S} for a vertex subset S. The r-dynamic chromatic number, written as χ r (G), is the minimum k such that G has an r-dynamic k-coloring. By simple observation it is easy to see that χ r (G) ≤ χ r+1(G), however χ r+1(G) - χ r (G) does not always show a small difference for any r. Thus, finding an exact value of χ r (G) is significantly useful. In this paper, we will study some of them especially when G are prism graph, three-cyclical ladder graph, joint graph and circulant graph.
Nonsymmetric dynamical thin-shell wormhole in Robinson-Trautman class
Svítek, O.; Tahamtan, T.
2018-02-01
The thin-shell wormhole created using the Darmois-Israel formalism applied to Robinson-Trautman family of spacetimes is presented. The stress energy tensor created on the throat is interpreted in terms of two dust streams and it is shown that asymptotically this wormhole settles to the Schwarzschild wormhole with a throat located at the position of the horizon. This behavior shows a nonlinear stability (within the Robinson-Trautman class) of this spherically symmetric wormhole. The gravitational radiation emitted by the Robinson-Trautman wormhole during the transition to spherical symmetry is indistinguishable from that of the corresponding black hole Robinson-Trautman spacetime. Subsequently, we show that the higher-dimensional generalization of Robinson-Trautman geometry offers a possibility of constructing wormholes without the need to violate the energy conditions for matter induced on the throat.
Directory of Open Access Journals (Sweden)
Jian Liu
Full Text Available In this paper, adaptive control is extended from real space to complex space, resulting in a new control scheme for a class of n-dimensional time-dependent strict-feedback complex-variable chaotic (hyperchaotic systems (CVCSs in the presence of uncertain complex parameters and perturbations, which has not been previously reported in the literature. In detail, we have developed a unified framework for designing the adaptive complex scalar controller to ensure this type of CVCSs asymptotically stable and for selecting complex update laws to estimate unknown complex parameters. In particular, combining Lyapunov functions dependent on complex-valued vectors and back-stepping technique, sufficient criteria on stabilization of CVCSs are derived in the sense of Wirtinger calculus in complex space. Finally, numerical simulation is presented to validate our theoretical results.
Liu, Jian; Liu, Kexin; Liu, Shutang
2017-01-01
In this paper, adaptive control is extended from real space to complex space, resulting in a new control scheme for a class of n-dimensional time-dependent strict-feedback complex-variable chaotic (hyperchaotic) systems (CVCSs) in the presence of uncertain complex parameters and perturbations, which has not been previously reported in the literature. In detail, we have developed a unified framework for designing the adaptive complex scalar controller to ensure this type of CVCSs asymptotically stable and for selecting complex update laws to estimate unknown complex parameters. In particular, combining Lyapunov functions dependent on complex-valued vectors and back-stepping technique, sufficient criteria on stabilization of CVCSs are derived in the sense of Wirtinger calculus in complex space. Finally, numerical simulation is presented to validate our theoretical results.
Nonsymmetric dynamical thin-shell wormhole in Robinson-Trautman class
Energy Technology Data Exchange (ETDEWEB)
Svitek, O. [Charles University, Institute of Theoretical Physics, Faculty of Mathematics and Physics, Prague (Czech Republic); Tahamtan, T. [Charles University, Institute of Theoretical Physics, Faculty of Mathematics and Physics, Prague (Czech Republic); Czech Academy of Sciences, Astronomical Institute, Prague (Czech Republic)
2018-02-15
The thin-shell wormhole created using the Darmois-Israel formalism applied to Robinson-Trautman family of spacetimes is presented. The stress energy tensor created on the throat is interpreted in terms of two dust streams and it is shown that asymptotically this wormhole settles to the Schwarzschild wormhole with a throat located at the position of the horizon. This behavior shows a nonlinear stability (within the Robinson-Trautman class) of this spherically symmetric wormhole. The gravitational radiation emitted by the Robinson-Trautman wormhole during the transition to spherical symmetry is indistinguishable from that of the corresponding black hole Robinson-Trautman spacetime. Subsequently, we show that the higher-dimensional generalization of Robinson-Trautman geometry offers a possibility of constructing wormholes without the need to violate the energy conditions for matter induced on the throat. (orig.)
Chang, Ya-Fen; Chen, Chia-Chen; Chang, Pei-Yu
2013-04-01
Nowadays, users/patients may gain desired medical services on-line because of the rapid development of computer network technologies. Conventional healthcare services are provided by a single server. However, care team collaboration by integrating services is the key to improve financial and clinical performance. How a user/patient accesses desired medical services provided by multiple servers becomes a challenge to realize care team collaboration. User authentication plays an important role to protect resources or services from being accessed by unauthorized users. In this paper, we first discuss the perceived security drawbacks of pervasive smart-card-based remote user authentication schemes. Then, we propose a novel dynamic-ID-based user authentication scheme based on elliptic curve cryptosystem (ECC) for multi-server environment with smart cards. The proposed scheme ensures user anonymity and computational efficiency and complies with essential requirements of a secure smart-card-based authentication scheme for multi-server environment to enable care team collaboration.
Robustness of MEK-ERK Dynamics and Origins of Cell-to-Cell Variability in MAPK Signaling
Directory of Open Access Journals (Sweden)
Sarah Filippi
2016-06-01
Full Text Available Cellular signaling processes can exhibit pronounced cell-to-cell variability in genetically identical cells. This affects how individual cells respond differentially to the same environmental stimulus. However, the origins of cell-to-cell variability in cellular signaling systems remain poorly understood. Here, we measure the dynamics of phosphorylated MEK and ERK across cell populations and quantify the levels of population heterogeneity over time using high-throughput image cytometry. We use a statistical modeling framework to show that extrinsic noise, particularly that from upstream MEK, is the dominant factor causing cell-to-cell variability in ERK phosphorylation, rather than stochasticity in the phosphorylation/dephosphorylation of ERK. We furthermore show that without extrinsic noise in the core module, variable (including noisy signals would be faithfully reproduced downstream, but the within-module extrinsic variability distorts these signals and leads to a drastic reduction in the mutual information between incoming signal and ERK activity.
Thomas-Claudepierre, Anne-Sophie; Robert, Isabelle; Rocha, Pedro P; Raviram, Ramya; Schiavo, Ebe; Heyer, Vincent; Bonneau, Richard; Luo, Vincent M; Reddy, Janardan K; Borggrefe, Tilman; Skok, Jane A; Reina-San-Martin, Bernardo
2016-03-07
Immunoglobulin (Ig) class switch recombination (CSR) is initiated by the transcription-coupled recruitment of activation-induced cytidine deaminase (AID) to Ig switch regions (S regions). During CSR, the IgH locus undergoes dynamic three-dimensional structural changes in which promoters, enhancers, and S regions are brought to close proximity. Nevertheless, little is known about the underlying mechanisms. In this study, we show that Med1 and Med12, two subunits of the mediator complex implicated in transcription initiation and long-range enhancer/promoter loop formation, are dynamically recruited to the IgH locus enhancers and the acceptor regions during CSR and that their knockdown in CH12 cells results in impaired CSR. Furthermore, we show that conditional inactivation of Med1 in B cells results in defective CSR and reduced acceptor S region transcription. Finally, we show that in B cells undergoing CSR, the dynamic long-range contacts between the IgH enhancers and the acceptor regions correlate with Med1 and Med12 binding and that they happen at a reduced frequency in Med1-deficient B cells. Our results implicate the mediator complex in the mechanism of CSR and are consistent with a model in which mediator facilitates the long-range contacts between S regions and the IgH locus enhancers during CSR and their transcriptional activation. © 2016 Thomas-Claudepierre et al.
The Dynamical Behaviors for a Class of Immunogenic Tumor Model with Delay
Directory of Open Access Journals (Sweden)
Ping Bi
2017-01-01
Full Text Available This paper aims at studying the model proposed by Kuznetsov and Taylor in 1994. Inspired by Mayer et al., time delay is introduced in the general model. The dynamic behaviors of this model are studied, which include the existence and stability of the equilibria and Hopf bifurcation of the model with discrete delays. The properties of the bifurcated periodic solutions are studied by using the normal form on the center manifold. Numerical examples and simulations are given to illustrate the bifurcation analysis and the obtained results.
Fan, Meng; Ye, Dan
2005-09-01
This paper studies the dynamics of a system of retarded functional differential equations (i.e., RF=Es), which generalize the Hopfield neural network models, the bidirectional associative memory neural networks, the hybrid network models of the cellular neural network type, and some population growth model. Sufficient criteria are established for the globally exponential stability and the existence and uniqueness of pseudo almost periodic solution. The approaches are based on constructing suitable Lyapunov functionals and the well-known Banach contraction mapping principle. The paper ends with some applications of the main results to some neural network models and population growth models and numerical simulations.
Geometry Dynamics of α-Helices in Different Class I Major Histocompatibility Complexes
Directory of Open Access Journals (Sweden)
Reiner Ribarics
2015-01-01
Full Text Available MHC α-helices form the antigen-binding cleft and are of particular interest for immunological reactions. To monitor these helices in molecular dynamics simulations, we applied a parsimonious fragment-fitting method to trace the axes of the α-helices. Each resulting axis was fitted by polynomials in a least-squares sense and the curvature integral was computed. To find the appropriate polynomial degree, the method was tested on two artificially modelled helices, one performing a bending movement and another a hinge movement. We found that second-order polynomials retrieve predefined parameters of helical motion with minimal relative error. From MD simulations we selected those parts of α-helices that were stable and also close to the TCR/MHC interface. We monitored the curvature integral, generated a ruled surface between the two MHC α-helices, and computed interhelical area and surface torsion, as they changed over time. We found that MHC α-helices undergo rapid but small changes in conformation. The curvature integral of helices proved to be a sensitive measure, which was closely related to changes in shape over time as confirmed by RMSD analysis. We speculate that small changes in the conformation of individual MHC α-helices are part of the intrinsic dynamics induced by engagement with the TCR.
Rodriguez Lucatero, C.; Schaum, A.; Alarcon Ramos, L.; Bernal-Jaquez, R.
2014-07-01
In this study, the dynamics of decisions in complex networks subject to external fields are studied within a Markov process framework using nonlinear dynamical systems theory. A mathematical discrete-time model is derived using a set of basic assumptions regarding the convincement mechanisms associated with two competing opinions. The model is analyzed with respect to the multiplicity of critical points and the stability of extinction states. Sufficient conditions for extinction are derived in terms of the convincement probabilities and the maximum eigenvalues of the associated connectivity matrices. The influences of exogenous (e.g., mass media-based) effects on decision behavior are analyzed qualitatively. The current analysis predicts: (i) the presence of fixed-point multiplicity (with a maximum number of four different fixed points), multi-stability, and sensitivity with respect to the process parameters; and (ii) the bounded but significant impact of exogenous perturbations on the decision behavior. These predictions were verified using a set of numerical simulations based on a scale-free network topology.
Sriboonchitta, Songsak; Huynh, Van-Nam
2017-01-01
This book presents recent research on robustness in econometrics. Robust data processing techniques – i.e., techniques that yield results minimally affected by outliers – and their applications to real-life economic and financial situations are the main focus of this book. The book also discusses applications of more traditional statistical techniques to econometric problems. Econometrics is a branch of economics that uses mathematical (especially statistical) methods to analyze economic systems, to forecast economic and financial dynamics, and to develop strategies for achieving desirable economic performance. In day-by-day data, we often encounter outliers that do not reflect the long-term economic trends, e.g., unexpected and abrupt fluctuations. As such, it is important to develop robust data processing techniques that can accommodate these fluctuations.
Directory of Open Access Journals (Sweden)
Afzali-Far Behrouz
2015-01-01
Full Text Available In this paper, we propose a class of Generalized Gough-Stewart Platforms (GGSPs used, as a novel approach, to eliminate the classical isotropic constraint of GSPs (hexapods. GGSPs are based on the standard GSP architecture with additional rotations of the three strut-pairs. Despite the architectural generalization introduced in GGSPs, they do not require much more effort in order to be fabricated. This is due to the fact that all the struts (actuators can be chosen identical, similar to standard GSPs. We analytically show how effectively the classical isotropic constraint is removed and that still sufficient simplicity is retained. Furthermore, this paper gives an intuitive understanding of dynamic isotropy in GGSPs as well as GSPs.
Mahiti, Macdonald; Brumme, Zabrina L; Jessen, Heiko; Brockman, Mark A; Ueno, Takamasa
2015-07-31
HLA class II-restricted CD4(+) T lymphocytes play an important role in controlling HIV-1 replication, especially in the acute/early infection stage. But, HIV-1 Nef counteracts this immune response by down-regulating HLA-DR and up-regulating the invariant chain associated with immature HLA-II (Ii). Although functional heterogeneity of various Nef activities, including down-regulation of HLA class I (HLA-I), is well documented, our understanding of Nef-mediated evasion of HLA-II-restricted immune responses during acute/early infection remains limited. Here, we examined the ability of Nef clones from 47 subjects with acute/early progressive infection and 46 subjects with chronic progressive infection to up-regulate Ii and down-regulate HLA-DR and HLA-I from the surface of HIV-infected cells. HLA-I down-regulation function was preserved among acute/early Nef clones, whereas both HLA-DR down-regulation and Ii up-regulation functions displayed relatively broad dynamic ranges. Nef's ability to down-regulate HLA-DR and up-regulate Ii correlated positively at this stage, suggesting they are functionally linked in vivo. Acute/early Nef clones also exhibited higher HLA-DR down-regulation and lower Ii up-regulation functions compared to chronic Nef clones. Taken together, our results support enhanced Nef-mediated HLA class II immune evasion activities in acute/early compared to chronic infection, highlighting the potential importance of these functions following transmission. Copyright © 2015 Elsevier Inc. All rights reserved.
Robust stability and ℋ ∞ -estimation for uncertain discrete systems with state-delay
Directory of Open Access Journals (Sweden)
Mahmoud Magdi S.
2001-01-01
Full Text Available In this paper, we investigate the problems of robust stability and ℋ ∞ -estimation for a class of linear discrete-time systems with time-varying norm-bounded parameter uncertainty and unknown state-delay. We provide complete results for robust stability with prescribed performance measure and establish a version of the discrete Bounded Real Lemma. Then, we design a linear estimator such that the estimation error dynamics is robustly stable with a guaranteed ℋ ∞ -performance irrespective of the parameteric uncertainties and unknown state delays. A numerical example is worked out to illustrate the developed theory.
Wang, Licheng; Wang, Zidong; Han, Qing-Long; Wei, Guoliang
2017-09-06
The synchronization control problem is investigated for a class of discrete-time dynamical networks with packet dropouts via a coding-decoding-based approach. The data is transmitted through digital communication channels and only the sequence of finite coded signals is sent to the controller. A series of mutually independent Bernoulli distributed random variables is utilized to model the packet dropout phenomenon occurring in the transmissions of coded signals. The purpose of the addressed synchronization control problem is to design a suitable coding-decoding procedure for each node, based on which an efficient decoder-based control protocol is developed to guarantee that the closed-loop network achieves the desired synchronization performance. By applying a modified uniform quantization approach and the Kronecker product technique, criteria for ensuring the detectability of the dynamical network are established by means of the size of the coding alphabet, the coding period and the probability information of packet dropouts. Subsequently, by resorting to the input-to-state stability theory, the desired controller parameter is obtained in terms of the solutions to a certain set of inequality constraints which can be solved effectively via available software packages. Finally, two simulation examples are provided to demonstrate the effectiveness of the obtained results.
Directory of Open Access Journals (Sweden)
Claude Gérard
Full Text Available microRNAs (miRNAs are small noncoding RNAs that are important post-transcriptional regulators of gene expression. miRNAs can induce thresholds in protein synthesis. Such thresholds in protein output can be also achieved by oligomerization of transcription factors (TF for the control of gene expression. First, we propose a minimal model for protein expression regulated by miRNA and by oligomerization of TF. We show that miRNA and oligomerization of TF generate a buffer, which increases the robustness of protein output towards molecular noise as well as towards random variation of kinetics parameters. Next, we extend the model by considering that the same miRNA can bind to multiple messenger RNAs, which accounts for the dynamics of a minimal competing endogenous RNAs (ceRNAs network. The model shows that, through common miRNA regulation, TF can control the expression of all proteins formed by the ceRNA network, even if it drives the expression of only one gene in the network. The model further suggests that the threshold in protein synthesis mediated by the oligomerization of TF can be propagated to the other genes, which can increase the robustness of the expression of all genes in such ceRNA network. Furthermore, we show that a miRNA could increase the time delay of a "Goodwin-like" oscillator model, which may favor the occurrence of oscillations of large amplitude. This result predicts important roles of miRNAs in the control of the molecular mechanisms leading to the emergence of biological rhythms. Moreover, a model for the latter oscillator embedded in a ceRNA network indicates that the oscillatory behavior can be propagated, via the shared miRNA, to all proteins formed by such ceRNA network. Thus, by means of computational models, we show that miRNAs could act as vectors allowing the propagation of robustness in protein synthesis as well as oscillatory behaviors within ceRNA networks.
Turmel, Monique; Otis, Christian; Lemieux, Claude
2015-07-01
Previous studies of trebouxiophycean chloroplast genomes revealed little information regarding the evolutionary dynamics of this genome because taxon sampling was too sparse and the relationships between the sampled taxa were unknown. We recently sequenced the chloroplast genomes of 27 trebouxiophycean and 2 pedinophycean green algae to resolve the relationships among the main lineages recognized for the Trebouxiophyceae. These taxa and the previously sampled members of the Pedinophyceae and Trebouxiophyceae are included in the comparative chloroplast genome analysis we report here. The 38 genomes examined display considerable variability at all levels, except gene content. Our results highlight the high propensity of the rDNA-containing large inverted repeat (IR) to vary in size, gene content and gene order as well as the repeated losses it experienced during trebouxiophycean evolution. Of the seven predicted IR losses, one event demarcates a superclade of 11 taxa representing 5 late-diverging lineages. IR expansions/contractions account not only for changes in gene content in this region but also for changes in gene order and gene duplications. Inversions also led to gene rearrangements within the IR, including the reversal or disruption of the rDNA operon in some lineages. Most of the 20 IR-less genomes are more rearranged compared with their IR-containing homologs and tend to show an accelerated rate of sequence evolution. In the IR-less superclade, several ancestral operons were disrupted, a few genes were fragmented, and a subgroup of taxa features a G+C-biased nucleotide composition. Our analyses also unveiled putative cases of gene acquisitions through horizontal transfer. © The Author(s) 2015. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.
Linear beam dynamics and ampere class superconducting RF cavities at RHIC
Calaga, Rama R.
-cell electron gun and a five-cell SRF linac cavity are presented. Several RF and beam dynamics issues ultimately resulting in an optimum cavity design are discussed in detail.
Robust and distributed hypothesis testing
Gül, Gökhan
2017-01-01
This book generalizes and extends the available theory in robust and decentralized hypothesis testing. In particular, it presents a robust test for modeling errors which is independent from the assumptions that a sufficiently large number of samples is available, and that the distance is the KL-divergence. Here, the distance can be chosen from a much general model, which includes the KL-divergence as a very special case. This is then extended by various means. A minimax robust test that is robust against both outliers as well as modeling errors is presented. Minimax robustness properties of the given tests are also explicitly proven for fixed sample size and sequential probability ratio tests. The theory of robust detection is extended to robust estimation and the theory of robust distributed detection is extended to classes of distributions, which are not necessarily stochastically bounded. It is shown that the quantization functions for the decision rules can also be chosen as non-monotone. Finally, the boo...
Energy Technology Data Exchange (ETDEWEB)
Shi, W.; Wehner, W.P.; Barton, J.E.; Boyer, M.D. [Mechanical Engineering and Mechanics, Lehigh University, Bethlehem, PA 18015 (United States); Schuster, E., E-mail: schuster@lehigh.edu [Mechanical Engineering and Mechanics, Lehigh University, Bethlehem, PA 18015 (United States); Moreau, D. [CEA, IRFM, F-13018 St Paul lez Durance (France); Walker, M.L.; Ferron, J.R.; Luce, T.C.; Humphreys, D.A.; Penaflor, B.G.; Johnson, R.D. [General Atomics, San Diego, CA 92121 (United States)
2017-04-15
A control-oriented, two-timescale, linear, dynamic, response model of the rotational transform ι profile and the normalized beta β{sub N} is proposed based on experimental data from the DIII-D tokamak. Dedicated system-identification experiments without feedback control have been carried out to generate data for the development of this model. The data-driven dynamic model, which is both device-specific and scenario-specific, represents the response of the ι profile and β{sub N} to the electric field due to induction as well as to the heating and current drive (H&CD) systems during the flat-top phase of an H-mode discharge in DIII-D. The control goal is to use both induction and the H&CD systems to locally regulate the plasma ι profile and β{sub N} around particular target values close to the reference state used for system identification. A singular value decomposition (SVD) of the plasma model at steady state is carried out to decouple the system and identify the most relevant control channels. A mixed-sensitivity robust control design problem is formulated based on the dynamic model to synthesize a stabilizing feedback controller without input constraints that minimizes the reference tracking error and rejects external disturbances with minimal control energy. The feedback controller is then augmented with an anti-windup compensator, which keeps the given controller well-behaved in the presence of magnitude constraints in the actuators and leaves the nominal closed-loop system unmodified when no saturation is present. The proposed controller represents one of the first feedback profile controllers integrating magnetic and kinetic variables ever implemented and experimentally tested in DIII-D. The preliminary experimental results presented in this work, although limited in number and constrained by actuator problems and design limitations, as it will be reported, show good progress towards routine current profile control in DIII-D and leave valuable lessons
Zhang, Yajun; Chai, Tianyou; Wang, Hong; Wang, Dianhui; Chen, Xinkai
2018-06-01
Complex industrial processes are multivariable and generally exhibit strong coupling among their control loops with heavy nonlinear nature. These make it very difficult to obtain an accurate model. As a result, the conventional and data-driven control methods are difficult to apply. Using a twin-tank level control system as an example, a novel multivariable decoupling control algorithm with adaptive neural-fuzzy inference system (ANFIS)-based unmodeled dynamics (UD) compensation is proposed in this paper for a class of complex industrial processes. At first, a nonlinear multivariable decoupling controller with UD compensation is introduced. Different from the existing methods, the decomposition estimation algorithm using ANFIS is employed to estimate the UD, and the desired estimating and decoupling control effects are achieved. Second, the proposed method does not require the complicated switching mechanism which has been commonly used in the literature. This significantly simplifies the obtained decoupling algorithm and its realization. Third, based on some new lemmas and theorems, the conditions on the stability and convergence of the closed-loop system are analyzed to show the uniform boundedness of all the variables. This is then followed by the summary on experimental tests on a heavily coupled nonlinear twin-tank system that demonstrates the effectiveness and the practicability of the proposed method.
Burro, Roberto; Raccanello, Daniela; Pasini, Margherita; Brondino, Margherita
2018-01-01
Conceptualizing affect as a complex nonlinear dynamic process, we used latent class extended mixed models (LCMM) to understand whether there were unobserved groupings in a dataset including longitudinal measures. Our aim was to identify affect profiles over time in people vicariously exposed to terrorism, studying their relations with personality traits. The participants were 193 university students who completed online measures of affect during the seven days following two terrorist attacks (Paris, November 13, 2015; Brussels, March 22, 2016); Big Five personality traits; and antecedents of affect. After selecting students whose negative affect was influenced by the two attacks (33%), we analysed the data with the LCMM package of R. We identified two affect profiles, characterized by different trends over time: The first profile comprised students with lower positive affect and higher negative affect compared to the second profile. Concerning personality traits, conscientious-ness was lower for the first profile compared to the second profile, and vice versa for neuroticism. Findings are discussed for both their theoretical and applied relevance.
Kinematically Optimal Robust Control of Redundant Manipulators
Galicki, M.
2017-12-01
This work deals with the problem of the robust optimal task space trajectory tracking subject to finite-time convergence. Kinematic and dynamic equations of a redundant manipulator are assumed to be uncertain. Moreover, globally unbounded disturbances are allowed to act on the manipulator when tracking the trajectory by the endeffector. Furthermore, the movement is to be accomplished in such a way as to minimize both the manipulator torques and their oscillations thus eliminating the potential robot vibrations. Based on suitably defined task space non-singular terminal sliding vector variable and the Lyapunov stability theory, we derive a class of chattering-free robust kinematically optimal controllers, based on the estimation of transpose Jacobian, which seem to be effective in counteracting both uncertain kinematics and dynamics, unbounded disturbances and (possible) kinematic and/or algorithmic singularities met on the robot trajectory. The numerical simulations carried out for a redundant manipulator of a SCARA type consisting of the three revolute kinematic pairs and operating in a two-dimensional task space, illustrate performance of the proposed controllers as well as comparisons with other well known control schemes.
Xu, Yunjun; Remeikas, Charles; Pham, Khanh
2014-03-01
Cooperative trajectory planning is crucial for networked vehicles to respond rapidly in cluttered environments and has a significant impact on many applications such as air traffic or border security monitoring and assessment. One of the challenges in cooperative planning is to find a computationally efficient algorithm that can accommodate both the complexity of the environment and real hardware and configuration constraints of vehicles in the formation. Inspired by a local pursuit strategy observed in foraging ants, feasible and optimal trajectory planning algorithms are proposed in this paper for a class of nonlinear constrained cooperative vehicles in environments with densely populated obstacles. In an iterative hierarchical approach, the local behaviours, such as the formation stability, obstacle avoidance, and individual vehicle's constraints, are considered in each vehicle's (i.e. follower's) decentralised optimisation. The cooperative-level behaviours, such as the inter-vehicle collision avoidance, are considered in the virtual leader's centralised optimisation. Early termination conditions are derived to reduce the computational cost by not wasting time in the local-level optimisation if the virtual leader trajectory does not satisfy those conditions. The expected advantages of the proposed algorithms are (1) the formation can be globally asymptotically maintained in a decentralised manner; (2) each vehicle decides its local trajectory using only the virtual leader and its own information; (3) the formation convergence speed is controlled by one single parameter, which makes it attractive for many practical applications; (4) nonlinear dynamics and many realistic constraints, such as the speed limitation and obstacle avoidance, can be easily considered; (5) inter-vehicle collision avoidance can be guaranteed in both the formation transient stage and the formation steady stage; and (6) the computational cost in finding both the feasible and optimal
Srivastava, Amit Kumar; Kapoor, Kalpesh
2017-01-01
Let Q be the set of primitive words over a finite alphabet with at least two symbols. We characterize a class of primitive words, Q_I, referred to as ins-robust primitive words, which remain primitive on insertion of any letter from the alphabet and present some properties that characterizes words in the set Q_I. It is shown that the language Q_I is dense. We prove that the language of primitive words that are not ins-robust is not context-free. We also present a linear time algorithm to reco...
Robustness of Linear Systems towards Multi-Dissipative Pertubations
DEFF Research Database (Denmark)
Thygesen, Uffe Høgsbro; Poulsen, Niels Kjølstad
1997-01-01
We consider the question of robust stability of a linear time invariant plant subject to dynamic perturbations, which are dissipative in the sense of Willems with respect to several quadratic supply rates. For instance, parasitic dynamics are often both small gain and passive. We reduce several...... robustness analysis questions to linear matrix inequalities: robust stability, robust H2 performance and robust performance in presence of disturbances with finite signal-to-noise ratios...
Robust output synchronization of heterogeneous nonlinear agents in uncertain networks.
Yang, Xi; Wan, Fuhua; Tu, Mengchuan; Shen, Guojiang
2017-11-01
This paper investigates the global robust output synchronization problem for a class of nonlinear multi-agent systems. In the considered setup, the controlled agents are heterogeneous and with both dynamic and parametric uncertainties, the controllers are incapable of exchanging their internal states with the neighbors, and the communication network among agents is defined by an uncertain simple digraph. The problem is pursued via nonlinear output regulation theory and internal model based design. For each agent, the input-driven filter and the internal model compose the controller, and the decentralized dynamic output feedback control law is derived by using backstepping method and the modified dynamic high-gain technique. The theoretical result is applied to output synchronization problem for uncertain network of Lorenz-type agents. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.
Energy Technology Data Exchange (ETDEWEB)
Pegan, Scott D. [Univ. of Denver, CO (United States); Rukseree, Kamolchanok [National Center for Genetic Engineering and Biotechnology (BIOTEC), Tha Khlong (Thailand); Capodagli, Glenn C. [Univ. of Denver, CO (United States); Baker, Erica A. [Univ. of Denver, CO (United States); Krasnykh, Olga [Univ. of Illinois, Chicago, IL (United States); Franzblau, Scott G. [Univ. of Illinois, Chicago, IL (United States); Mesecar, Andrew D. [Purdue Univ., West Lafayette, IN (United States)
2013-01-08
The class II fructose 1,6-bisphosphate aldolases (FBAs, EC 4.1.2.13) comprises one of two families of aldolases. Instead of forming a Schiff base intermediate using an ε-amino group of a lysine side chain, class II FBAs utilize Zn(II) to stabilize a proposed hydroxyenolate intermediate (HEI) in the reversible cleavage of fructose 1,6-bisphosphate, forming glyceraldehyde 3-phosphate and dihydroxyacetone phosphate (DHAP). As class II FBAs have been shown to be essential in pathogenic bacteria, focus has been placed on these enzymes as potential antibacterial targets. Although structural studies of class II FBAs from Mycobacterium tuberculosis (MtFBA), other bacteria, and protozoa have been reported, the structure of the active site loop responsible for catalyzing the protonation–deprotonation steps of the reaction for class II FBAs has not yet been observed. We therefore utilized the potent class II FBA inhibitor phosphoglycolohydroxamate (PGH) as a mimic of the HEI- and DHAP-bound form of the enzyme and determined the X-ray structure of the MtFBA–PGH complex to 1.58 Å. Remarkably, we are able to observe well-defined electron density for the previously elusive active site loop of MtFBA trapped in a catalytically competent orientation. Utilization of this structural information and site-directed mutagenesis and kinetic studies conducted on a series of residues within the active site loop revealed that E169 facilitates a water-mediated deprotonation–protonation step of the MtFBA reaction mechanism. Furthermore, solvent isotope effects on MtFBA and catalytically relevant mutants were used to probe the effect of loop flexibility on catalytic efficiency. Additionally, we also reveal the structure of MtFBA in its holoenzyme form.
Methods for robustness programming
Olieman, N.J.
2008-01-01
Robustness of an object is defined as the probability that an object will have properties as required. Robustness Programming (RP) is a mathematical approach for Robustness estimation and Robustness optimisation. An example in the context of designing a food product, is finding the best composition
Star, L.
2008-01-01
The aim of the project ‘The genetics of robustness in laying hens’ was to investigate nature and regulation of robustness in laying hens under sub-optimal conditions and the possibility to increase robustness by using animal breeding without loss of production. At the start of the project, a robust
International Nuclear Information System (INIS)
Chen, J.-D.
2007-01-01
In this paper, the robust control problem of output dynamic observer-based control for a class of uncertain neutral systems with discrete and distributed time delays is considered. Linear matrix inequality (LMI) optimization approach is used to design the new output dynamic observer-based controls. Three classes of observer-based controls are proposed and the maximal perturbed bound is given. Based on the results of this paper, the constraint of matrix equality is not necessary for designing the observer-based controls. Finally, a numerical example is given to illustrate the usefulness of the proposed method
Loosely coupled class families
DEFF Research Database (Denmark)
Ernst, Erik
2001-01-01
are expressed using virtual classes seem to be very tightly coupled internally. While clients have achieved the freedom to dynamically use one or the other family, it seems that any given family contains a xed set of classes and we will need to create an entire family of its own just in order to replace one...... of the members with another class. This paper shows how to express class families in such a manner that the classes in these families can be used in many dierent combinations, still enabling family polymorphism and ensuring type safety....
Robustness: confronting lessons from physics and biology.
Lesne, Annick
2008-11-01
The term robustness is encountered in very different scientific fields, from engineering and control theory to dynamical systems to biology. The main question addressed herein is whether the notion of robustness and its correlates (stability, resilience, self-organisation) developed in physics are relevant to biology, or whether specific extensions and novel frameworks are required to account for the robustness properties of living systems. To clarify this issue, the different meanings covered by this unique term are discussed; it is argued that they crucially depend on the kind of perturbations that a robust system should by definition withstand. Possible mechanisms underlying robust behaviours are examined, either encountered in all natural systems (symmetries, conservation laws, dynamic stability) or specific to biological systems (feedbacks and regulatory networks). Special attention is devoted to the (sometimes counterintuitive) interrelations between robustness and noise. A distinction between dynamic selection and natural selection in the establishment of a robust behaviour is underlined. It is finally argued that nested notions of robustness, relevant to different time scales and different levels of organisation, allow one to reconcile the seemingly contradictory requirements for robustness and adaptability in living systems.
Kumar, Sivakumar Prasanth; Patel, Chirag N; Jha, Prakash C; Pandya, Himanshu A
2017-12-01
The identification of isatin sulfonamide as a potent small molecule inhibitor of caspase-3 had fuelled the synthesis and characterization of the numerous sulfonamide class of inhibitors to optimize for potency. Recent works that relied on the ligand-based approaches have successfully shown the regions of optimizations for sulfonamide scaffold. We present here molecular dynamics-based pharmacophore modeling of caspase-3-isatin sulfonamide crystal structure, to elucidate the essential non-covalent contacts and its associated pharmacophore features necessary to ensure caspase-3 optimal binding. We performed 20ns long dynamics of this crystal structure to extract global conformation states and converted into structure-based pharmacophore hypotheses which were rigorously validated using an exclusive focussed library of experimental actives and inactives of sulfonamide class by Receiver Operating Characteristic (ROC) statistic. Eighteen structure-based pharmacophore hypotheses with better sensitivity and specificity measures (>0.6) were chosen which collectively showed the role of pocket residues viz. Cys163 (S 1 sub-site; required for covalent and H bonding with Michael acceptor of inhibitors), His121 (S 1 ; π stack with bicyclic isatin moiety), Gly122 (S 1 ; H bond with carbonyl oxygen) and Tyr204 (S 2 ; π stack with phenyl group of the isatin sulfonamide molecule) as stringent binding entities for enabling caspase-3 optimal binding. The introduction of spatial pharmacophore site points obtained from dynamics-based pharmacophore models in a virtual screening strategy will be helpful to screen and optimize molecules belonging to sulfonamide class of caspase-3 inhibitors. Copyright © 2017 Elsevier Ltd. All rights reserved.
Majumdar, Apala
2013-06-01
We analyze the dynamical stability of a naturally straight, inextensible and unshearable elastic rod, under tension and controlled end rotation, within the Kirchhoff model in three dimensions. The cases of clamped boundary conditions and isoperimetric constraints are treated separately. We obtain explicit criteria for the static stability of arbitrary extrema of a general quadratic strain energy. We exploit the equivalence between the total energy and a suitably defined norm to prove that local minimizers of the strain energy, under explicit hypotheses, are stable in the dynamic sense due to Liapounov. We also extend our analysis to damped systems to show that static equilibria are dynamically stable in the Liapounov sense, in the presence of a suitably defined local drag force. © 2013 Elsevier B.V. All rights reserved.
Directory of Open Access Journals (Sweden)
Xiangyong Chen
2014-01-01
hybrid dynamic systems is established based on Lanchester equation in a (n,1 battle, where a heterogeneous force of n different troop types faces a homogeneous force. This model can be characterized by the interaction of continuous-time models (governed by Lanchester equation, and discrete event systems (described by variable tactics. Furthermore, an expository discussion is presented on an optimal variable tactics control problem for warfare hybrid dynamic system. The optimal control strategies are designed based on dynamic programming and differential game theory. As an example of the consequences of this optimal control problem, we take the (2, 1 case and solve the optimal strategies in a (2, 1 case. Simulation results show the feasibility of warfare hybrid system model and the effectiveness of the optimal control strategies designed.
International Nuclear Information System (INIS)
Li, Lixiang; Li, Weiwei; Kurths, Jürgen; Luo, Qun; Yang, Yixian; Li, Shudong
2015-01-01
For the reason that the uncertain complex dynamic network with multi-link is quite close to various practical networks, there is superiority in the fields of research and application. In this paper, we focus upon pinning adaptive synchronization for uncertain complex dynamic networks with multi-link against network deterioration. The pinning approach can be applied to adapt uncertain coupling factors of deteriorated networks which can compensate effects of uncertainty. Several new synchronization criterions for networks with multi-link are derived, which ensure the synchronized states to be local or global stable with uncertainty and deterioration. Results of simulation are shown to demonstrate the feasibility and usefulness of our method
DEFF Research Database (Denmark)
Pedersen, Søren Nygaard
The research presented in this PhD thesis has focused on a perceptual approach to robust design. The results of the research and the original contribution to knowledge is a preliminary framework for understanding, positioning, and applying perceptual robust design. Product quality is a topic...... been presented. Therefore, this study set out to contribute to the understanding and application of perceptual robust design. To achieve this, a state-of-the-art and current practice review was performed. From the review two main research problems were identified. Firstly, a lack of tools...... for perceptual robustness was found to overlap with the optimum for functional robustness and at most approximately 2.2% out of the 14.74% could be ascribed solely to the perceptual robustness optimisation. In conclusion, the thesis have offered a new perspective on robust design by merging robust design...
CSIR Research Space (South Africa)
Everard, DA
1995-12-01
Full Text Available Indigenous forest in Kwa Zulu-Natal has been fairly well described, however, very little has been published on its dynamics. There is, to our knowledge, nothing published on disturbances regimes, dendrology and life histories of constituent species...
Neutrality and robustness in evo-devo: emergence of lateral inhibition.
Directory of Open Access Journals (Sweden)
Andreea Munteanu
2008-11-01
Full Text Available Embryonic development is defined by the hierarchical dynamical process that translates genetic information (genotype into a spatial gene expression pattern (phenotype providing the positional information for the correct unfolding of the organism. The nature and evolutionary implications of genotype-phenotype mapping still remain key topics in evolutionary developmental biology (evo-devo. We have explored here issues of neutrality, robustness, and diversity in evo-devo by means of a simple model of gene regulatory networks. The small size of the system allowed an exhaustive analysis of the entire fitness landscape and the extent of its neutrality. This analysis shows that evolution leads to a class of robust genetic networks with an expression pattern characteristic of lateral inhibition. This class is a repertoire of distinct implementations of this key developmental process, the diversity of which provides valuable clues about its underlying causal principles.
DEFF Research Database (Denmark)
Gasiunas, Vaidas; Mezini, Mira; Ostermann, Klaus
2007-01-01
of dependent classes and a machine-checked type soundness proof in Isabelle/HOL [29], the first of this kind for a language with virtual classes and path-dependent types. [29] T.Nipkow, L.C. Poulson, and M. Wenzel. Isabelle/HOL -- A Proof Assistant for Higher-Order Logic, volume 2283 of LNCS, Springer, 2002......Virtual classes allow nested classes to be refined in subclasses. In this way nested classes can be seen as dependent abstractions of the objects of the enclosing classes. Expressing dependency via nesting, however, has two limitations: Abstractions that depend on more than one object cannot...... be modeled and a class must know all classes that depend on its objects. This paper presents dependent classes, a generalization of virtual classes that expresses similar semantics by parameterization rather than by nesting. This increases expressivity of class variations as well as the flexibility...
Directory of Open Access Journals (Sweden)
Simone Monteiro
2009-06-01
Full Text Available Este trabalho discute as dinâmicas de discriminação entre moças e rapazes das camadas populares do Rio de Janeiro, considerando o papel que as hierarquias de cor/raça, gênero e classe social desempenham na configuração das práticas sociais. A análise tem por base entrevistas em profundidade com 42 jovens, de 18 a 24 anos. As situações de discriminação são referidas com maior frequência pelos rapazes. Entre os homens tais experiências estão associadas principalmente aos espaços públicos e ao mercado de trabalho, enquanto entre as mulheres a discriminação está mais vinculada aos espaços privados e ao local de moradia. Os dados estimulam uma discussão sobre a heterogeneidade das experiências de discriminação, na qual a cor/raça está associada às condições sociais e às relações de gênero.This work discuss the dynamics of discrimination of lower income male and female youths from Rio de Janeiro, considering the impact of the color/race, gender and social class hierarchies in the configurations of social practices. The analysis is based on in-depth interviews of 42 young people from 18 to 24 years of age. Situations of discrimination are much more referred to by men. The public spaces and the labor market are cited mainly by the boys. In the girls' view the discrimination is more associated to the place of residence and the private sphere. These data stimulate an analysis about the heterogeneity of the experiences of discrimination, where color/race is associated to social condition and gender relations.
Robustness of Structural Systems
DEFF Research Database (Denmark)
Canisius, T.D.G.; Sørensen, John Dalsgaard; Baker, J.W.
2007-01-01
The importance of robustness as a property of structural systems has been recognised following several structural failures, such as that at Ronan Point in 1968,where the consequenceswere deemed unacceptable relative to the initiating damage. A variety of research efforts in the past decades have...... attempted to quantify aspects of robustness such as redundancy and identify design principles that can improve robustness. This paper outlines the progress of recent work by the Joint Committee on Structural Safety (JCSS) to develop comprehensive guidance on assessing and providing robustness in structural...... systems. Guidance is provided regarding the assessment of robustness in a framework that considers potential hazards to the system, vulnerability of system components, and failure consequences. Several proposed methods for quantifying robustness are reviewed, and guidelines for robust design...
J Olive, David
2017-01-01
This text presents methods that are robust to the assumption of a multivariate normal distribution or methods that are robust to certain types of outliers. Instead of using exact theory based on the multivariate normal distribution, the simpler and more applicable large sample theory is given. The text develops among the first practical robust regression and robust multivariate location and dispersion estimators backed by theory. The robust techniques are illustrated for methods such as principal component analysis, canonical correlation analysis, and factor analysis. A simple way to bootstrap confidence regions is also provided. Much of the research on robust multivariate analysis in this book is being published for the first time. The text is suitable for a first course in Multivariate Statistical Analysis or a first course in Robust Statistics. This graduate text is also useful for people who are familiar with the traditional multivariate topics, but want to know more about handling data sets with...
Ray, Jessica L; Althammer, Julia; Skaar, Katrine S; Simonelli, Paolo; Larsen, Aud; Stoecker, Diane; Sazhin, Andrey; Ijaz, Umer Z; Quince, Christopher; Nejstgaard, Jens C; Frischer, Marc; Pohnert, Georg; Troedsson, Christofer
2016-11-01
In order to characterize copepod feeding in relation to microbial plankton community dynamics, we combined metabarcoding and metabolome analyses during a 22-day seawater mesocosm experiment. Nutrient amendment of mesocosms promoted the development of haptophyte (Phaeocystis pouchetii)- and diatom (Skeletonema marinoi)-dominated plankton communities in mesocosms, in which Calanus sp. copepods were incubated for 24 h in flow-through chambers to allow access to prey particles (<500 μm). Copepods and mesocosm water sampled six times spanning the experiment were analysed using metabarcoding, while intracellular metabolite profiles of mesocosm plankton communities were generated for all experimental days. Taxon-specific metabarcoding ratios (ratio of consumed prey to available prey in the surrounding seawater) revealed diverse and dynamic copepod feeding selection, with positive selection on large diatoms, heterotrophic nanoflagellates and fungi, while smaller phytoplankton, including P. pouchetii, were passively consumed or even negatively selected according to our indicator. Our analysis of the relationship between Calanus grazing ratios and intracellular metabolite profiles indicates the importance of carbohydrates and lipids in plankton succession and copepod-prey interactions. This molecular characterization of Calanus sp. grazing therefore provides new evidence for selective feeding in mixed plankton assemblages and corroborates previous findings that copepod grazing may be coupled to the developmental and metabolic stage of the entire prey community rather than to individual prey abundances. © 2016 John Wiley & Sons Ltd.
Robust sawtooth period control based on adaptive online optimization
International Nuclear Information System (INIS)
Bolder, J.J.; Witvoet, G.; De Baar, M.R.; Steinbuch, M.; Van de Wouw, N.; Haring, M.A.M.; Westerhof, E.; Doelman, N.J.
2012-01-01
The systematic design of a robust adaptive control strategy for the sawtooth period using electron cyclotron current drive (ECCD) is presented. Recent developments in extremum seeking control (ESC) are employed to derive an optimized controller structure and offer practical tuning guidelines for its parameters. In this technique a cost function in terms of the desired sawtooth period is optimized online by changing the ECCD deposition location based on online estimations of the gradient of the cost function. The controller design does not require a detailed model of the sawtooth instability. Therefore, the proposed ESC is widely applicable to any sawtoothing plasma or plasma simulation and is inherently robust against uncertainties or plasma variations. Moreover, it can handle a broad class of disturbances. This is demonstrated by time-domain simulations, which show successful tracking of time-varying sawtooth period references throughout the whole operating space, even in the presence of variations in plasma parameters, disturbances and slow launcher mirror dynamics. Due to its simplicity and robustness the proposed ESC is a valuable sawtooth control candidate for any experimental tokamak plasma, and may even be applicable to other fusion-related control problems. (paper)
DEFF Research Database (Denmark)
Faber, Michael Havbro; Vrouwenvelder, A.C.W.M.; Sørensen, John Dalsgaard
2011-01-01
In 2005, the Joint Committee on Structural Safety (JCSS) together with Working Commission (WC) 1 of the International Association of Bridge and Structural Engineering (IABSE) organized a workshop on robustness of structures. Two important decisions resulted from this workshop, namely...... ‘COST TU0601: Robustness of Structures’ was initiated in February 2007, aiming to provide a platform for exchanging and promoting research in the area of structural robustness and to provide a basic framework, together with methods, strategies and guidelines enhancing robustness of structures...... the development of a joint European project on structural robustness under the COST (European Cooperation in Science and Technology) programme and the decision to develop a more elaborate document on structural robustness in collaboration between experts from the JCSS and the IABSE. Accordingly, a project titled...
Li, Xiao-Jian; Yang, Guang-Hong
2017-03-01
This paper is concerned with the problem of adaptive fault-tolerant synchronization control of a class of complex dynamical networks (CDNs) with actuator faults and unknown coupling weights. The considered input distribution matrix is assumed to be an arbitrary matrix, instead of a unit one. Within this framework, an adaptive fault-tolerant controller is designed to achieve synchronization for the CDN. Moreover, a convex combination technique and an important graph theory result are developed, such that the rigorous convergence analysis of synchronization errors can be conducted. In particular, it is shown that the proposed fault-tolerant synchronization control approach is valid for the CDN with both time-invariant and time-varying coupling weights. Finally, two simulation examples are provided to validate the effectiveness of the theoretical results.
Doppelhofer, Gernot; Weeks, Melvyn
2011-01-01
This paper investigates the robustness of determinants of economic growth in the presence of model uncertainty, parameter heterogeneity and outliers. The robust model averaging approach introduced in the paper uses a flexible and parsi- monious mixture modeling that allows for fat-tailed errors compared to the normal benchmark case. Applying robust model averaging to growth determinants, the paper finds that eight out of eighteen variables found to be significantly related to economic growth ...
Bishop , Matt; Elliott , Chip
2011-01-01
Part 2: WISE 7; International audience; Robust programming lies at the heart of the type of coding called “secure programming”. Yet it is rarely taught in academia. More commonly, the focus is on how to avoid creating well-known vulnerabilities. While important, that misses the point: a well-structured, robust program should anticipate where problems might arise and compensate for them. This paper discusses one view of robust programming and gives an example of how it may be taught.
ROBUST MPC FOR STABLE LINEAR SYSTEMS
Directory of Open Access Journals (Sweden)
M.A. Rodrigues
2002-03-01
Full Text Available In this paper, a new model predictive controller (MPC, which is robust for a class of model uncertainties, is developed. Systems with stable dynamics and time-invariant model uncertainty are treated. The development herein proposed is focused on real industrial systems where the controller is part of an on-line optimization scheme and works in the output-tracking mode. In addition, the system has a time-varying number of degrees of freedom since some of the manipulated inputs may become constrained. Moreover, the number of controlled outputs may also vary during system operation. Consequently, the actual system may show operating conditions with a number of controlled outputs larger than the number of available manipulated inputs. The proposed controller uses a state-space model, which is aimed at the representation of the output-predicted trajectory. Based on this model, a cost function is proposed whereby the output error is integrated along an infinite prediction horizon. It is considered the case of multiple operating points, where the controller stabilizes a set of models corresponding to different operating conditions for the system. It is shown that closed-loop stability is guaranteed by the feasibility of a linear matrix optimization problem.
Hacker, Andrew
1976-01-01
Provides critical reviews of three books, "The Political Economy of Social Class", "Ethnicity: Theory and Experience," and "Ethnicity in the United States," focusing on the political economy of social class and ethnicity. (Author/AM)
Fernández-Reiriz, M J; Pérez-Camacho, A; Delgado, M; Labarta, U
2007-08-01
This study evaluates the effect of temperature, coupled with ingestion rate, on the dynamics of biochemical components and lipid classes in R. philippinarum. The data are discussed with regard to sexual development and energy balance. Experimental protocol developed in the present study used two groups of the clam R. philippinarum: L (temperatures of 14 degrees C and 18 degrees C) and H (temperatures of 18 degrees C and 22 degrees C). The intra-group ingestion level was similar, although the ingestion level of the clams in the group H was 2.4 times higher than group L. We observed that R. philippinarum conditioned at 18 degrees C (18L) shows higher protein content, furthermore an important loss of organic weight was observed after 48 days. In such a situation, the clams use their own reserves (carbohydrates and glycogen) for sexual development while in situations without food stress (positive energy balance) and low temperature (14 degrees C) an accumulation of reserves is produced. Strikingly dissimilar behaviour in biochemical composition was observed for the 18H and 22H treatments, both with a positive energy balance. Despite similar protein content, the highest levels of carbohydrates were observed at the lower temperature (18 degrees C). Glycogen was also higher for the 18 degrees C treatment, although the differences were significant only in the males. Although the total lipids in R. philippinarum showed no significant differences in any treatment, they became apparent and related to sex when considering the individual lipid classes. There was no variation in lipid classes in the males between the 14L and 22H treatments despite the large disparity in the degree of sexual development. However, in the females significant differences in lipid classes (phospholipids, triglycerides) were observed. The results of this study show that a positive energy balance permits R. philippinarum gonadal development and accumulation of reserves both in low and high temperature
Li, Ning; Cao, Chao; Wang, Cong
2017-06-15
Supporting simultaneous access of machine-type devices is a critical challenge in machine-to-machine (M2M) communications. In this paper, we propose an optimal scheme to dynamically adjust the Access Class Barring (ACB) factor and the number of random access channel (RACH) resources for clustered machine-to-machine (M2M) communications, in which Delay-Sensitive (DS) devices coexist with Delay-Tolerant (DT) ones. In M2M communications, since delay-sensitive devices share random access resources with delay-tolerant devices, reducing the resources consumed by delay-sensitive devices means that there will be more resources available to delay-tolerant ones. Our goal is to optimize the random access scheme, which can not only satisfy the requirements of delay-sensitive devices, but also take the communication quality of delay-tolerant ones into consideration. We discuss this problem from the perspective of delay-sensitive services by adjusting the resource allocation and ACB scheme for these devices dynamically. Simulation results show that our proposed scheme realizes good performance in satisfying the delay-sensitive services as well as increasing the utilization rate of the random access resources allocated to them.
Robust procedures in chemometrics
DEFF Research Database (Denmark)
Kotwa, Ewelina
properties of the analysed data. The broad theoretical background of robust procedures was given as a very useful supplement to the classical methods, and a new tool, based on robust PCA, aiming at identifying Rayleigh and Raman scatters in excitation-mission (EEM) data was developed. The results show...
International Nuclear Information System (INIS)
Chedjou, Jean Chamberlain; Kyamakya, Kyandoghere
2010-01-01
It is well known that a machine vision-based analysis of a dynamic scene, for example in the context of advanced driver assistance systems (ADAS), does require real-time processing capabilities. Therefore, the system used must be capable of performing both robust and ultrafast analyses. Machine vision in ADAS must fulfil the above requirements when dealing with a dynamically changing visual context (i.e. driving in darkness or in a foggy environment, etc). Among the various challenges related to the analysis of a dynamic scene, this paper focuses on contrast enhancement, which is a well-known basic operation to improve the visual quality of an image (dynamic or static) suffering from poor illumination. The key objective is to develop a systematic and fundamental concept for image contrast enhancement that should be robust despite a dynamic environment and that should fulfil the real-time constraints by ensuring an ultrafast analysis. It is demonstrated that the new approach developed in this paper is capable of fulfilling the expected requirements. The proposed approach combines the good features of the 'coupled oscillators'-based signal processing paradigm with the good features of the 'cellular neural network (CNN)'-based one. The first paradigm in this combination is the 'master system' and consists of a set of coupled nonlinear ordinary differential equations (ODEs) that are (a) the so-called 'van der Pol oscillator' and (b) the so-called 'Duffing oscillator'. It is then implemented or realized on top of a 'slave system' platform consisting of a CNN-processors platform. An offline bifurcation analysis is used to find out, a priori, the windows of parameter settings in which the coupled oscillator system exhibits the best and most appropriate behaviours of interest for an optimal resulting image processing quality. In the frame of the extensive bifurcation analysis carried out, analytical formulae have been derived, which are capable of determining the various
Soliton robustness in optical fibers
International Nuclear Information System (INIS)
Menyuk, C.R.
1993-01-01
Simulations and experiments indicate that solitons in optical fibers are robust in the presence of Hamiltonian deformations such as higher-order dispersion and birefringence but are destroyed in the presence of non-Hamiltonian deformations such as attenuation and the Raman effect. Two hypotheses are introduced that generalize these observations and give a recipe for when deformations will be Hamiltonian. Concepts from nonlinear dynamics are used to make these two hypotheses plausible. Soliton stabilization with frequency filtering is also briefly discussed from this point of view
Robustness Beamforming Algorithms
Directory of Open Access Journals (Sweden)
Sajad Dehghani
2014-04-01
Full Text Available Adaptive beamforming methods are known to degrade in the presence of steering vector and covariance matrix uncertinity. In this paper, a new approach is presented to robust adaptive minimum variance distortionless response beamforming make robust against both uncertainties in steering vector and covariance matrix. This method minimize a optimization problem that contains a quadratic objective function and a quadratic constraint. The optimization problem is nonconvex but is converted to a convex optimization problem in this paper. It is solved by the interior-point method and optimum weight vector to robust beamforming is achieved.
Directory of Open Access Journals (Sweden)
W. A. Stygar
2016-07-01
Full Text Available We have developed a conceptual design of a next-generation pulsed-power accelerator that is optimized for megajoule-class dynamic-material-physics experiments. Sufficient electrical energy is delivered by the accelerator to a physics load to achieve—within centimeter-scale samples—material pressures as high as 1 TPa. The accelerator design is based on an architecture that is founded on three concepts: single-stage electrical-pulse compression, impedance matching, and transit-time-isolated drive circuits. The prime power source of the accelerator consists of 600 independent impedance-matched Marx generators. Each Marx comprises eight 5.8-GW bricks connected electrically in series, and generates a 100-ns 46-GW electrical-power pulse. A 450-ns-long water-insulated coaxial-transmission-line impedance transformer transports the power generated by each Marx to a system of twelve 2.5-m-radius water-insulated conical transmission lines. The conical lines are connected electrically in parallel at a 66-cm radius by a water-insulated 45-post sextuple-post-hole convolute. The convolute sums the electrical currents at the outputs of the conical lines, and delivers the combined current to a single solid-dielectric-insulated radial transmission line. The radial line in turn transmits the combined current to the load. Since much of the accelerator is water insulated, we refer to it as Neptune. Neptune is 40 m in diameter, stores 4.8 MJ of electrical energy in its Marx capacitors, and generates 28 TW of peak electrical power. Since the Marxes are transit-time isolated from each other for 900 ns, they can be triggered at different times to construct–over an interval as long as 1 μs–the specific load-current time history required for a given experiment. Neptune delivers 1 MJ and 20 MA in a 380-ns current pulse to an 18-mΩ load; hence Neptune is a megajoule-class 20-MA arbitrary waveform generator. Neptune will allow the international
International Nuclear Information System (INIS)
McMahon, Ryan; Papiez, Lech; Rangaraj, Dharanipathy
2007-01-01
An algorithm is presented that allows for the control of multileaf collimation (MLC) leaves based entirely on real-time calculations of the intensity delivered over the target. The algorithm is capable of efficiently correcting generalized delivery errors without requiring the interruption of delivery (self-correcting trajectories), where a generalized delivery error represents anything that causes a discrepancy between the delivered and intended intensity profiles. The intensity actually delivered over the target is continually compared to its intended value. For each pair of leaves, these comparisons are used to guide the control of the following leaf and keep this discrepancy below a user-specified value. To demonstrate the basic principles of the algorithm, results of corrected delivery are shown for a leading leaf positional error during dynamic-MLC (DMLC) IMRT delivery over a rigid moving target. It is then shown that, with slight modifications, the algorithm can be used to track moving targets in real time. The primary results of this article indicate that the algorithm is capable of accurately delivering DMLC IMRT over a rigid moving target whose motion is (1) completely unknown prior to delivery and (2) not faster than the maximum MLC leaf velocity over extended periods of time. These capabilities are demonstrated for clinically derived intensity profiles and actual tumor motion data, including situations when the target moves in some instances faster than the maximum admissible MLC leaf velocity. The results show that using the algorithm while calculating the delivered intensity every 50 ms will provide a good level of accuracy when delivering IMRT over a rigid moving target translating along the direction of MLC leaf travel. When the maximum velocities of the MLC leaves and target were 4 and 4.2 cm/s, respectively, the resulting error in the two intensity profiles used was 0.1±3.1% and -0.5±2.8% relative to the maximum of the intensity profiles. For
Directory of Open Access Journals (Sweden)
Muhammad Rehan
2012-01-01
Full Text Available Synchronization of chaotic neurons under external electrical stimulation (EES is studied in order to understand information processing in the brain and to improve the methodologies employed in the treatment of cognitive diseases. This paper investigates the dynamics of uncertain coupled chaotic delayed FitzHugh-Nagumo (FHN neurons under EES for incorporated parametric variations. A global nonlinear control law for synchronization of delayed neurons with known parameters is developed. Based on local and global Lipschitz conditions, knowledge of the bounds on the neuronal states, the Lyapunov-Krasovskii functional, and the L2 gain reduction, a less conservative local robust nonlinear control law is formulated to address the problem of robust asymptotic synchronization of delayed FHN neurons under parametric uncertainties. The proposed local control law guarantees both robust stability and robust performance and provides the L2 bound for uncertainty rejection in the synchronization error dynamics. Separate conditions for single-input and multiple-input control schemes for synchronization of a wide class of FHN systems are provided. The results of the proposed techniques are verified through numerical simulations.
Robustness Metrics: Consolidating the multiple approaches to quantify Robustness
DEFF Research Database (Denmark)
Göhler, Simon Moritz; Eifler, Tobias; Howard, Thomas J.
2016-01-01
robustness metrics; 3) Functional expectancy and dispersion robustness metrics; and 4) Probability of conformance robustness metrics. The goal was to give a comprehensive overview of robustness metrics and guidance to scholars and practitioners to understand the different types of robustness metrics...
DEFF Research Database (Denmark)
Vrouwenvelder, T.; Sørensen, John Dalsgaard
2009-01-01
After the collapse of the World Trade Centre towers in 2001 and a number of collapses of structural systems in the beginning of the century, robustness of structural systems has gained renewed interest. Despite many significant theoretical, methodical and technological advances, structural...... of robustness for structural design such requirements are not substantiated in more detail, nor have the engineering profession been able to agree on an interpretation of robustness which facilitates for its uantification. A European COST action TU 601 on ‘Robustness of structures' has started in 2007...... by a group of members of the CSS. This paper describes the ongoing work in this action, with emphasis on the development of a theoretical and risk based quantification and optimization procedure on the one side and a practical pre-normative guideline on the other....
Robustness - theoretical framework
DEFF Research Database (Denmark)
Sørensen, John Dalsgaard; Rizzuto, Enrico; Faber, Michael H.
2010-01-01
More frequent use of advanced types of structures with limited redundancy and serious consequences in case of failure combined with increased requirements to efficiency in design and execution followed by increased risk of human errors has made the need of requirements to robustness of new struct...... of this fact sheet is to describe a theoretical and risk based framework to form the basis for quantification of robustness and for pre-normative guidelines....
Qualitative Robustness in Estimation
Directory of Open Access Journals (Sweden)
Mohammed Nasser
2012-07-01
Full Text Available Normal 0 false false false EN-US X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Times New Roman","serif";} Qualitative robustness, influence function, and breakdown point are three main concepts to judge an estimator from the viewpoint of robust estimation. It is important as well as interesting to study relation among them. This article attempts to present the concept of qualitative robustness as forwarded by first proponents and its later development. It illustrates intricacies of qualitative robustness and its relation with consistency, and also tries to remove commonly believed misunderstandings about relation between influence function and qualitative robustness citing some examples from literature and providing a new counter-example. At the end it places a useful finite and a simulated version of qualitative robustness index (QRI. In order to assess the performance of the proposed measures, we have compared fifteen estimators of correlation coefficient using simulated as well as real data sets.
Weng, Yiqun; Colle, Marivi; Wang, Yuhui; Yang, Luming; Rubinstein, Mor; Sherman, Amir; Ophir, Ron; Grumet, Rebecca
2015-09-01
QTL analysis in multi-development stages with different QTL models identified 12 consensus QTLs underlying fruit elongation and radial growth presenting a dynamic view of genetic control of cucumber fruit development. Fruit size is an important quality trait in cucumber (Cucumis sativus L.) of different market classes. However, the genetic and molecular basis of fruit size variations in cucumber is not well understood. In this study, we conducted QTL mapping of fruit size in cucumber using F2, F2-derived F3 families and recombinant inbred lines (RILs) from a cross between two inbred lines Gy14 (North American picking cucumber) and 9930 (North China fresh market cucumber). Phenotypic data of fruit length and diameter were collected at three development stages (anthesis, immature and mature fruits) in six environments over 4 years. QTL analysis was performed with three QTL models including composite interval mapping (CIM), Bayesian interval mapping (BIM), and multiple QTL mapping (MQM). Twenty-nine consistent and distinct QTLs were detected for nine traits from multiple mapping populations and QTL models. Synthesis of information from available fruit size QTLs allowed establishment of 12 consensus QTLs underlying fruit elongation and radial growth, which presented a dynamic view of genetic control of cucumber fruit development. Results from this study highlighted the benefits of QTL analysis with multiple QTL models and different mapping populations in improving the power of QTL detection. Discussion was presented in the context of domestication and diversifying selection of fruit length and diameter, marker-assisted selection of fruit size, as well as identification of candidate genes for fruit size QTLs in cucumber.
Energy Technology Data Exchange (ETDEWEB)
Wang, Ya; Su, Yingna; Hong, Zhenxiang; Ji, Haisheng [Key Laboratory of DMSA, Purple Mountain Observatory, CAS, Nanjing, 210008 (China); Zeng, Zhicheng; Goode, Philip R.; Cao, Wenda [Big Bear Solar Observatory, 40386 North Shore Lane, Big Bear City, CA 92314 (United States); Ji, Kaifan [Yunnan Astronomical Observatories, Kunming 650011 (China)
2016-12-20
In this paper, we report our first-step results of high resolution He i 10830 Å narrow-band imaging (bandpass: 0.5 Å) of an M1.8 class two-ribbon flare on 2012 July 5. The flare was observed with the 1.6 m aperture New Solar Telescope at Big Bear Solar Observatory. For this unique data set, sunspot dynamics during flaring were analyzed for the first time. By directly imaging the upper chromosphere, running penumbral waves are clearly seen as an outward extension of umbral flashes; both take the form of absorption in the 10830 Å narrow-band images. From a space–time image made of a slit cutting across a flare ribbon and the sunspot, we find that the dark lanes for umbral flashes and penumbral waves are obviously broadened after the flare. The most prominent feature is the sudden appearance of an oscillating absorption strip inside the ribbon when it sweeps into the sunspot’s penumbral and umbral regions. During each oscillation, outwardly propagating umbral flashes and subsequent penumbral waves rush out into the inwardly sweeping ribbon, followed by a return of the absorption strip with similar speed. We tentatively explain the phenomena as the result of a sudden increase in the density of ortho-helium atoms in the area of the sunspot being excited by the flare’s extreme ultraviolet illumination. This explanation is based on the observation that 10830 Å absorption around the sunspot area gets enhanced during the flare. Nevertheless, questions are still open and we need further well-devised observations to investigate the behavior of sunspot dynamics during flares.
Directory of Open Access Journals (Sweden)
E.I. Alexeeva
2008-01-01
Full Text Available An objective of this trial was evaluation of effect of treatment with blocker of tumor necrosis factor infliximab on dynamics of functional class and radiological changes of bone and cartilaginous tissue of joints in children with different clinical types of juvenile arthritis (JA. Infliximab was used according to standard scheme on 0, 2, 6 and then every 8 week by intravenous infusion. Mean single dose of infliximab was 6,8 ± 2,3 mg/kg. All children were treated with immunosuppressive agents (ciclosporin in 6% of patients, methotrexate in 60%, ciclosporin combined with methotrexate — 20%, ciclosporin with leflunomide — 5%, leflunomide with methotreate — 4% combined with anti cytokine treatment. 7 children were treated with oral glucocorticoids in mean dose 0,37 mg/kg daily. disorders in joint function and structural changes of joints of different severity (radiological sign were discovered in all patients before starting of treatment with infliximab. Duration of observation was 6 week — 2 years. Authors made a conclusion that treatment with infliximab prevents progressing of bone and cartilaginous destruction in all types of AJ, not depending on intensity of its clinical activity. This medication provides for full functional recovery of joints and elimination of features of disablement in patients with good clinical activity.Key words: children, juvenile arthritis, infliximab, treatment.
Information theory perspective on network robustness
International Nuclear Information System (INIS)
Schieber, Tiago A.; Carpi, Laura; Frery, Alejandro C.; Rosso, Osvaldo A.; Pardalos, Panos M.; Ravetti, Martín G.
2016-01-01
A crucial challenge in network theory is the study of the robustness of a network when facing a sequence of failures. In this work, we propose a dynamical definition of network robustness based on Information Theory, that considers measurements of the structural changes caused by failures of the network's components. Failures are defined here as a temporal process defined in a sequence. Robustness is then evaluated by measuring dissimilarities between topologies after each time step of the sequence, providing a dynamical information about the topological damage. We thoroughly analyze the efficiency of the method in capturing small perturbations by considering different probability distributions on networks. In particular, we find that distributions based on distances are more consistent in capturing network structural deviations, as better reflect the consequences of the failures. Theoretical examples and real networks are used to study the performance of this methodology. - Highlights: • A novel methodology to measure the robustness of a network to component failure or targeted attacks is proposed. • The use of the network's distance PDF allows a precise analysis. • The method provides a dynamic robustness profile showing the response of the topology to each failure event. • The measure is capable to detect network's critical elements.
Neural network-based robust actuator fault diagnosis for a non-linear multi-tank system.
Mrugalski, Marcin; Luzar, Marcel; Pazera, Marcin; Witczak, Marcin; Aubrun, Christophe
2016-03-01
The paper is devoted to the problem of the robust actuator fault diagnosis of the dynamic non-linear systems. In the proposed method, it is assumed that the diagnosed system can be modelled by the recurrent neural network, which can be transformed into the linear parameter varying form. Such a system description allows developing the designing scheme of the robust unknown input observer within H∞ framework for a class of non-linear systems. The proposed approach is designed in such a way that a prescribed disturbance attenuation level is achieved with respect to the actuator fault estimation error, while guaranteeing the convergence of the observer. The application of the robust unknown input observer enables actuator fault estimation, which allows applying the developed approach to the fault tolerant control tasks. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.
Optimal interdependence enhances robustness of complex systems
Singh, R. K.; Sinha, Sitabhra
2017-01-01
While interdependent systems have usually been associated with increased fragility, we show that strengthening the interdependence between dynamical processes on different networks can make them more robust. By coupling the dynamics of networks that in isolation exhibit catastrophic collapse with extinction of nodal activity, we demonstrate system-wide persistence of activity for an optimal range of interdependence between the networks. This is related to the appearance of attractors of the g...
Parametric uncertainty modeling for robust control
DEFF Research Database (Denmark)
Rasmussen, K.H.; Jørgensen, Sten Bay
1999-01-01
The dynamic behaviour of a non-linear process can often be approximated with a time-varying linear model. In the presented methodology the dynamics is modeled non-conservatively as parametric uncertainty in linear lime invariant models. The obtained uncertainty description makes it possible...... to perform robustness analysis on a control system using the structured singular value. The idea behind the proposed method is to fit a rational function to the parameter variation. The parameter variation can then be expressed as a linear fractional transformation (LFT), It is discussed how the proposed...... point changes. It is shown that a diagonal PI control structure provides robust performance towards variations in feed flow rate or feed concentrations. However including both liquid and vapor flow delays robust performance specifications cannot be satisfied with this simple diagonal control structure...
Tension and robustness in multitasking cellular networks.
Directory of Open Access Journals (Sweden)
Jeffrey V Wong
Full Text Available Cellular networks multitask by exhibiting distinct, context-dependent dynamics. However, network states (parameters that generate a particular dynamic are often sub-optimal for others, defining a source of "tension" between them. Though multitasking is pervasive, it is not clear where tension arises, what consequences it has, and how it is resolved. We developed a generic computational framework to examine the source and consequences of tension between pairs of dynamics exhibited by the well-studied RB-E2F switch regulating cell cycle entry. We found that tension arose from task-dependent shifts in parameters associated with network modules. Although parameter sets common to distinct dynamics did exist, tension reduced both their accessibility and resilience to perturbation, indicating a trade-off between "one-size-fits-all" solutions and robustness. With high tension, robustness can be preserved by dynamic shifting of modules, enabling the network to toggle between tasks, and by increasing network complexity, in this case by gene duplication. We propose that tension is a general constraint on the architecture and operation of multitasking biological networks. To this end, our work provides a framework to quantify the extent of tension between any network dynamics and how it affects network robustness. Such analysis would suggest new ways to interfere with network elements to elucidate the design principles of cellular networks.
Robust Utility Maximization Under Convex Portfolio Constraints
International Nuclear Information System (INIS)
Matoussi, Anis; Mezghani, Hanen; Mnif, Mohamed
2015-01-01
We study a robust maximization problem from terminal wealth and consumption under a convex constraints on the portfolio. We state the existence and the uniqueness of the consumption–investment strategy by studying the associated quadratic backward stochastic differential equation. We characterize the optimal control by using the duality method and deriving a dynamic maximum principle
Robust control investigations for equipment loaded panels
DEFF Research Database (Denmark)
Aglietti, G.S.; Langley, R.S.; Rogers, E.
1998-01-01
This paper develops a modelling technique for equipment load panels which directly produces (adequate) models of the underlying dynamics on which to base robust controller design/evaluations. This technique is based on the use of the Lagrange's equations of motion and the resulting models...
2013-01-01
This contributed volume collects research papers, presented at the CIRP Sponsored Conference Robust Manufacturing Control: Innovative and Interdisciplinary Approaches for Global Networks (RoMaC 2012, Jacobs University, Bremen, Germany, June 18th-20th 2012). These research papers present the latest developments and new ideas focusing on robust manufacturing control for global networks. Today, Global Production Networks (i.e. the nexus of interconnected material and information flows through which products and services are manufactured, assembled and distributed) are confronted with and expected to adapt to: sudden and unpredictable large-scale changes of important parameters which are occurring more and more frequently, event propagation in networks with high degree of interconnectivity which leads to unforeseen fluctuations, and non-equilibrium states which increasingly characterize daily business. These multi-scale changes deeply influence logistic target achievement and call for robust planning and control ...
Directory of Open Access Journals (Sweden)
Orlando – Regalón Anias
2012-11-01
Full Text Available Existen múltiples sistemas dinámicos cuyos modelos matemáticos se caracterizan por ser de primer orden yparámetros variables con el tiempo. En estos casos las herramientas clásicas no siempre logran un sistema decontrol que sea estable, posea un buen desempeño dinámico y rechace adecuadamente las perturbaciones, cuandoel modelo de la planta se desvía del nominal, para el cual se realizó el diseño.En este trabajo se evalúa elcomportamiento de tres estrategias de control en presencia de variación de parámetros. Estas son: control clásico,control adaptable y control robusto. Se realiza un estudio comparativo de las mismas en cuanto a complejidad deldiseño, costo computacional de la implementación y sensibilidad ante variaciones en los parámetros y/o presencia dedisturbios. Se llega a conclusiones que permiten disponer de criterios para la elección más adecuada, endependencia de los requerimientos dinámicos que la aplicación demande, así como de los medios técnicos de que sedisponga.Many dynamic systems have first order mathematic models, with time variable parameters. In these cases, theclassical tools do not satisfy at all control system stability, good performance and perturbation rejection, when theplant model differs from the nominal one, for which the controller was designed.In this article, three control strategiesare evaluated in parameter variations and disturbance presence. The strategies are the followings: classical control,adaptive control and robust control. A comparative study is carried out, taking into account the design complexity, thecomputational cost and the sensitivity. The obtained conclusions helps to provide the criterion to choose the mostadequate control strategy, according to the necessary dynamic, as well as the available technical means.
Acikmese, Behcet A.; Carson, John M., III
2005-01-01
A robustly stabilizing MPC (model predictive control) algorithm for uncertain nonlinear systems is developed that guarantees the resolvability of the associated finite-horizon optimal control problem in a receding-horizon implementation. The control consists of two components; (i) feedforward, and (ii) feedback part. Feed-forward control is obtained by online solution of a finite-horizon optimal control problem for the nominal system dynamics. The feedback control policy is designed off-line based on a bound on the uncertainty in the system model. The entire controller is shown to be robustly stabilizing with a region of attraction composed of initial states for which the finite-horizon optimal control problem is feasible. The controller design for this algorithm is demonstrated on a class of systems with uncertain nonlinear terms that have norm-bounded derivatives, and derivatives in polytopes. An illustrative numerical example is also provided.
Vadivel, P.; Sakthivel, R.; Mathiyalagan, K.; Arunkumar, A.
2013-09-01
This paper addresses the issue of robust state estimation for a class of fuzzy bidirectional associative memory (BAM) neural networks with time-varying delays and parameter uncertainties. By constructing the Lyapunov-Krasovskii functional, which contains the triple-integral term and using the free-weighting matrix technique, a set of sufficient conditions are derived in terms of linear matrix inequalities (LMIs) to estimate the neuron states through available output measurements such that the dynamics of the estimation error system is robustly asymptotically stable. In particular, we consider a generalized activation function in which the traditional assumptions on the boundedness, monotony and differentiability of the activation functions are removed. More precisely, the design of the state estimator for such BAM neural networks can be obtained by solving some LMIs, which are dependent on the size of the time derivative of the time-varying delays. Finally, a numerical example with simulation result is given to illustrate the obtained theoretical results.
International Nuclear Information System (INIS)
Vadivel, P; Sakthivel, R; Mathiyalagan, K; Arunkumar, A
2013-01-01
This paper addresses the issue of robust state estimation for a class of fuzzy bidirectional associative memory (BAM) neural networks with time-varying delays and parameter uncertainties. By constructing the Lyapunov–Krasovskii functional, which contains the triple-integral term and using the free-weighting matrix technique, a set of sufficient conditions are derived in terms of linear matrix inequalities (LMIs) to estimate the neuron states through available output measurements such that the dynamics of the estimation error system is robustly asymptotically stable. In particular, we consider a generalized activation function in which the traditional assumptions on the boundedness, monotony and differentiability of the activation functions are removed. More precisely, the design of the state estimator for such BAM neural networks can be obtained by solving some LMIs, which are dependent on the size of the time derivative of the time-varying delays. Finally, a numerical example with simulation result is given to illustrate the obtained theoretical results. (paper)
DEFF Research Database (Denmark)
Kostiučenko, Oksana; Fiutowski, Jacek; Tamulevicius, Tomas
2014-01-01
Robustness is a key issue for the applications of plasmonic substrates such as tip-enhanced Raman spectroscopy, surface-enhanced spectroscopies, enhanced optical biosensing, optical and optoelectronic plasmonic nanosensors and others. A novel approach for the fabrication of robust plasmonic...... substrates is presented, which relies on the coverage of gold nanostructures with diamond-like carbon (DLC) thin films of thicknesses 25, 55 and 105 nm. DLC thin films were grown by direct hydrocarbon ion beam deposition. In order to find the optimum balance between optical and mechanical properties...
Robust Self Tuning Controllers
DEFF Research Database (Denmark)
Poulsen, Niels Kjølstad
1985-01-01
The present thesis concerns robustness properties of adaptive controllers. It is addressed to methods for robustifying self tuning controllers with respect to abrupt changes in the plant parameters. In the thesis an algorithm for estimating abruptly changing parameters is presented. The estimator...... has several operation modes and a detector for controlling the mode. A special self tuning controller has been developed to regulate plant with changing time delay.......The present thesis concerns robustness properties of adaptive controllers. It is addressed to methods for robustifying self tuning controllers with respect to abrupt changes in the plant parameters. In the thesis an algorithm for estimating abruptly changing parameters is presented. The estimator...
Robust performance results for discrete-time systems
Directory of Open Access Journals (Sweden)
Mahmoud Magdi S.
1997-01-01
Full Text Available The problems of robust performance and feedback control synthesis for a class of linear discrete-time systems with time-varying parametric uncertainties are addressed in this paper. The uncertainties are bound and have a linear matrix fractional form. Based on the concept of strongly robust H ∞ -performance criterion, results of robust stability and performance are developed and expressed in easily computable linear matrix inequalities. Synthesis of robust feedback controllers is carried out for several system models of interest.
Dynamic Network Analysis for Robust Uncertainty Management
2010-03-01
multitarget fusion." IEEE Aerosp. Electron . Syst. Mag., vol. 19, no. 1. pp. 53-64. 2004. |9| K. Kastella. "A maximum likelihood estimator for repon-to-track...These metabolites function as carriers for transferring electrons and certain functional groups (phosphate group, amino group, one carbon unit, methyl... plasm . Thus, the transcription is temporarily terminated by the association with protein IKBQ. The switch protein IKKa itself is also constantly
DEFF Research Database (Denmark)
Rijkhoff, Jan
2007-01-01
in grammatical descriptions of some 50 languages, which together constitute a representative sample of the world’s languages (Hengeveld et al. 2004: 529). It appears that there are both quantitative and qualitative differences between word class systems of individual languages. Whereas some languages employ...... a parts-of-speech system that includes the categories Verb, Noun, Adjective and Adverb, other languages may use only a subset of these four lexical categories. Furthermore, quite a few languages have a major word class whose members cannot be classified in terms of the categories Verb – Noun – Adjective...... – Adverb, because they have properties that are strongly associated with at least two of these four traditional word classes (e.g. Adjective and Adverb). Finally, this article discusses some of the ways in which word class distinctions interact with other grammatical domains, such as syntax and morphology....
Robust Active Portfolio Management
National Research Council Canada - National Science Library
Erdogan, E; Goldfarb, D; Iyengar, G
2006-01-01
... on the portfolio beta, and limits on cash and industry exposure. We show that the optimal portfolios can be computed by solving second-order cone programs -- a class of optimization problems with a worst case complexity (i.e...
Hans, Elias W.; Wullink, Gerhard; van Houdenhoven, Mark; Kazemier, Geert
2008-01-01
We consider the robust surgery loading problem for a hospital’s operating theatre department, which concerns assigning surgeries and sufficient planned slack to operating room days. The objective is to maximize capacity utilization and minimize the risk of overtime, and thus cancelled patients. This
Robustness Envelopes of Networks
Trajanovski, S.; Martín-Hernández, J.; Winterbach, W.; Van Mieghem, P.
2013-01-01
We study the robustness of networks under node removal, considering random node failure, as well as targeted node attacks based on network centrality measures. Whilst both of these have been studied in the literature, existing approaches tend to study random failure in terms of average-case
Cruz, Jorddy N; Costa, José F S; Khayat, André S; Kuca, Kamil; Barros, Carlos A L; Neto, A M J C
2018-05-04
In this work, the binding mechanism of new Polyketide Synthase 13 (Pks13) inhibitors has been studied through molecular dynamics simulation and free energy calculations. The drug Tam1 and its analogs, belonging to the benzofuran class, were submitted to 100 ns simulations, and according to the results obtained for root mean square deviation, all the simulations converged from approximately 30 ns. For the analysis of backbone flotation, the root mean square fluctuations were plotted for the Cα atoms; analysis revealed that the greatest fluctuation occurred in the residues that are part of the protein lid domain. The binding free energy value (ΔG bind ) obtained for the Tam16 lead molecule was of -51.43 kcal/mol. When comparing this result with the ΔG bind values for the remaining analogs, the drug Tam16 was found to be the highest ranked: this result is in agreement with the experimental results obtained by Aggarwal and collaborators, where it was verified that the IC 50 for Tam16 is the smallest necessary to inhibit the Pks13 (IC 50 = 0.19 μM). The energy decomposition analysis suggested that the residues which most interact with inhibitors are: Ser1636, Tyr1637, Asn1640, Ala1667, Phe1670, and Tyr1674, from which the greatest energy contribution to Phe1670 was particularly notable. For the lead molecule Tam16, a hydrogen bond with the hydroxyl of the phenol not observed in the other analogs induced a more stable molecular structure. Aggarwal and colleagues reported this hydrogen bonding as being responsible for the stability of the molecule, optimizing its physic-chemical, toxicological, and pharmacokinetic properties.
Measure of robustness for complex networks
Youssef, Mina Nabil
Critical infrastructures are repeatedly attacked by external triggers causing tremendous amount of damages. Any infrastructure can be studied using the powerful theory of complex networks. A complex network is composed of extremely large number of different elements that exchange commodities providing significant services. The main functions of complex networks can be damaged by different types of attacks and failures that degrade the network performance. These attacks and failures are considered as disturbing dynamics, such as the spread of viruses in computer networks, the spread of epidemics in social networks, and the cascading failures in power grids. Depending on the network structure and the attack strength, every network differently suffers damages and performance degradation. Hence, quantifying the robustness of complex networks becomes an essential task. In this dissertation, new metrics are introduced to measure the robustness of technological and social networks with respect to the spread of epidemics, and the robustness of power grids with respect to cascading failures. First, we introduce a new metric called the Viral Conductance (VCSIS ) to assess the robustness of networks with respect to the spread of epidemics that are modeled through the susceptible/infected/susceptible (SIS) epidemic approach. In contrast to assessing the robustness of networks based on a classical metric, the epidemic threshold, the new metric integrates the fraction of infected nodes at steady state for all possible effective infection strengths. Through examples, VCSIS provides more insights about the robustness of networks than the epidemic threshold. In addition, both the paradoxical robustness of Barabasi-Albert preferential attachment networks and the effect of the topology on the steady state infection are studied, to show the importance of quantifying the robustness of networks. Second, a new metric VCSIR is introduced to assess the robustness of networks with respect
Class size versus class composition
DEFF Research Database (Denmark)
Jones, Sam
Raising schooling quality in low-income countries is a pressing challenge. Substantial research has considered the impact of cutting class sizes on skills acquisition. Considerably less attention has been given to the extent to which peer effects, which refer to class composition, also may affect...... bias from omitted variables, the preferred IV results indicate considerable negative effects due to larger class sizes and larger numbers of overage-for-grade peers. The latter, driven by the highly prevalent practices of grade repetition and academic redshirting, should be considered an important...
Criteria for robustness of heteroclinic cycles in neural microcircuits
2011-01-01
We introduce a test for robustness of heteroclinic cycles that appear in neural microcircuits modeled as coupled dynamical cells. Robust heteroclinic cycles (RHCs) can appear as robust attractors in Lotka-Volterra-type winnerless competition (WLC) models as well as in more general coupled and/or symmetric systems. It has been previously suggested that RHCs may be relevant to a range of neural activities, from encoding and binding to spatio-temporal sequence generation. The robustness or otherwise of such cycles depends both on the coupling structure and the internal structure of the neurons. We verify that robust heteroclinic cycles can appear in systems of three identical cells, but only if we require perturbations to preserve some invariant subspaces for the individual cells. On the other hand, heteroclinic attractors can appear robustly in systems of four or more identical cells for some symmetric coupling patterns, without restriction on the internal dynamics of the cells. PMID:22656192
Passivity analysis of higher order evolutionary dynamics and population games
Mabrok, Mohamed
2017-01-05
Evolutionary dynamics describe how the population composition changes in response to the fitness levels, resulting in a closed-loop feedback system. Recent work established a connection between passivity theory and certain classes of population games, namely so-called “stable games”. In particular, it was shown that a combination of stable games and (an analogue of) passive evolutionary dynamics results in stable convergence to Nash equilibrium. This paper considers the converse question of necessary conditions for evolutionary dynamics to exhibit stable behaviors for all generalized stable games. Using methods from robust control analysis, we show that if an evolutionary dynamic does not satisfy a passivity property, then it is possible to construct a generalized stable game that results in instability. The results are illustrated on selected evolutionary dynamics with particular attention to replicator dynamics, which are also shown to be lossless, a special class of passive systems.
Adaptive Critic Nonlinear Robust Control: A Survey.
Wang, Ding; He, Haibo; Liu, Derong
2017-10-01
Adaptive dynamic programming (ADP) and reinforcement learning are quite relevant to each other when performing intelligent optimization. They are both regarded as promising methods involving important components of evaluation and improvement, at the background of information technology, such as artificial intelligence, big data, and deep learning. Although great progresses have been achieved and surveyed when addressing nonlinear optimal control problems, the research on robustness of ADP-based control strategies under uncertain environment has not been fully summarized. Hence, this survey reviews the recent main results of adaptive-critic-based robust control design of continuous-time nonlinear systems. The ADP-based nonlinear optimal regulation is reviewed, followed by robust stabilization of nonlinear systems with matched uncertainties, guaranteed cost control design of unmatched plants, and decentralized stabilization of interconnected systems. Additionally, further comprehensive discussions are presented, including event-based robust control design, improvement of the critic learning rule, nonlinear H ∞ control design, and several notes on future perspectives. By applying the ADP-based optimal and robust control methods to a practical power system and an overhead crane plant, two typical examples are provided to verify the effectiveness of theoretical results. Overall, this survey is beneficial to promote the development of adaptive critic control methods with robustness guarantee and the construction of higher level intelligent systems.
Emergence of robustness in networks of networks
Roth, Kevin; Morone, Flaviano; Min, Byungjoon; Makse, Hernán A.
2017-06-01
A model of interdependent networks of networks (NONs) was introduced recently [Proc. Natl. Acad. Sci. (USA) 114, 3849 (2017), 10.1073/pnas.1620808114] in the context of brain activation to identify the neural collective influencers in the brain NON. Here we investigate the emergence of robustness in such a model, and we develop an approach to derive an exact expression for the random percolation transition in Erdös-Rényi NONs of this kind. Analytical calculations are in agreement with numerical simulations, and highlight the robustness of the NON against random node failures, which thus presents a new robust universality class of NONs. The key aspect of this robust NON model is that a node can be activated even if it does not belong to the giant mutually connected component, thus allowing the NON to be built from below the percolation threshold, which is not possible in previous models of interdependent networks. Interestingly, the phase diagram of the model unveils particular patterns of interconnectivity for which the NON is most vulnerable, thereby marking the boundary above which the robustness of the system improves with increasing dependency connections.
Robust Parametric Control of Spacecraft Rendezvous
Directory of Open Access Journals (Sweden)
Dake Gu
2014-01-01
Full Text Available This paper proposes a method to design the robust parametric control for autonomous rendezvous of spacecrafts with the inertial information with uncertainty. We consider model uncertainty of traditional C-W equation to formulate the dynamic model of the relative motion. Based on eigenstructure assignment and model reference theory, a concise control law for spacecraft rendezvous is proposed which could be fixed through solving an optimization problem. The cost function considers the stabilization of the system and other performances. Simulation results illustrate the robustness and effectiveness of the proposed control.
Robust-mode analysis of hydrodynamic flows
Roy, Sukesh; Gord, James R.; Hua, Jia-Chen; Gunaratne, Gemunu H.
2017-04-01
The emergence of techniques to extract high-frequency high-resolution data introduces a new avenue for modal decomposition to assess the underlying dynamics, especially of complex flows. However, this task requires the differentiation of robust, repeatable flow constituents from noise and other irregular features of a flow. Traditional approaches involving low-pass filtering and principle components analysis have shortcomings. The approach outlined here, referred to as robust-mode analysis, is based on Koopman decomposition. Three applications to (a) a counter-rotating cellular flame state, (b) variations in financial markets, and (c) turbulent injector flows are provided.
Kutzner, Florian; Vogel, Tobias; Freytag, Peter; Fiedler, Klaus
2011-01-01
In the present research, we argue for the robustness of illusory correlations (ICs, Hamilton & Gifford, 1976) regarding two boundary conditions suggested in previous research. First, we argue that ICs are maintained under extended experience. Using simulations, we derive conflicting predictions. Whereas noise-based accounts predict ICs to be maintained (Fielder, 2000; Smith, 1991), a prominent account based on discrepancy-reducing feedback learning predicts ICs to disappear (Van Rooy et al., 2003). An experiment involving 320 observations with majority and minority members supports the claim that ICs are maintained. Second, we show that actively using the stereotype to make predictions that are met with reward and punishment does not eliminate the bias. In addition, participants' operant reactions afford a novel online measure of ICs. In sum, our findings highlight the robustness of ICs that can be explained as a result of unbiased but noisy learning.
Eggenberg, Niklaus; Salani, Matteo; Bierlaire, Michel
2010-01-01
Due to economic pressure industries, when planning, tend to focus on optimizing the expected profit or the yield. The consequence of highly optimized solutions is an increased sensitivity to uncertainty. This generates additional "operational" costs, incurred by possible modifications of the original plan to be performed when reality does not reflect what was expected in the planning phase. The modern research trend focuses on "robustness" of solutions instead of yield or profit. Although ro...
Directory of Open Access Journals (Sweden)
Marek Hicar
2004-01-01
Full Text Available The article is about a control design for complete structure of the crane: crab, bridge and crane uplift.The most important unknown parameters for simulations are burden weight and length of hanging rope. We will use robustcontrol for crab and bridge control to ensure adaptivity for burden weight and rope length. Robust control will be designed for current control of the crab and bridge, necessary is to know the range of unknown parameters. Whole robust will be splitto subintervals and after correct identification of unknown parameters the most suitable robust controllers will be chosen.The most important condition at the crab and bridge motion is avoiding from burden swinging in the final position. Crab and bridge drive is designed by asynchronous motor fed from frequency converter. We will use crane uplift with burden weightobserver in combination for uplift, crab and bridge drive with cooperation of their parameters: burden weight, rope length and crab and bridge position. Controllers are designed by state control method. We will use preferably a disturbance observerwhich will identify burden weight as a disturbance. The system will be working in both modes at empty hook as well asat maximum load: burden uplifting and dropping down.
DEFF Research Database (Denmark)
Aktor, Mikael
2018-01-01
. Although this social structure was ideal in nature and not equally confirmed in other genres of ancient and medieval literature, it has nevertheless had an immense impact on Indian society. The chapter presents an overview of the system with its three privileged classes, the Brahmins, the Kṣatriyas......The notions of class (varṇa) and caste (jāti) run through the dharmaśāstra literature (i.e. Hindu Law Books) on all levels. They regulate marriage, economic transactions, work, punishment, penance, entitlement to rituals, identity markers like the sacred thread, and social interaction in general...
International Nuclear Information System (INIS)
Peng Yafu
2009-01-01
In this paper, a robust intelligent sliding model control (RISMC) scheme using an adaptive recurrent cerebellar model articulation controller (RCMAC) is developed for a class of uncertain nonlinear chaotic systems. This RISMC system offers a design approach to drive the state trajectory to track a desired trajectory, and it is comprised of an adaptive RCMAC and a robust controller. The adaptive RCMAC is used to mimic an ideal sliding mode control (SMC) due to unknown system dynamics, and a robust controller is designed to recover the residual approximation error for guaranteeing the stable characteristic. Moreover, the Taylor linearization technique is employed to derive the linearized model of the RCMAC. The all adaptation laws of the RISMC system are derived based on the Lyapunov stability analysis and projection algorithm, so that the stability of the system can be guaranteed. Finally, the proposed RISMC system is applied to control a Van der Pol oscillator, a Genesio chaotic system and a Chua's chaotic circuit. The effectiveness of the proposed control scheme is verified by some simulation results with unknown system dynamics and existence of external disturbance. In addition, the advantages of the proposed RISMC are indicated in comparison with a SMC system
Directory of Open Access Journals (Sweden)
Orlando Regalón Anias
2012-11-01
Full Text Available Existen múltiples sistemas dinámicos cuyos modelos matemáticos se caracterizan por ser de primer orden y parámetros variables con el tiempo. En estos casos las herramientas clásicas no siempre logran un sistema decontrol que sea estable, posea un buen desempeño dinámico y rechace adecuadamente las perturbaciones, cuando el modelo de la planta se desvía del nominal, para el cual se realizó el diseño.En este trabajo se evalúa el comportamiento de tres estrategias de control en presencia de variación de parámetros. Estas son: control clásico, control adaptable y control robusto. Se realiza un estudio comparativo de las mismas en cuanto a complejidad del diseño, costo computacional de la implementación y sensibilidad ante variaciones en los parámetros y/o presencia de disturbios. Se llega a conclusiones que permiten disponer de criterios para la elección más adecuada, en dependencia de los requerimientos dinámicos que la aplicación demande, así como de los medios técnicos de que se disponga. Many dynamic systems have first order mathematic models, with time variable parameters. In these cases, the classical tools do not satisfy at all control system stability, good performance and perturbation rejection, when the plant model differs from the nominal one, for which the controller was designed.In this article, three control strategies are evaluated in parameter variations and disturbance presence. The strategies are the followings: classical control, adaptive control and robust control. A comparative study is carried out, taking into account the design complexity, the computational cost and the sensitivity. The obtained conclusions helps to provide the criterion to choose the mostadequate control strategy, according to the necessary dynamic, as well as the available technical means.
... management options. Breastfeeding basics. Caring for baby at home. Birthing classes are not just for new parents, though. ... midwife. Postpartum care. Caring for your baby at home, including baby first aid. Lamaze One of the most popular birthing techniques in the U.S., Lamaze has been around ...
Muscle Synergy-Driven Robust Motion Control.
Min, Kyuengbo; Iwamoto, Masami; Kakei, Shinji; Kimpara, Hideyuki
2018-04-01
Humans are able to robustly maintain desired motion and posture under dynamically changing circumstances, including novel conditions. To accomplish this, the brain needs to optimize the synergistic control between muscles against external dynamic factors. However, previous related studies have usually simplified the control of multiple muscles using two opposing muscles, which are minimum actuators to simulate linear feedback control. As a result, they have been unable to analyze how muscle synergy contributes to motion control robustness in a biological system. To address this issue, we considered a new muscle synergy concept used to optimize the synergy between muscle units against external dynamic conditions, including novel conditions. We propose that two main muscle control policies synergistically control muscle units to maintain the desired motion against external dynamic conditions. Our assumption is based on biological evidence regarding the control of multiple muscles via the corticospinal tract. One of the policies is the group control policy (GCP), which is used to control muscle group units classified based on functional similarities in joint control. This policy is used to effectively resist external dynamic circumstances, such as disturbances. The individual control policy (ICP) assists the GCP in precisely controlling motion by controlling individual muscle units. To validate this hypothesis, we simulated the reinforcement of the synergistic actions of the two control policies during the reinforcement learning of feedback motion control. Using this learning paradigm, the two control policies were synergistically combined to result in robust feedback control under novel transient and sustained disturbances that did not involve learning. Further, by comparing our data to experimental data generated by human subjects under the same conditions as those of the simulation, we showed that the proposed synergy concept may be used to analyze muscle synergy
Occupant behaviour and robustness of building design
DEFF Research Database (Denmark)
Buso, Tiziana; Fabi, Valentina; Andersen, Rune Korsholm
2015-01-01
in a dynamic building energy simulation tool (IDA ICE). The analysis was carried out by simulating 15 building envelope designs in different thermal zones of an Office Reference Building in 3 climates: Stockholm, Frankfurt and Athens.In general, robustness towards changes in occupants' behaviour increased......Occupant behaviour can cause major discrepancies between the designed and the real total energy use in buildings. A possible solution to reduce the differences between predictions and actual performances is designing robust buildings, i.e. buildings whose performances show little variations...... with alternating occupant behaviour patterns. The aim of this work was to investigate how alternating occupant behaviour patterns impact the performance of different envelope design solutions in terms of building robustness. Probabilistic models of occupants' window opening and use of shading were implemented...
Robustness of Distance-to-Default
DEFF Research Database (Denmark)
Jessen, Cathrine; Lando, David
2013-01-01
Distance-to-default is a remarkably robust measure for ranking firms according to their risk of default. The ranking seems to work despite the fact that the Merton model from which the measure is derived produces default probabilities that are far too small when applied to real data. We use...... simulations to investigate the robustness of the distance-to-default measure to different model specifications. Overall we find distance-to-default to be robust to a number of deviations from the simple Merton model that involve different asset value dynamics and different default triggering mechanisms....... A notable exception is a model with stochastic volatility of assets. In this case both the ranking of firms and the estimated default probabilities using distance-to-default perform significantly worse. We therefore propose a volatility adjustment of the distance-to-default measure, that significantly...
Robustness of cooperation in the evolutionary prisoner's dilemma on complex networks
International Nuclear Information System (INIS)
Poncela, J; Gomez-Gardenes, J; FlorIa, L M; Moreno, Y
2007-01-01
Recent studies on the evolutionary dynamics of the prisoner's dilemma game in scale-free networks have demonstrated that the heterogeneity of the network interconnections enhances the evolutionary success of cooperation. In this paper we address the issue of how the characterization of the asymptotic states of the evolutionary dynamics depends on the initial concentration of cooperators. We find that the measure and the connectedness properties of the set of nodes where cooperation reaches fixation is largely independent of initial conditions, in contrast with the behaviour of both the set of nodes where defection is fixed, and the fluctuating nodes. We also check for the robustness of these results when varying the degree heterogeneity along a one-parametric family of networks interpolating between the class of Erdos-Renyi graphs and the Barabasi-Albert networks
Robust estimation for ordinary differential equation models.
Cao, J; Wang, L; Xu, J
2011-12-01
Applied scientists often like to use ordinary differential equations (ODEs) to model complex dynamic processes that arise in biology, engineering, medicine, and many other areas. It is interesting but challenging to estimate ODE parameters from noisy data, especially when the data have some outliers. We propose a robust method to address this problem. The dynamic process is represented with a nonparametric function, which is a linear combination of basis functions. The nonparametric function is estimated by a robust penalized smoothing method. The penalty term is defined with the parametric ODE model, which controls the roughness of the nonparametric function and maintains the fidelity of the nonparametric function to the ODE model. The basis coefficients and ODE parameters are estimated in two nested levels of optimization. The coefficient estimates are treated as an implicit function of ODE parameters, which enables one to derive the analytic gradients for optimization using the implicit function theorem. Simulation studies show that the robust method gives satisfactory estimates for the ODE parameters from noisy data with outliers. The robust method is demonstrated by estimating a predator-prey ODE model from real ecological data. © 2011, The International Biometric Society.
Robust and Adaptive Control With Aerospace Applications
Lavretsky, Eugene
2013-01-01
Robust and Adaptive Control shows the reader how to produce consistent and accurate controllers that operate in the presence of uncertainties and unforeseen events. Driven by aerospace applications the focus of the book is primarily on continuous-dynamical systems. The text is a three-part treatment, beginning with robust and optimal linear control methods and moving on to a self-contained presentation of the design and analysis of model reference adaptive control (MRAC) for nonlinear uncertain dynamical systems. Recent extensions and modifications to MRAC design are included, as are guidelines for combining robust optimal and MRAC controllers. Features of the text include: · case studies that demonstrate the benefits of robust and adaptive control for piloted, autonomous and experimental aerial platforms; · detailed background material for each chapter to motivate theoretical developments; · realistic examples and simulation data illustrating key features ...
Robust efficient video fingerprinting
Puri, Manika; Lubin, Jeffrey
2009-02-01
We have developed a video fingerprinting system with robustness and efficiency as the primary and secondary design criteria. In extensive testing, the system has shown robustness to cropping, letter-boxing, sub-titling, blur, drastic compression, frame rate changes, size changes and color changes, as well as to the geometric distortions often associated with camcorder capture in cinema settings. Efficiency is afforded by a novel two-stage detection process in which a fast matching process first computes a number of likely candidates, which are then passed to a second slower process that computes the overall best match with minimal false alarm probability. One key component of the algorithm is a maximally stable volume computation - a three-dimensional generalization of maximally stable extremal regions - that provides a content-centric coordinate system for subsequent hash function computation, independent of any affine transformation or extensive cropping. Other key features include an efficient bin-based polling strategy for initial candidate selection, and a final SIFT feature-based computation for final verification. We describe the algorithm and its performance, and then discuss additional modifications that can provide further improvement to efficiency and accuracy.
DEFF Research Database (Denmark)
Ejsing-Duun, Stine; Hansbøl, Mikala
Denne rapport rummer evaluering og dokumentation af Coding Class projektet1. Coding Class projektet blev igangsat i skoleåret 2016/2017 af IT-Branchen i samarbejde med en række medlemsvirksomheder, Københavns kommune, Vejle Kommune, Styrelsen for IT- og Læring (STIL) og den frivillige forening...... Coding Pirates2. Rapporten er forfattet af Docent i digitale læringsressourcer og forskningskoordinator for forsknings- og udviklingsmiljøet Digitalisering i Skolen (DiS), Mikala Hansbøl, fra Institut for Skole og Læring ved Professionshøjskolen Metropol; og Lektor i læringsteknologi, interaktionsdesign......, design tænkning og design-pædagogik, Stine Ejsing-Duun fra Forskningslab: It og Læringsdesign (ILD-LAB) ved Institut for kommunikation og psykologi, Aalborg Universitet i København. Vi har fulgt og gennemført evaluering og dokumentation af Coding Class projektet i perioden november 2016 til maj 2017...
Matlab as a robust control design tool
Gregory, Irene M.
1994-01-01
This presentation introduces Matlab as a tool used in flight control research. The example used to illustrate some of the capabilities of this software is a robust controller designed for a single stage to orbit air breathing vehicles's ascent to orbit. The global requirements of the controller are to stabilize the vehicle and follow a trajectory in the presence of atmospheric disturbances and strong dynamic coupling between airframe and propulsion.
Effect of smoothing on robust chaos.
Deshpande, Amogh; Chen, Qingfei; Wang, Yan; Lai, Ying-Cheng; Do, Younghae
2010-08-01
In piecewise-smooth dynamical systems, situations can arise where the asymptotic attractors of the system in an open parameter interval are all chaotic (e.g., no periodic windows). This is the phenomenon of robust chaos. Previous works have established that robust chaos can occur through the mechanism of border-collision bifurcation, where border is the phase-space region where discontinuities in the derivatives of the dynamical equations occur. We investigate the effect of smoothing on robust chaos and find that periodic windows can arise when a small amount of smoothness is present. We introduce a parameter of smoothing and find that the measure of the periodic windows in the parameter space scales linearly with the parameter, regardless of the details of the smoothing function. Numerical support and a heuristic theory are provided to establish the scaling relation. Experimental evidence of periodic windows in a supposedly piecewise linear dynamical system, which has been implemented as an electronic circuit, is also provided.
Nonlinear robust hierarchical control for nonlinear uncertain systems
Directory of Open Access Journals (Sweden)
Leonessa Alexander
1999-01-01
Full Text Available A nonlinear robust control-system design framework predicated on a hierarchical switching controller architecture parameterized over a set of moving nominal system equilibria is developed. Specifically, using equilibria-dependent Lyapunov functions, a hierarchical nonlinear robust control strategy is developed that robustly stabilizes a given nonlinear system over a prescribed range of system uncertainty by robustly stabilizing a collection of nonlinear controlled uncertain subsystems. The robust switching nonlinear controller architecture is designed based on a generalized (lower semicontinuous Lyapunov function obtained by minimizing a potential function over a given switching set induced by the parameterized nominal system equilibria. The proposed framework robustly stabilizes a compact positively invariant set of a given nonlinear uncertain dynamical system with structured parametric uncertainty. Finally, the efficacy of the proposed approach is demonstrated on a jet engine propulsion control problem with uncertain pressure-flow map data.
Robust automated knowledge capture.
Energy Technology Data Exchange (ETDEWEB)
Stevens-Adams, Susan Marie; Abbott, Robert G.; Forsythe, James Chris; Trumbo, Michael Christopher Stefan; Haass, Michael Joseph; Hendrickson, Stacey M. Langfitt
2011-10-01
This report summarizes research conducted through the Sandia National Laboratories Robust Automated Knowledge Capture Laboratory Directed Research and Development project. The objective of this project was to advance scientific understanding of the influence of individual cognitive attributes on decision making. The project has developed a quantitative model known as RumRunner that has proven effective in predicting the propensity of an individual to shift strategies on the basis of task and experience related parameters. Three separate studies are described which have validated the basic RumRunner model. This work provides a basis for better understanding human decision making in high consequent national security applications, and in particular, the individual characteristics that underlie adaptive thinking.
Passion, Robustness and Perseverance
DEFF Research Database (Denmark)
Lim, Miguel Antonio; Lund, Rebecca
2016-01-01
Evaluation and merit in the measured university are increasingly based on taken-for-granted assumptions about the “ideal academic”. We suggest that the scholar now needs to show that she is passionate about her work and that she gains pleasure from pursuing her craft. We suggest that passion...... and pleasure achieve an exalted status as something compulsory. The scholar ought to feel passionate about her work and signal that she takes pleasure also in the difficult moments. Passion has become a signal of robustness and perseverance in a job market characterised by funding shortages, increased pressure...... way to demonstrate their potential and, crucially, their passion for their work. Drawing on the literature on technologies of governance, we reflect on what is captured and what is left out by these two evaluation instruments. We suggest that bibliometric analysis at the individual level is deeply...
Robust Optical Flow Estimation
Directory of Open Access Journals (Sweden)
Javier Sánchez Pérez
2013-10-01
Full Text Available n this work, we describe an implementation of the variational method proposed by Brox etal. in 2004, which yields accurate optical flows with low running times. It has several benefitswith respect to the method of Horn and Schunck: it is more robust to the presence of outliers,produces piecewise-smooth flow fields and can cope with constant brightness changes. Thismethod relies on the brightness and gradient constancy assumptions, using the information ofthe image intensities and the image gradients to find correspondences. It also generalizes theuse of continuous L1 functionals, which help mitigate the effect of outliers and create a TotalVariation (TV regularization. Additionally, it introduces a simple temporal regularizationscheme that enforces a continuous temporal coherence of the flow fields.
Robust Multimodal Dictionary Learning
Cao, Tian; Jojic, Vladimir; Modla, Shannon; Powell, Debbie; Czymmek, Kirk; Niethammer, Marc
2014-01-01
We propose a robust multimodal dictionary learning method for multimodal images. Joint dictionary learning for both modalities may be impaired by lack of correspondence between image modalities in training data, for example due to areas of low quality in one of the modalities. Dictionaries learned with such non-corresponding data will induce uncertainty about image representation. In this paper, we propose a probabilistic model that accounts for image areas that are poorly corresponding between the image modalities. We cast the problem of learning a dictionary in presence of problematic image patches as a likelihood maximization problem and solve it with a variant of the EM algorithm. Our algorithm iterates identification of poorly corresponding patches and re-finements of the dictionary. We tested our method on synthetic and real data. We show improvements in image prediction quality and alignment accuracy when using the method for multimodal image registration. PMID:24505674
Robust snapshot interferometric spectropolarimetry.
Kim, Daesuk; Seo, Yoonho; Yoon, Yonghee; Dembele, Vamara; Yoon, Jae Woong; Lee, Kyu Jin; Magnusson, Robert
2016-05-15
This Letter describes a Stokes vector measurement method based on a snapshot interferometric common-path spectropolarimeter. The proposed scheme, which employs an interferometric polarization-modulation module, can extract the spectral polarimetric parameters Ψ(k) and Δ(k) of a transmissive anisotropic object by which an accurate Stokes vector can be calculated in the spectral domain. It is inherently strongly robust to the object 3D pose variation, since it is designed distinctly so that the measured object can be placed outside of the interferometric module. Experiments are conducted to verify the feasibility of the proposed system. The proposed snapshot scheme enables us to extract the spectral Stokes vector of a transmissive anisotropic object within tens of msec with high accuracy.
International Conference on Robust Statistics
Filzmoser, Peter; Gather, Ursula; Rousseeuw, Peter
2003-01-01
Aspects of Robust Statistics are important in many areas. Based on the International Conference on Robust Statistics 2001 (ICORS 2001) in Vorau, Austria, this volume discusses future directions of the discipline, bringing together leading scientists, experienced researchers and practitioners, as well as younger researchers. The papers cover a multitude of different aspects of Robust Statistics. For instance, the fundamental problem of data summary (weights of evidence) is considered and its robustness properties are studied. Further theoretical subjects include e.g.: robust methods for skewness, time series, longitudinal data, multivariate methods, and tests. Some papers deal with computational aspects and algorithms. Finally, the aspects of application and programming tools complete the volume.
Automatic Synthesis of Robust and Optimal Controllers
DEFF Research Database (Denmark)
Cassez, Franck; Jessen, Jan Jacob; Larsen, Kim Guldstrand
2009-01-01
In this paper, we show how to apply recent tools for the automatic synthesis of robust and near-optimal controllers for a real industrial case study. We show how to use three different classes of models and their supporting existing tools, Uppaal-TiGA for synthesis, phaver for verification......, and Simulink for simulation, in a complementary way. We believe that this case study shows that our tools have reached a level of maturity that allows us to tackle interesting and relevant industrial control problems....
Robust classification using mixtures of dependency networks
DEFF Research Database (Denmark)
Gámez, José A.; Mateo, Juan L.; Nielsen, Thomas Dyhre
2008-01-01
Dependency networks have previously been proposed as alternatives to e.g. Bayesian networks by supporting fast algorithms for automatic learning. Recently dependency networks have also been proposed as classiﬁcation models, but as with e.g. general probabilistic inference, the reported speed......-ups are often obtained at the expense of accuracy. In this paper we try to address this issue through the use of mixtures of dependency networks. To reduce learning time and improve robustness when dealing with data sparse classes, we outline methods for reusing calculations across mixture components. Finally...
Robustness Analyses of Timber Structures
DEFF Research Database (Denmark)
Kirkegaard, Poul Henning; Sørensen, John Dalsgaard; Hald, Frederik
2013-01-01
The robustness of structural systems has obtained a renewed interest arising from a much more frequent use of advanced types of structures with limited redundancy and serious consequences in case of failure. In order to minimise the likelihood of such disproportionate structural failures, many mo...... with respect to robustness of timber structures and will discuss the consequences of such robustness issues related to the future development of timber structures.......The robustness of structural systems has obtained a renewed interest arising from a much more frequent use of advanced types of structures with limited redundancy and serious consequences in case of failure. In order to minimise the likelihood of such disproportionate structural failures, many...... modern building codes consider the need for the robustness of structures and provide strategies and methods to obtain robustness. Therefore, a structural engineer may take necessary steps to design robust structures that are insensitive to accidental circumstances. The present paper summaries issues...
Heck, A.; Houwing, H.; de Beurs, C.
2009-01-01
In 2007, a small team of university and secondary school mathematics teachers jointly developed and piloted an e-class for 4th and 5th grade students (age: 16-17yrs) at both pre-university and general vocational level. The goal was to develop and try out innovative ways of teaching mathematics that
Robust Trajectory Design in Highly Perturbed Environments Leveraging Continuation Methods, Phase I
National Aeronautics and Space Administration — Research is proposed to investigate continuation methods to improve the robustness of trajectory design algorithms for spacecraft in highly perturbed dynamical...
Robust digital processing of speech signals
Kovacevic, Branko; Veinović, Mladen; Marković, Milan
2017-01-01
This book focuses on speech signal phenomena, presenting a robustification of the usual speech generation models with regard to the presumed types of excitation signals, which is equivalent to the introduction of a class of nonlinear models and the corresponding criterion functions for parameter estimation. Compared to the general class of nonlinear models, such as various neural networks, these models possess good properties of controlled complexity, the option of working in “online” mode, as well as a low information volume for efficient speech encoding and transmission. Providing comprehensive insights, the book is based on the authors’ research, which has already been published, supplemented by additional texts discussing general considerations of speech modeling, linear predictive analysis and robust parameter estimation.
Goodman, Lawrence E
2001-01-01
Beginning text presents complete theoretical treatment of mechanical model systems and deals with technological applications. Topics include introduction to calculus of vectors, particle motion, dynamics of particle systems and plane rigid bodies, technical applications in plane motions, theory of mechanical vibrations, and more. Exercises and answers appear in each chapter.
Shah, Sohil Atul; Koltun, Vladlen
2017-09-12
Clustering is a fundamental procedure in the analysis of scientific data. It is used ubiquitously across the sciences. Despite decades of research, existing clustering algorithms have limited effectiveness in high dimensions and often require tuning parameters for different domains and datasets. We present a clustering algorithm that achieves high accuracy across multiple domains and scales efficiently to high dimensions and large datasets. The presented algorithm optimizes a smooth continuous objective, which is based on robust statistics and allows heavily mixed clusters to be untangled. The continuous nature of the objective also allows clustering to be integrated as a module in end-to-end feature learning pipelines. We demonstrate this by extending the algorithm to perform joint clustering and dimensionality reduction by efficiently optimizing a continuous global objective. The presented approach is evaluated on large datasets of faces, hand-written digits, objects, newswire articles, sensor readings from the Space Shuttle, and protein expression levels. Our method achieves high accuracy across all datasets, outperforming the best prior algorithm by a factor of 3 in average rank.
Network class superposition analyses.
Directory of Open Access Journals (Sweden)
Carl A B Pearson
Full Text Available Networks are often used to understand a whole system by modeling the interactions among its pieces. Examples include biomolecules in a cell interacting to provide some primary function, or species in an environment forming a stable community. However, these interactions are often unknown; instead, the pieces' dynamic states are known, and network structure must be inferred. Because observed function may be explained by many different networks (e.g., ≈ 10(30 for the yeast cell cycle process, considering dynamics beyond this primary function means picking a single network or suitable sample: measuring over all networks exhibiting the primary function is computationally infeasible. We circumvent that obstacle by calculating the network class ensemble. We represent the ensemble by a stochastic matrix T, which is a transition-by-transition superposition of the system dynamics for each member of the class. We present concrete results for T derived from boolean time series dynamics on networks obeying the Strong Inhibition rule, by applying T to several traditional questions about network dynamics. We show that the distribution of the number of point attractors can be accurately estimated with T. We show how to generate Derrida plots based on T. We show that T-based Shannon entropy outperforms other methods at selecting experiments to further narrow the network structure. We also outline an experimental test of predictions based on T. We motivate all of these results in terms of a popular molecular biology boolean network model for the yeast cell cycle, but the methods and analyses we introduce are general. We conclude with open questions for T, for example, application to other models, computational considerations when scaling up to larger systems, and other potential analyses.
Directory of Open Access Journals (Sweden)
Glauco S. F. da Silva
2012-05-01
Full Text Available We present the learning-teaching process case of a group of High School students and emphasize their relation with physics subject-matter, the interventions of the teacher (presential and institutional and the difficult situations faced by them within the group. We used Pichon-Rivière’s theory of operative groups to analyze this data. In this theory, some important elements are: the task of the group, the bond and the roles the members play. We made a diachronical analysis of the group, raising the hypothesis of the dependence from the teacher, and we made a synchronical analysis from one class to reveal some details of the group process. We concluded that the members’ dependence was related to “not knowing Physics” whose teacher was the one who could solve their problems. Lastly, we discuss teacher’s intervention function in a students’groupwork during physics classes.
Fan, Cong; Huang, Yanxin
2017-09-23
Histone deacetylases (HDACs) family has been widely reported as an important class of enzyme targets for cancer therapy. Much effort has been made in discovery of novel scaffolds for HDACs inhibition besides existing hydroxamic acids, cyclic peptides, benzamides, and short-chain fatty acids. Herein we set up an in-silico protocol which not only could detect potential Zn 2+ chelation bonds but also still adopted non-bonded model to be effective in discovery of Class I HDACs inhibitors, with little human's subjective visual judgment involved. We applied the protocol to screening of Chembridge database and selected out 7 scaffolds, 3 with probability of more than 99%. Biological assay results demonstrated that two of them exhibited HDAC-inhibitory activity and are thus considerable for structure modification to further improve their bio-activity. Copyright © 2017. Published by Elsevier Inc.
International Nuclear Information System (INIS)
Peng, Y.-F.
2009-01-01
The cerebellar model articulation controller (CMAC) is a non-linear adaptive system with built-in simple computation, good generalization capability and fast learning property. In this paper, a robust intelligent backstepping tracking control (RIBTC) system combined with adaptive CMAC and H ∞ control technique is proposed for a class of chaotic systems with unknown system dynamics and external disturbance. In the proposed control system, an adaptive backstepping cerebellar model articulation controller (ABCMAC) is used to mimic an ideal backstepping control (IBC), and a robust H ∞ controller is designed to attenuate the effect of the residual approximation errors and external disturbances with desired attenuation level. Moreover, the all adaptation laws of the RIBTC system are derived based on the Lyapunov stability analysis, the Taylor linearization technique and H ∞ control theory, so that the stability of the closed-loop system and H ∞ tracking performance can be guaranteed. Finally, three application examples, including a Duffing-Holmes chaotic system, a Genesio chaotic system and a Sprott circuit system, are used to demonstrate the effectiveness and performance of proposed robust control technique.
Robust Trust in Expert Testimony
Directory of Open Access Journals (Sweden)
Christian Dahlman
2015-05-01
Full Text Available The standard of proof in criminal trials should require that the evidence presented by the prosecution is robust. This requirement of robustness says that it must be unlikely that additional information would change the probability that the defendant is guilty. Robustness is difficult for a judge to estimate, as it requires the judge to assess the possible effect of information that the he or she does not have. This article is concerned with expert witnesses and proposes a method for reviewing the robustness of expert testimony. According to the proposed method, the robustness of expert testimony is estimated with regard to competence, motivation, external strength, internal strength and relevance. The danger of trusting non-robust expert testimony is illustrated with an analysis of the Thomas Quick Case, a Swedish legal scandal where a patient at a mental institution was wrongfully convicted for eight murders.
A Robust Mathematical Model On Infectious Diseases | Omorogbe ...
African Journals Online (AJOL)
The paper presents a robust epidemiological compartment model on infectious diseases. The model obviates the limitations of the classical epidemiological model by accommodating different levels of vulnerability and susceptibility to infections within different social class and spatial structures. Unlike the classical model ...
On the robustness of two-stage estimators
Zhelonkin, Mikhail; Genton, Marc G.; Ronchetti, Elvezio
2012-01-01
The aim of this note is to provide a general framework for the analysis of the robustness properties of a broad class of two-stage models. We derive the influence function, the change-of-variance function, and the asymptotic variance of a general
International Nuclear Information System (INIS)
Tang Yong; Yuan Wei; Pan Minqiang; Li Zongtao; Chen Guoqing; Li Yong
2010-01-01
The dynamic performance is a very important evaluation index of proton exchange membrane (PEM) fuel cells used for real application, which is mostly related with water, heat and gas management. A commercial PEM fuel cell system of Nexa module is employed to experimentally investigate the dynamic behavior and transient response of a PEM fuel cell stack and reveal involved influential factors. Five groups of dynamic tests are conducted and divided into different stage such as start-up, shut-down, step-up load, regular load variation and irregular load variation. It is observed that the external load changes the current output proportionally and reverses stack voltage accordingly. The purge operation benefits performance recovery and enhancement during a constant load and its time strongly depends on the operational current level. Overshoot and undershoot behaviors are observed during transience. But the current undershoot does not appear due to charge double-layer effect. Additionally, magnitudes of the peaks of the voltage overshoot and undershoot vary at different current levels. The operating temperature responds fast to current load but changes slowly showing an arc-like profile without any overshoot and undershoot events. The air flow rate changes directly following the dynamic load demand. But the increased amount of air flow rate during different step-change is not identical, which depends on the requirement of internal reaction and flooding intensity. The results can be utilized for validation of dynamic fuel cell models, and regarded as reference for effective control and management strategies.
The role of robust optimization in single-leg airline revenue management
Birbil, S.I.; Frenk, J.B.G.; Gromicho Dos Santos, J.A.; Zhang, S.
2009-01-01
In this paper, we introduce robust versions of the classical static and dynamic single-leg seat allocation models. These robust models take into account the inaccurate estimates of the underlying probability distributions. As observed by simulation experiments, it turns out that for these robust
A robust nonlinear filter for image restoration.
Koivunen, V
1995-01-01
A class of nonlinear regression filters based on robust estimation theory is introduced. The goal of the filtering is to recover a high-quality image from degraded observations. Models for desired image structures and contaminating processes are employed, but deviations from strict assumptions are allowed since the assumptions on signal and noise are typically only approximately true. The robustness of filters is usually addressed only in a distributional sense, i.e., the actual error distribution deviates from the nominal one. In this paper, the robustness is considered in a broad sense since the outliers may also be due to inappropriate signal model, or there may be more than one statistical population present in the processing window, causing biased estimates. Two filtering algorithms minimizing a least trimmed squares criterion are provided. The design of the filters is simple since no scale parameters or context-dependent threshold values are required. Experimental results using both real and simulated data are presented. The filters effectively attenuate both impulsive and nonimpulsive noise while recovering the signal structure and preserving interesting details.
The Model Construction of English Ecological Class in the High School in China
Zhou, Zhen
2017-01-01
The Ecological class is a kind of class in which the system of class teaching is in a state of dynamic balance and it can enhance the efficiency of class teaching. The article analyzes the feature of English ecological class, illustrates the non-ecological class teaching problems and explores the ways to establish English ecological class from the…
Track filtering by robust neural network
International Nuclear Information System (INIS)
Baginyan, S.A.; Kisel', I.V.; Konotopskaya, E.V.; Ososkov, G.A.
1993-01-01
In the present paper we study the following problems of track information extraction by the artificial neural network (ANN) rotor model: providing initial ANN configuration by an algorithm general enough to be applicable for any discrete detector in- or out of a magnetic field; robustness to heavy contaminated raw data (up to 100% signal-to-noise ratio); stability to the growing event multiplicity. These problems were carried out by corresponding innovations of our model, namely: by a special one-dimensional histogramming, by multiplying weights by a specially designed robust multiplier, and by replacing the simulated annealing schedule by ANN dynamics with an optimally fixed temperature. Our approach is valid for both circular and straight (non-magnetic) tracks and tested on 2D simulated data contaminated by 100% noise points distributed uniformly. To be closer to some reality in our simulation, we keep parameters of the cylindrical spectrometer ARES. 12 refs.; 9 figs
Robustness analysis method for orbit control
Zhang, Jingrui; Yang, Keying; Qi, Rui; Zhao, Shuge; Li, Yanyan
2017-08-01
Satellite orbits require periodical maintenance due to the presence of perturbations. However, random errors caused by inaccurate orbit determination and thrust implementation may lead to failure of the orbit control strategy. Therefore, it is necessary to analyze the robustness of the orbit control methods. Feasible strategies which are tolerant to errors of a certain magnitude can be developed to perform reliable orbit control for the satellite. In this paper, first, the orbital dynamic model is formulated by Gauss' form of the planetary equation using the mean orbit elements; the atmospheric drag and the Earth's non-spherical perturbations are taken into consideration in this model. Second, an impulsive control strategy employing the differential correction algorithm is developed to maintain the satellite trajectory parameters in given ranges. Finally, the robustness of the impulsive control method is analyzed through Monte Carlo simulations while taking orbit determination error and thrust error into account.
Robust blood-glucose control using Mathematica.
Kovács, Levente; Paláncz, Béla; Benyó, Balázs; Török, László; Benyó, Zoltán
2006-01-01
A robust control design on frequency domain using Mathematica is presented for regularization of glucose level in type I diabetes persons under intensive care. The method originally proposed under Mathematica by Helton and Merino, --now with an improved disturbance rejection constraint inequality--is employed, using a three-state minimal patient model. The robustness of the resulted high-order linear controller is demonstrated by nonlinear closed loop simulation in state-space, in case of standard meal disturbances and is compared with H infinity design implemented with the mu-toolbox of Matlab. The controller designed with model parameters represented the most favorable plant dynamics from the point of view of control purposes, can operate properly even in case of parameter values of the worst-case scenario.
Model predictive control classical, robust and stochastic
Kouvaritakis, Basil
2016-01-01
For the first time, a textbook that brings together classical predictive control with treatment of up-to-date robust and stochastic techniques. Model Predictive Control describes the development of tractable algorithms for uncertain, stochastic, constrained systems. The starting point is classical predictive control and the appropriate formulation of performance objectives and constraints to provide guarantees of closed-loop stability and performance. Moving on to robust predictive control, the text explains how similar guarantees may be obtained for cases in which the model describing the system dynamics is subject to additive disturbances and parametric uncertainties. Open- and closed-loop optimization are considered and the state of the art in computationally tractable methods based on uncertainty tubes presented for systems with additive model uncertainty. Finally, the tube framework is also applied to model predictive control problems involving hard or probabilistic constraints for the cases of multiplic...
Robust online Hamiltonian learning
International Nuclear Information System (INIS)
Granade, Christopher E; Ferrie, Christopher; Wiebe, Nathan; Cory, D G
2012-01-01
In this work we combine two distinct machine learning methodologies, sequential Monte Carlo and Bayesian experimental design, and apply them to the problem of inferring the dynamical parameters of a quantum system. We design the algorithm with practicality in mind by including parameters that control trade-offs between the requirements on computational and experimental resources. The algorithm can be implemented online (during experimental data collection), avoiding the need for storage and post-processing. Most importantly, our algorithm is capable of learning Hamiltonian parameters even when the parameters change from experiment-to-experiment, and also when additional noise processes are present and unknown. The algorithm also numerically estimates the Cramer–Rao lower bound, certifying its own performance. (paper)
Robust filtering for uncertain systems a parameter-dependent approach
Gao, Huijun
2014-01-01
This monograph provides the reader with a systematic treatment of robust filter design, a key issue in systems, control and signal processing, because of the fact that the inevitable presence of uncertainty in system and signal models often degrades the filtering performance and may even cause instability. The methods described are therefore not subject to the rigorous assumptions of traditional Kalman filtering. The monograph is concerned with robust filtering for various dynamical systems with parametric uncertainties, and focuses on parameter-dependent approaches to filter design. Classical filtering schemes, like H2 filtering and H¥ filtering, are addressed, and emerging issues such as robust filtering with constraints on communication channels and signal frequency characteristics are discussed. The text features: · design approaches to robust filters arranged according to varying complexity level, and emphasizing robust filtering in the parameter-dependent framework for the first time; ·...
Ding, Weili; Lehrer, Steven F.
2009-01-01
This paper introduces an empirical strategy to estimate dynamic treatment effects in randomized trials that provide treatment in multiple stages and in which various noncompliance problems arise such as attrition and selective transitions between treatment and control groups. Our approach is applied to the highly influential four year randomized…
Robustness of IPTV business models
Bouwman, H.; Zhengjia, M.; Duin, P. van der; Limonard, S.
2008-01-01
The final stage in the STOF method is an evaluation of the robustness of the design, for which the method provides some guidelines. For many innovative services, the future holds numerous uncertainties, which makes evaluating the robustness of a business model a difficult task. In this chapter, we
Robustness Evaluation of Timber Structures
DEFF Research Database (Denmark)
Kirkegaard, Poul Henning; Sørensen, John Dalsgaard
2009-01-01
Robustness of structural systems has obtained a renewed interest due to a much more frequent use of advanced types of structures with limited redundancy and serious consequences in case of failure.......Robustness of structural systems has obtained a renewed interest due to a much more frequent use of advanced types of structures with limited redundancy and serious consequences in case of failure....
Multivariable robust adaptive controller using reduced-order model
Directory of Open Access Journals (Sweden)
Wei Wang
1990-04-01
Full Text Available In this paper a multivariable robust adaptive controller is presented for a plant with bounded disturbances and unmodeled dynamics due to plant-model order mismatches. The robust stability of the closed-loop system is achieved by using the normalization technique and the least squares parameter estimation scheme with dead zones. The weighting polynomial matrices are incorporated into the control law, so that the open-loop unstable or/and nonminimum phase plants can be handled.
Robust statistical methods with R
Jureckova, Jana
2005-01-01
Robust statistical methods were developed to supplement the classical procedures when the data violate classical assumptions. They are ideally suited to applied research across a broad spectrum of study, yet most books on the subject are narrowly focused, overly theoretical, or simply outdated. Robust Statistical Methods with R provides a systematic treatment of robust procedures with an emphasis on practical application.The authors work from underlying mathematical tools to implementation, paying special attention to the computational aspects. They cover the whole range of robust methods, including differentiable statistical functions, distance of measures, influence functions, and asymptotic distributions, in a rigorous yet approachable manner. Highlighting hands-on problem solving, many examples and computational algorithms using the R software supplement the discussion. The book examines the characteristics of robustness, estimators of real parameter, large sample properties, and goodness-of-fit tests. It...
Integrated robust controller for vehicle path following
Energy Technology Data Exchange (ETDEWEB)
Mashadi, Behrooz; Ahmadizadeh, Pouyan, E-mail: p-ahmadizadeh@iust.ac.ir; Majidi, Majid, E-mail: m-majidi@iust.ac.ir [Iran University of Science and Technology, School of Automotive Engineering (Iran, Islamic Republic of); Mahmoodi-Kaleybar, Mehdi, E-mail: m-mahmoodi-k@iust.ac.ir [Iran University of Science and Technology, School of Mechanical Engineering (Iran, Islamic Republic of)
2015-02-15
The design of an integrated 4WS+DYC control system to guide a vehicle on a desired path is presented. The lateral dynamics of the path follower vehicle is formulated by considering important parameters. To reduce the effect of uncertainties in vehicle parameters, a robust controller is designed based on a μ-synthesis approach. Numerical simulations are performed using a nonlinear vehicle model in MATLAB environment in order to investigate the effectiveness of the designed controller. Results of simulations show that the controller has a profound ability to making the vehicle track the desired path in the presence of uncertainties.
Integrated robust controller for vehicle path following
International Nuclear Information System (INIS)
Mashadi, Behrooz; Ahmadizadeh, Pouyan; Majidi, Majid; Mahmoodi-Kaleybar, Mehdi
2015-01-01
The design of an integrated 4WS+DYC control system to guide a vehicle on a desired path is presented. The lateral dynamics of the path follower vehicle is formulated by considering important parameters. To reduce the effect of uncertainties in vehicle parameters, a robust controller is designed based on a μ-synthesis approach. Numerical simulations are performed using a nonlinear vehicle model in MATLAB environment in order to investigate the effectiveness of the designed controller. Results of simulations show that the controller has a profound ability to making the vehicle track the desired path in the presence of uncertainties
Human Relations Class. A Syllabus.
Guillen, Mary A.
A junior high level human relations class develops human interaction and oral communication skills. A week-by-week syllabus contains the following components: introduction of the students to each other and to the principles of body language, transactional analysis, and group interaction; behavior contracts; group dynamics topics and exercises;…
Universality Classes of Interaction Structures for NK Fitness Landscapes
Hwang, Sungmin; Schmiegelt, Benjamin; Ferretti, Luca; Krug, Joachim
2018-02-01
Kauffman's NK-model is a paradigmatic example of a class of stochastic models of genotypic fitness landscapes that aim to capture generic features of epistatic interactions in multilocus systems. Genotypes are represented as sequences of L binary loci. The fitness assigned to a genotype is a sum of contributions, each of which is a random function defined on a subset of k ≤ L loci. These subsets or neighborhoods determine the genetic interactions of the model. Whereas earlier work on the NK model suggested that most of its properties are robust with regard to the choice of neighborhoods, recent work has revealed an important and sometimes counter-intuitive influence of the interaction structure on the properties of NK fitness landscapes. Here we review these developments and present new results concerning the number of local fitness maxima and the statistics of selectively accessible (that is, fitness-monotonic) mutational pathways. In particular, we develop a unified framework for computing the exponential growth rate of the expected number of local fitness maxima as a function of L, and identify two different universality classes of interaction structures that display different asymptotics of this quantity for large k. Moreover, we show that the probability that the fitness landscape can be traversed along an accessible path decreases exponentially in L for a large class of interaction structures that we characterize as locally bounded. Finally, we discuss the impact of the NK interaction structures on the dynamics of evolution using adaptive walk models.
Robust loss functions for boosting.
Kanamori, Takafumi; Takenouchi, Takashi; Eguchi, Shinto; Murata, Noboru
2007-08-01
Boosting is known as a gradient descent algorithm over loss functions. It is often pointed out that the typical boosting algorithm, Adaboost, is highly affected by outliers. In this letter, loss functions for robust boosting are studied. Based on the concept of robust statistics, we propose a transformation of loss functions that makes boosting algorithms robust against extreme outliers. Next, the truncation of loss functions is applied to contamination models that describe the occurrence of mislabels near decision boundaries. Numerical experiments illustrate that the proposed loss functions derived from the contamination models are useful for handling highly noisy data in comparison with other loss functions.
Theoretical Framework for Robustness Evaluation
DEFF Research Database (Denmark)
Sørensen, John Dalsgaard
2011-01-01
This paper presents a theoretical framework for evaluation of robustness of structural systems, incl. bridges and buildings. Typically modern structural design codes require that ‘the consequence of damages to structures should not be disproportional to the causes of the damages’. However, although...... the importance of robustness for structural design is widely recognized the code requirements are not specified in detail, which makes the practical use difficult. This paper describes a theoretical and risk based framework to form the basis for quantification of robustness and for pre-normative guidelines...
Robustness of airline route networks
Lordan, Oriol; Sallan, Jose M.; Escorihuela, Nuria; Gonzalez-Prieto, David
2016-03-01
Airlines shape their route network by defining their routes through supply and demand considerations, paying little attention to network performance indicators, such as network robustness. However, the collapse of an airline network can produce high financial costs for the airline and all its geographical area of influence. The aim of this study is to analyze the topology and robustness of the network route of airlines following Low Cost Carriers (LCCs) and Full Service Carriers (FSCs) business models. Results show that FSC hubs are more central than LCC bases in their route network. As a result, LCC route networks are more robust than FSC networks.
Robustness Property of Robust-BD Wald-Type Test for Varying-Dimensional General Linear Models
Directory of Open Access Journals (Sweden)
Xiao Guo
2018-03-01
Full Text Available An important issue for robust inference is to examine the stability of the asymptotic level and power of the test statistic in the presence of contaminated data. Most existing results are derived in finite-dimensional settings with some particular choices of loss functions. This paper re-examines this issue by allowing for a diverging number of parameters combined with a broader array of robust error measures, called “robust- BD ”, for the class of “general linear models”. Under regularity conditions, we derive the influence function of the robust- BD parameter estimator and demonstrate that the robust- BD Wald-type test enjoys the robustness of validity and efficiency asymptotically. Specifically, the asymptotic level of the test is stable under a small amount of contamination of the null hypothesis, whereas the asymptotic power is large enough under a contaminated distribution in a neighborhood of the contiguous alternatives, thus lending supports to the utility of the proposed robust- BD Wald-type test.
A new criterion for global robust stability of interval neural networks with discrete time delays
International Nuclear Information System (INIS)
Li Chuandong; Chen Jinyu; Huang Tingwen
2007-01-01
This paper further studies global robust stability of a class of interval neural networks with discrete time delays. By introducing an equivalent transformation of interval matrices, a new criterion on global robust stability is established. In comparison with the results reported in the literature, the proposed approach leads to results with less restrictive conditions. Numerical examples are also worked through to illustrate our results
DEFF Research Database (Denmark)
Pakazad, Sina Khoshfetrat; Hansson, Anders; Andersen, Martin Skovgaard
2013-01-01
We consider a class of convex feasibility problems where the constraints that describe the feasible set are loosely coupled. These problems arise in robust stability analysis of large, weakly interconnected uncertain systems. To facilitate distributed implementation of robust stability analysis o...
Sufficient conditions for BIBO robust stabilization : given by the gap metric
Zhu, S.Q.; Hautus, M.L.J.; Praagman, C.
1987-01-01
A relation between coprlme fractions and the gap metric is presented. Using this result we provide some sufficient conditions for BIBO robust stabilization for a very wide class of systems. These conditions allow the plant and compensator to be disturbed simultaneously. Keywords: Robust
Robust Portfolio Optimization Using Pseudodistances.
Toma, Aida; Leoni-Aubin, Samuela
2015-01-01
The presence of outliers in financial asset returns is a frequently occurring phenomenon which may lead to unreliable mean-variance optimized portfolios. This fact is due to the unbounded influence that outliers can have on the mean returns and covariance estimators that are inputs in the optimization procedure. In this paper we present robust estimators of mean and covariance matrix obtained by minimizing an empirical version of a pseudodistance between the assumed model and the true model underlying the data. We prove and discuss theoretical properties of these estimators, such as affine equivariance, B-robustness, asymptotic normality and asymptotic relative efficiency. These estimators can be easily used in place of the classical estimators, thereby providing robust optimized portfolios. A Monte Carlo simulation study and applications to real data show the advantages of the proposed approach. We study both in-sample and out-of-sample performance of the proposed robust portfolios comparing them with some other portfolios known in literature.
International Nuclear Information System (INIS)
Davidson, J.A.; Ceschini, L.J.; Shogan, R.P.; Rao, G.V.
1976-10-01
As a result of the Heavy Section Steel Technology Program (HSST), sponsored by the Nuclear Regulatory Commission, Westinghouse Electric Corporation conducted dynamic fracture toughness tests on irradiated HSST Plate 02 and submerged arc weldment material. Testing performed at the Westinghouse Research and Development Laboratory in Pittsburgh, Pennsylvania, included 0.394T compact tension, 1.9T compact tension, and 4T compact tension specimens. This data showed that, in the transition region, dynamic test procedures resulted in lower (compared to static) fracture toughness results, and that weak direction (WR) oriented specimen data were lower than the strong direction (RW) oriented specimen results. Irradiated lower-bound fracture toughness results of the HSST Program material were well above the adjusted ASME Section III K/sub IR/ curve. An irradiated and nonirradiated 4T-CT specimen was tested during a fracture toughness test as a preliminary study to determine the effect of irradiation on the acoustic emission-stress intensity factor relation in pressure vessel grade steel. The results indicated higher levels of acoustic emission activity from the irradiated sample as compared to the unirradiated one at a given stress intensity factor (K) level
Robust methods for data reduction
Farcomeni, Alessio
2015-01-01
Robust Methods for Data Reduction gives a non-technical overview of robust data reduction techniques, encouraging the use of these important and useful methods in practical applications. The main areas covered include principal components analysis, sparse principal component analysis, canonical correlation analysis, factor analysis, clustering, double clustering, and discriminant analysis.The first part of the book illustrates how dimension reduction techniques synthesize available information by reducing the dimensionality of the data. The second part focuses on cluster and discriminant analy
Robust Covariance Estimators Based on Information Divergences and Riemannian Manifold
Directory of Open Access Journals (Sweden)
Xiaoqiang Hua
2018-03-01
Full Text Available This paper proposes a class of covariance estimators based on information divergences in heterogeneous environments. In particular, the problem of covariance estimation is reformulated on the Riemannian manifold of Hermitian positive-definite (HPD matrices. The means associated with information divergences are derived and used as the estimators. Without resorting to the complete knowledge of the probability distribution of the sample data, the geometry of the Riemannian manifold of HPD matrices is considered in mean estimators. Moreover, the robustness of mean estimators is analyzed using the influence function. Simulation results indicate the robustness and superiority of an adaptive normalized matched filter with our proposed estimators compared with the existing alternatives.
Global robust stability of delayed recurrent neural networks
International Nuclear Information System (INIS)
Cao Jinde; Huang Deshuang; Qu Yuzhong
2005-01-01
This paper is concerned with the global robust stability of a class of delayed interval recurrent neural networks which contain time-invariant uncertain parameters whose values are unknown but bounded in given compact sets. A new sufficient condition is presented for the existence, uniqueness, and global robust stability of equilibria for interval neural networks with time delays by constructing Lyapunov functional and using matrix-norm inequality. An error is corrected in an earlier publication, and an example is given to show the effectiveness of the obtained results
The Fermilab physics class library
International Nuclear Information System (INIS)
Fischler, M.; Brown, W.; Gaines, I.; Kennedy, R.D.; Marraffino, J.; Michelotti, L.; Sexton-Kennedy, E.; Yoh, J.; Adams, D.; Paterno, M.
1997-02-01
The Fermilab Physics Class Library Task Force has been formed to supply classes and utilities, primarily in support of efforts by CDF and D0 toward using C++. A collection of libraries and tools will be assembled via development by the task force, collaboration with other HEP developers, and acquisition of existing modules. The main emphasis is on a kit of resources which physics coders can incorporate into their programs, with confidence in robustness and correct behavior. The task force is drawn from CDF, DO and the FNAL Computing and Beams Divisions. Modules-containers, linear algebra, histograms, etc.-have been assigned priority, based on immediate Run II coding activity, and will be available at times ranging from now to late May
Supervised Object Class Colour Normalisation
DEFF Research Database (Denmark)
Riabchenko, Ekatarina; Lankinen, Jukka; Buch, Anders Glent
2013-01-01
. In this work, we develop a such colour normalisation technique, where true colours are not important per se but where examples of same classes have photometrically consistent appearance. This is achieved by supervised estimation of a class specic canonical colour space where the examples have minimal variation......Colour is an important cue in many applications of computer vision and image processing, but robust usage often requires estimation of the unknown illuminant colour. Usually, to obtain images invariant to the illumination conditions under which they were taken, color normalisation is used...... in their colours. We demonstrate the effectiveness of our method with qualitative and quantitative examples from the Caltech-101 data set and a real application of 3D pose estimation for robot grasping....
Calibration robust entanglement detection beyond Bell inequalities
Energy Technology Data Exchange (ETDEWEB)
Moroder, Tobias [Institut fuer Quantenoptik und Quanteninformation, Oesterreichische Akademie der Wissenschaften, Technikerstrasse 21A, A-6020 Innsbruck (Austria); Gittsovich, Oleg [Department of Physics and Astronomy, Institute for Quantum Computing, University of Waterloo, 200 University Avenue West, N2L 3G1 Waterloo, Ontario (Canada)
2012-07-01
In its vast majority entanglement verification is examined either in the complete characterized or totally device independent scenario. The assumptions imposed by these extreme cases are often either too weak or strong for real experiments. Here we investigate this detection task for the intermediate regime where partial knowledge of the measured observables is known, considering cases like orthogonal, sharp or only dimension bounded measurements. We show that for all these assumptions it is not necessary to violate a corresponding Bell inequality in order to detect entanglement. We derive strong detection criteria that can be directly evaluated for experimental data and which are robust against large classes of calibration errors. The conditions are even capable of detecting bound entanglement under the sole assumption of dimension bounded measurements.
Robust network topologies for generating switch-like cellular responses.
Directory of Open Access Journals (Sweden)
Najaf A Shah
2011-06-01
Full Text Available Signaling networks that convert graded stimuli into binary, all-or-none cellular responses are critical in processes ranging from cell-cycle control to lineage commitment. To exhaustively enumerate topologies that exhibit this switch-like behavior, we simulated all possible two- and three-component networks on random parameter sets, and assessed the resulting response profiles for both steepness (ultrasensitivity and extent of memory (bistability. Simulations were used to study purely enzymatic networks, purely transcriptional networks, and hybrid enzymatic/transcriptional networks, and the topologies in each class were rank ordered by parametric robustness (i.e., the percentage of applied parameter sets exhibiting ultrasensitivity or bistability. Results reveal that the distribution of network robustness is highly skewed, with the most robust topologies clustering into a small number of motifs. Hybrid networks are the most robust in generating ultrasensitivity (up to 28% and bistability (up to 18%; strikingly, a purely transcriptional framework is the most fragile in generating either ultrasensitive (up to 3% or bistable (up to 1% responses. The disparity in robustness among the network classes is due in part to zero-order ultrasensitivity, an enzyme-specific phenomenon, which repeatedly emerges as a particularly robust mechanism for generating nonlinearity and can act as a building block for switch-like responses. We also highlight experimentally studied examples of topologies enabling switching behavior, in both native and synthetic systems, that rank highly in our simulations. This unbiased approach for identifying topologies capable of a given response may be useful in discovering new natural motifs and in designing robust synthetic gene networks.
Mulder, Kevin P.; Cortazar-Chinarro, Maria; Harris, D. James; Crottini, Angelica; Grant, Evan H. Campbell; Fleischer, Robert C.; Savage, Anna E.
2017-01-01
The Major Histocompatibility Complex (MHC) is a genomic region encoding immune loci that are important and frequently used markers in studies of adaptive genetic variation and disease resistance. Given the primary role of infectious diseases in contributing to global amphibian declines, we characterized the hypervariable exon 2 and flanking introns of the MHC Class IIβ chain for 17 species of frogs in the Ranidae, a speciose and cosmopolitan family facing widespread pathogen infections and declines. We find high levels of genetic variation concentrated in the Peptide Binding Region (PBR) of the exon. Ten codons are under positive selection, nine of which are located in the mammal-defined PBR. We hypothesize that the tenth codon (residue 21) is an amphibian-specific PBR site that may be important in disease resistance. Trans-species and trans-generic polymorphisms are evident from exon-based genealogies, and co-phylogenetic analyses between intron, exon and mitochondrial based reconstructions reveal incongruent topologies, likely due to different locus histories. We developed two sets of barcoded adapters that reliably amplify a single and likely functional locus in all screened species using both 454 and Illumina based sequencing methods. These primers provide a resource for multiplexing and directly sequencing hundreds of samples in a single sequencing run, avoiding the labour and chimeric sequences associated with cloning, and enabling MHC population genetic analyses. Although the primers are currently limited to the 17 species we tested, these sequences and protocols provide a useful genetic resource and can serve as a starting point for future disease, adaptation and conservation studies across a range of anuran taxa.
Social Class on Campus: Theories and Manifestations
Barratt, Will
2011-01-01
This is at once a playful text with a serious purpose: to provide the reader with the theoretical lenses to analyze the dynamics of social class. It will appeal to students, and indeed anyone interested in how class mediates relationships in higher education, both because of its engaging tone, and because it uses the college campus as a microcosm…
Bukhari, Hassan J.
2017-12-01
In this paper a framework for robust optimization of mechanical design problems and process systems that have parametric uncertainty is presented using three different approaches. Robust optimization problems are formulated so that the optimal solution is robust which means it is minimally sensitive to any perturbations in parameters. The first method uses the price of robustness approach which assumes the uncertain parameters to be symmetric and bounded. The robustness for the design can be controlled by limiting the parameters that can perturb.The second method uses the robust least squares method to determine the optimal parameters when data itself is subjected to perturbations instead of the parameters. The last method manages uncertainty by restricting the perturbation on parameters to improve sensitivity similar to Tikhonov regularization. The methods are implemented on two sets of problems; one linear and the other non-linear. This methodology will be compared with a prior method using multiple Monte Carlo simulation runs which shows that the approach being presented in this paper results in better performance.
Numerically robust geometry engine for compound solid geometries
International Nuclear Information System (INIS)
Vlachoudis, V.; Sinuela-Pastor, D.
2013-01-01
Monte Carlo programs heavily rely on a fast and numerically robust solid geometry engines. However the success of solid modeling, depends on facilities for specifying and editing parameterized models through a user-friendly graphical front-end. Such a user interface has to be fast enough in order to be interactive for 2D and/or 3D displays, but at the same time numerically robust in order to display possible modeling errors at real time that could be critical for the simulation. The graphical user interface Flair for FLUKA currently employs such an engine where special emphasis has been given on being fast and numerically robust. The numerically robustness is achieved by a novel method of estimating the floating precision of the operations, which dynamically adapts all the decision operations accordingly. Moreover a predictive caching mechanism is ensuring that logical errors in the geometry description are found online, without compromising the processing time by checking all regions. (authors)
Slow dynamics in translation-invariant quantum lattice models
Michailidis, Alexios A.; Žnidarič, Marko; Medvedyeva, Mariya; Abanin, Dmitry A.; Prosen, Tomaž; Papić, Z.
2018-03-01
Many-body quantum systems typically display fast dynamics and ballistic spreading of information. Here we address the open problem of how slow the dynamics can be after a generic breaking of integrability by local interactions. We develop a method based on degenerate perturbation theory that reveals slow dynamical regimes and delocalization processes in general translation invariant models, along with accurate estimates of their delocalization time scales. Our results shed light on the fundamental questions of the robustness of quantum integrable systems and the possibility of many-body localization without disorder. As an example, we construct a large class of one-dimensional lattice models where, despite the absence of asymptotic localization, the transient dynamics is exceptionally slow, i.e., the dynamics is indistinguishable from that of many-body localized systems for the system sizes and time scales accessible in experiments and numerical simulations.
U.S. Department of Health & Human Services — The RxClass Browser is a web application for exploring and navigating through the class hierarchies to find the RxNorm drug members associated with each class....
Designing Robustness to Temperature in a Feedforward Loop Circuit
Sen, Shaunak; Kim, Jongmin; Murray, Richard M.
2013-01-01
Incoherent feedforward loops represent important biomolecular circuit elements capable of a rich set of dynamic behavior including adaptation and pulsed responses. Temperature can modulate some of these properties through its effect on the underlying reaction rate parameters. It is generally unclear how to design such a circuit where the properties are robust to variations in temperature. Here, we address this issue using a combination of tools from control and dynamical systems theory as wel...
A robust multivariate long run analysis of European electricity prices
Bruno Bosco; Lucia Parisio; Matteo Pelagatti; Fabio Baldi
2007-01-01
This paper analyses the interdependencies existing in wholesale electricity prices in six major European countries. The results of our robust multivariate long run dynamic analysis reveal the presence of four highly integrated central European markets (France, Germany, the Netherlands and Austria). The trend shared by these four electricity markets appears to be common also to gas prices, but not to oil prices. The existence of long term dynamics among electricity prices and between electrici...
Virtual partitioning for robust resource sharing: computational techniques for heterogeneous traffic
Borst, S.C.; Mitra, D.
1998-01-01
We consider virtual partitioning (VP), which is a scheme for sharing a resource among several traffic classes in an efficient, fair, and robust manner. In the preliminary design stage, each traffic class is allocated a nominal capacity, which is based on expected offered traffic and required quality
The Robust Control Mixer Module Method for Control Reconfiguration
DEFF Research Database (Denmark)
Yang, Z.; Blanke, M.
1999-01-01
into a LTI dynamical system, and furthermore multiple dynamical control mixer modules can be employed in our consideration. The H_{\\infty} control theory is used for the analysis and design of the robust control mixer modules. Finally, one practical robot arm system as benchmark is used to test the proposed......The control mixer concept is efficient in improving an ordinary control system into a fault tolerant one, especially for these control systems of which the real-time and on-line redesign of the control laws is very difficult. In order to consider the stability, performance and robustness...... of the reconfigurated system simultaneously, and to deal with a more general controller reconfiguration than the static feedback mechanism by using the control mixer approach, the robust control mixer module method is proposed in this paper. The form of the control mixer module extends from a static gain matrix...
Robust combined position and formation control for marine surface craft
DEFF Research Database (Denmark)
Ihle, Ivar-Andre F.; Jouffroy, Jerome; Fossen, Thor I.
We consider the robustness properties of a formation control system for marine surface vessels. Intervessel constraint functions are stabilized to achieve the desired formation configuration. We show that the formation dynamics is Input-to-State Stable (ISS) to both environmental perturbations th...
Advances in robust fractional control
Padula, Fabrizio
2015-01-01
This monograph presents design methodologies for (robust) fractional control systems. It shows the reader how to take advantage of the superior flexibility of fractional control systems compared with integer-order systems in achieving more challenging control requirements. There is a high degree of current interest in fractional systems and fractional control arising from both academia and industry and readers from both milieux are catered to in the text. Different design approaches having in common a trade-off between robustness and performance of the control system are considered explicitly. The text generalizes methodologies, techniques and theoretical results that have been successfully applied in classical (integer) control to the fractional case. The first part of Advances in Robust Fractional Control is the more industrially-oriented. It focuses on the design of fractional controllers for integer processes. In particular, it considers fractional-order proportional-integral-derivative controllers, becau...
Robustness of digital artist authentication
DEFF Research Database (Denmark)
Jacobsen, Robert; Nielsen, Morten
In many cases it is possible to determine the authenticity of a painting from digital reproductions of the paintings; this has been demonstrated for a variety of artists and with different approaches. Common to all these methods in digital artist authentication is that the potential of the method...... is in focus, while the robustness has not been considered, i.e. the degree to which the data collection process influences the decision of the method. However, in order for an authentication method to be successful in practice, it needs to be robust to plausible error sources from the data collection....... In this paper we investigate the robustness of the newly proposed authenticity method introduced by the authors based on second generation multiresolution analysis. This is done by modelling a number of realistic factors that can occur in the data collection....
Robustness of holonomic quantum gates
International Nuclear Information System (INIS)
Solinas, P.; Zanardi, P.; Zanghi, N.
2005-01-01
Full text: If the driving field fluctuates during the quantum evolution this produces errors in the applied operator. The holonomic (and geometrical) quantum gates are believed to be robust against some kind of noise. Because of the geometrical dependence of the holonomic operators can be robust against this kind of noise; in fact if the fluctuations are fast enough they cancel out leaving the final operator unchanged. I present the numerical studies of holonomic quantum gates subject to this parametric noise, the fidelity of the noise and ideal evolution is calculated for different noise correlation times. The holonomic quantum gates seem robust not only for fast fluctuating fields but also for slow fluctuating fields. These results can be explained as due to the geometrical feature of the holonomic operator: for fast fluctuating fields the fluctuations are canceled out, for slow fluctuating fields the fluctuations do not perturb the loop in the parameter space. (author)
Robust estimation and hypothesis testing
Tiku, Moti L
2004-01-01
In statistical theory and practice, a certain distribution is usually assumed and then optimal solutions sought. Since deviations from an assumed distribution are very common, one cannot feel comfortable with assuming a particular distribution and believing it to be exactly correct. That brings the robustness issue in focus. In this book, we have given statistical procedures which are robust to plausible deviations from an assumed mode. The method of modified maximum likelihood estimation is used in formulating these procedures. The modified maximum likelihood estimators are explicit functions of sample observations and are easy to compute. They are asymptotically fully efficient and are as efficient as the maximum likelihood estimators for small sample sizes. The maximum likelihood estimators have computational problems and are, therefore, elusive. A broad range of topics are covered in this book. Solutions are given which are easy to implement and are efficient. The solutions are also robust to data anomali...
Balamurugan, Appakalai N.; Green, Michael L.; Breite, Andrew G.; Loganathan, Gopalakrishnan; Wilhelm, Joshua J.; Tweed, Benjamin; Vargova, Lenka; Lockridge, Amber; Kuriti, Manikya; Hughes, Michael G.; Williams, Stuart K.; Hering, Bernhard J.; Dwulet, Francis E.; McCarthy, Robert C.
2015-01-01
Isolation following a good manufacturing practice-compliant, human islet product requires development of a robust islet isolation procedure where effective limits of key reagents are known. The enzymes used for islet isolation are critical but little is known about the doses of class I and class II collagenase required for successful islet isolation.
Robustness in Railway Operations (RobustRailS)
DEFF Research Database (Denmark)
Jensen, Jens Parbo; Nielsen, Otto Anker
This study considers the problem of enhancing railway timetable robustness without adding slack time, hence increasing the travel time. The approach integrates a transit assignment model to assess how passengers adapt their behaviour whenever operations are changed. First, the approach considers...
Robust fast controller design via nonlinear fractional differential equations.
Zhou, Xi; Wei, Yiheng; Liang, Shu; Wang, Yong
2017-07-01
A new method for linear system controller design is proposed whereby the closed-loop system achieves both robustness and fast response. The robustness performance considered here means the damping ratio of closed-loop system can keep its desired value under system parameter perturbation, while the fast response, represented by rise time of system output, can be improved by tuning the controller parameter. We exploit techniques from both the nonlinear systems control and the fractional order systems control to derive a novel nonlinear fractional order controller. For theoretical analysis of the closed-loop system performance, two comparison theorems are developed for a class of fractional differential equations. Moreover, the rise time of the closed-loop system can be estimated, which facilitates our controller design to satisfy the fast response performance and maintain the robustness. Finally, numerical examples are given to illustrate the effectiveness of our methods. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.
Critical cooperation range to improve spatial network robustness.
Directory of Open Access Journals (Sweden)
Vitor H P Louzada
Full Text Available A robust worldwide air-transportation network (WAN is one that minimizes the number of stranded passengers under a sequence of airport closures. Building on top of this realistic example, here we address how spatial network robustness can profit from cooperation between local actors. We swap a series of links within a certain distance, a cooperation range, while following typical constraints of spatially embedded networks. We find that the network robustness is only improved above a critical cooperation range. Such improvement can be described in the framework of a continuum transition, where the critical exponents depend on the spatial correlation of connected nodes. For the WAN we show that, except for Australia, all continental networks fall into the same universality class. Practical implications of this result are also discussed.
Adaptive integral robust control and application to electromechanical servo systems.
Deng, Wenxiang; Yao, Jianyong
2017-03-01
This paper proposes a continuous adaptive integral robust control with robust integral of the sign of the error (RISE) feedback for a class of uncertain nonlinear systems, in which the RISE feedback gain is adapted online to ensure the robustness against disturbances without the prior bound knowledge of the additive disturbances. In addition, an adaptive compensation integrated with the proposed adaptive RISE feedback term is also constructed to further reduce design conservatism when the system also exists parametric uncertainties. Lyapunov analysis reveals the proposed controllers could guarantee the tracking errors are asymptotically converging to zero with continuous control efforts. To illustrate the high performance nature of the developed controllers, numerical simulations are provided. At the end, an application case of an actual electromechanical servo system driven by motor is also studied, with some specific design consideration, and comparative experimental results are obtained to verify the effectiveness of the proposed controllers. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.
A Robust Design Applicability Model
DEFF Research Database (Denmark)
Ebro, Martin; Lars, Krogstie; Howard, Thomas J.
2015-01-01
to be applicable in organisations assigning a high importance to one or more factors that are known to be impacted by RD, while also experiencing a high level of occurrence of this factor. The RDAM supplements existing maturity models and metrics to provide a comprehensive set of data to support management......This paper introduces a model for assessing the applicability of Robust Design (RD) in a project or organisation. The intention of the Robust Design Applicability Model (RDAM) is to provide support for decisions by engineering management considering the relevant level of RD activities...
On the robustness of two-stage estimators
Zhelonkin, Mikhail
2012-04-01
The aim of this note is to provide a general framework for the analysis of the robustness properties of a broad class of two-stage models. We derive the influence function, the change-of-variance function, and the asymptotic variance of a general two-stage M-estimator, and provide their interpretations. We illustrate our results in the case of the two-stage maximum likelihood estimator and the two-stage least squares estimator. © 2011.
Robust Stabilization of Discrete-Time Systems with Time-Varying Delay: An LMI Approach
Directory of Open Access Journals (Sweden)
Valter J. S. Leite
2008-01-01
Full Text Available Sufficient linear matrix inequality (LMI conditions to verify the robust stability and to design robust state feedback gains for the class of linear discrete-time systems with time-varying delay and polytopic uncertainties are presented. The conditions are obtained through parameter-dependent Lyapunov-Krasovskii functionals and use some extra variables, which yield less conservative LMI conditions. Both problems, robust stability analysis and robust synthesis, are formulated as convex problems where all system matrices can be affected by uncertainty. Some numerical examples are presented to illustrate the advantages of the proposed LMI conditions.
Directory of Open Access Journals (Sweden)
Deyin Yao
2014-01-01
Full Text Available This paper deals with the problem of robust model predictive control (RMPC for a class of linear time-varying systems with constraints and data losses. We take the polytopic uncertainties into account to describe the uncertain systems. First, we design a robust state observer by using the linear matrix inequality (LMI constraints so that the original system state can be tracked. Second, the MPC gain is calculated by minimizing the upper bound of infinite horizon robust performance objective in terms of linear matrix inequality conditions. The method of robust MPC and state observer design is illustrated by a numerical example.
Lee, W.-J.; Do, S.-H.; Lee, S.; Choi, Y.-S.; Choi, K.-Y.; Yoon, Sungwon; Suh, Byoungjin; Jang, Zeehoon
2018-01-01
We report on the spin dynamics of the strong spin-orbit coupled antiferromagnets Ba3Ru1- x Ir x Ti2O9 ( x = 0.5 and 0.8), which comprise a mixture of edge- and corner-sharing triangles. Muon spin-relaxation measurements give no hints of long-range magnetic order down to 25 mK. Rather, the muon spin-relaxation rates λ( T) show persistent spin dynamics below 1 K, indicating that fast fluctuations are dominant in spite of Ir4+( J eff = 1/2)/Ru4+( S = 1) randomness. The muon spin depolarization of both compounds is well described by a stretched exponential function with the stretching exponent β = 0.4 (0.6) for x = 0.5 (0.8) at low temperatures, which is larger than β = 1/3 expected for a spin glass. Our results suggest that randomness in the spin number and the exchange interaction induces a partial spin freezing, but the majority of spins remain dynamically fluctuating.
Multi-Class Motor Imagery EEG Decoding for Brain-Computer Interfaces
Wang, Deng; Miao, Duoqian; Blohm, Gunnar
2012-01-01
Recent studies show that scalp electroencephalography (EEG) as a non-invasive interface has great potential for brain-computer interfaces (BCIs). However, one factor that has limited practical applications for EEG-based BCI so far is the difficulty to decode brain signals in a reliable and efficient way. This paper proposes a new robust processing framework for decoding of multi-class motor imagery (MI) that is based on five main processing steps. (i) Raw EEG segmentation without the need of visual artifact inspection. (ii) Considering that EEG recordings are often contaminated not just by electrooculography (EOG) but also other types of artifacts, we propose to first implement an automatic artifact correction method that combines regression analysis with independent component analysis for recovering the original source signals. (iii) The significant difference between frequency components based on event-related (de-) synchronization and sample entropy is then used to find non-contiguous discriminating rhythms. After spectral filtering using the discriminating rhythms, a channel selection algorithm is used to select only relevant channels. (iv) Feature vectors are extracted based on the inter-class diversity and time-varying dynamic characteristics of the signals. (v) Finally, a support vector machine is employed for four-class classification. We tested our proposed algorithm on experimental data that was obtained from dataset 2a of BCI competition IV (2008). The overall four-class kappa values (between 0.41 and 0.80) were comparable to other models but without requiring any artifact-contaminated trial removal. The performance showed that multi-class MI tasks can be reliably discriminated using artifact-contaminated EEG recordings from a few channels. This may be a promising avenue for online robust EEG-based BCI applications. PMID:23087607
Essays on robust asset pricing
Horváth, Ferenc
2017-01-01
The central concept of this doctoral dissertation is robustness. I analyze how model and parameter uncertainty affect financial decisions of investors and fund managers, and what their equilibrium consequences are. Chapter 1 gives an overview of the most important concepts and methodologies used in
International Nuclear Information System (INIS)
Fournel, Thierry; Coltuc, Daniela
2010-01-01
Designed to maximize information transmission in the presence of noise, independent component analysis (ICA) could appear in certain circumstances as a statistics-based tool for robust visual hashing. Several ICA-based scenarios can attempt to reach this goal. A first one is here considered.
Robustness of raw quantum tomography
Asorey, M.; Facchi, P.; Florio, G.; Man'ko, V. I.; Marmo, G.; Pascazio, S.; Sudarshan, E. C. G.
2011-01-01
We scrutinize the effects of non-ideal data acquisition on the tomograms of quantum states. The presence of a weight function, schematizing the effects of a finite window or equivalently noise, only affects the state reconstruction procedure by a normalization constant. The results are extended to a discrete mesh and show that quantum tomography is robust under incomplete and approximate knowledge of tomograms.
Robustness of raw quantum tomography
Energy Technology Data Exchange (ETDEWEB)
Asorey, M. [Departamento de Fisica Teorica, Facultad de Ciencias, Universidad de Zaragoza, 50009 Zaragoza (Spain); Facchi, P. [Dipartimento di Matematica, Universita di Bari, I-70125 Bari (Italy); INFN, Sezione di Bari, I-70126 Bari (Italy); MECENAS, Universita Federico II di Napoli and Universita di Bari (Italy); Florio, G. [Dipartimento di Fisica, Universita di Bari, I-70126 Bari (Italy); INFN, Sezione di Bari, I-70126 Bari (Italy); MECENAS, Universita Federico II di Napoli and Universita di Bari (Italy); Man' ko, V.I., E-mail: manko@lebedev.r [P.N. Lebedev Physical Institute, Leninskii Prospect 53, Moscow 119991 (Russian Federation); Marmo, G. [Dipartimento di Scienze Fisiche, Universita di Napoli ' Federico II' , I-80126 Napoli (Italy); INFN, Sezione di Napoli, I-80126 Napoli (Italy); MECENAS, Universita Federico II di Napoli and Universita di Bari (Italy); Pascazio, S. [Dipartimento di Fisica, Universita di Bari, I-70126 Bari (Italy); INFN, Sezione di Bari, I-70126 Bari (Italy); MECENAS, Universita Federico II di Napoli and Universita di Bari (Italy); Sudarshan, E.C.G. [Department of Physics, University of Texas, Austin, TX 78712 (United States)
2011-01-31
We scrutinize the effects of non-ideal data acquisition on the tomograms of quantum states. The presence of a weight function, schematizing the effects of a finite window or equivalently noise, only affects the state reconstruction procedure by a normalization constant. The results are extended to a discrete mesh and show that quantum tomography is robust under incomplete and approximate knowledge of tomograms.
Aspects of robust linear regression
Davies, P.L.
1993-01-01
Section 1 of the paper contains a general discussion of robustness. In Section 2 the influence function of the Hampel-Rousseeuw least median of squares estimator is derived. Linearly invariant weak metrics are constructed in Section 3. It is shown in Section 4 that $S$-estimators satisfy an exact
Manipulation Robustness of Collaborative Filtering
Benjamin Van Roy; Xiang Yan
2010-01-01
A collaborative filtering system recommends to users products that similar users like. Collaborative filtering systems influence purchase decisions and hence have become targets of manipulation by unscrupulous vendors. We demonstrate that nearest neighbors algorithms, which are widely used in commercial systems, are highly susceptible to manipulation and introduce new collaborative filtering algorithms that are relatively robust.
Robustness Regions for Dichotomous Decisions.
Vijn, Pieter; Molenaar, Ivo W.
1981-01-01
In the case of dichotomous decisions, the total set of all assumptions/specifications for which the decision would have been the same is the robustness region. Inspection of this (data-dependent) region is a form of sensitivity analysis which may lead to improved decision making. (Author/BW)
Theoretical Framework for Robustness Evaluation
DEFF Research Database (Denmark)
Sørensen, John Dalsgaard
2011-01-01
This paper presents a theoretical framework for evaluation of robustness of structural systems, incl. bridges and buildings. Typically modern structural design codes require that ‘the consequence of damages to structures should not be disproportional to the causes of the damages’. However, althou...
Robust control design with MATLAB
Gu, Da-Wei; Konstantinov, Mihail M
2013-01-01
Robust Control Design with MATLAB® (second edition) helps the student to learn how to use well-developed advanced robust control design methods in practical cases. To this end, several realistic control design examples from teaching-laboratory experiments, such as a two-wheeled, self-balancing robot, to complex systems like a flexible-link manipulator are given detailed presentation. All of these exercises are conducted using MATLAB® Robust Control Toolbox 3, Control System Toolbox and Simulink®. By sharing their experiences in industrial cases with minimum recourse to complicated theories and formulae, the authors convey essential ideas and useful insights into robust industrial control systems design using major H-infinity optimization and related methods allowing readers quickly to move on with their own challenges. The hands-on tutorial style of this text rests on an abundance of examples and features for the second edition: · rewritten and simplified presentation of theoretical and meth...
Robust Portfolio Optimization Using Pseudodistances
2015-01-01
The presence of outliers in financial asset returns is a frequently occurring phenomenon which may lead to unreliable mean-variance optimized portfolios. This fact is due to the unbounded influence that outliers can have on the mean returns and covariance estimators that are inputs in the optimization procedure. In this paper we present robust estimators of mean and covariance matrix obtained by minimizing an empirical version of a pseudodistance between the assumed model and the true model underlying the data. We prove and discuss theoretical properties of these estimators, such as affine equivariance, B-robustness, asymptotic normality and asymptotic relative efficiency. These estimators can be easily used in place of the classical estimators, thereby providing robust optimized portfolios. A Monte Carlo simulation study and applications to real data show the advantages of the proposed approach. We study both in-sample and out-of-sample performance of the proposed robust portfolios comparing them with some other portfolios known in literature. PMID:26468948
Facial Symmetry in Robust Anthropometrics
Czech Academy of Sciences Publication Activity Database
Kalina, Jan
2012-01-01
Roč. 57, č. 3 (2012), s. 691-698 ISSN 0022-1198 R&D Projects: GA MŠk(CZ) 1M06014 Institutional research plan: CEZ:AV0Z10300504 Keywords : forensic science * anthropology * robust image analysis * correlation analysis * multivariate data * classification Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 1.244, year: 2012
Sparse and Robust Factor Modelling
C. Croux (Christophe); P. Exterkate (Peter)
2011-01-01
textabstractFactor construction methods are widely used to summarize a large panel of variables by means of a relatively small number of representative factors. We propose a novel factor construction procedure that enjoys the properties of robustness to outliers and of sparsity; that is, having
Robust distributed cognitive relay beamforming
Pandarakkottilil, Ubaidulla; Aissa, Sonia
2012-01-01
design takes into account a parameter of the error in the channel state information (CSI) to render the performance of the beamformer robust in the presence of imperfect CSI. Though the original problem is non-convex, we show that the proposed design can
Approximability of Robust Network Design
Olver, N.K.; Shepherd, F.B.
2014-01-01
We consider robust (undirected) network design (RND) problems where the set of feasible demands may be given by an arbitrary convex body. This model, introduced by Ben-Ameur and Kerivin [Ben-Ameur W, Kerivin H (2003) New economical virtual private networks. Comm. ACM 46(6):69-73], generalizes the
Robust Control Design via Linear Programming
Keel, L. H.; Bhattacharyya, S. P.
1998-01-01
This paper deals with the problem of synthesizing or designing a feedback controller of fixed dynamic order. The closed loop specifications considered here are given in terms of a target performance vector representing a desired set of closed loop transfer functions connecting various signals. In general these point targets are unattainable with a fixed order controller. By enlarging the target from a fixed point set to an interval set the solvability conditions with a fixed order controller are relaxed and a solution is more easily enabled. Results from the parametric robust control literature can be used to design the interval target family so that the performance deterioration is acceptable, even when plant uncertainty is present. It is shown that it is possible to devise a computationally simple linear programming approach that attempts to meet the desired closed loop specifications.
Robust Adaptive Thresholder For Document Scanning Applications
Hsing, To R.
1982-12-01
In document scanning applications, thresholding is used to obtain binary data from a scanner. However, due to: (1) a wide range of different color backgrounds; (2) density variations of printed text information; and (3) the shading effect caused by the optical systems, the use of adaptive thresholding to enhance the useful information is highly desired. This paper describes a new robust adaptive thresholder for obtaining valid binary images. It is basically a memory type algorithm which can dynamically update the black and white reference level to optimize a local adaptive threshold function. The results of high image quality from different types of simulate test patterns can be obtained by this algorithm. The software algorithm is described and experiment results are present to describe the procedures. Results also show that the techniques described here can be used for real-time signal processing in the varied applications.
Trading Robustness Requirements in Mars Entry Trajectory Design
Lafleur, Jarret M.
2009-01-01
One of the most important metrics characterizing an atmospheric entry trajectory in preliminary design is the size of its predicted landing ellipse. Often, requirements for this ellipse are set early in design and significantly influence both the expected scientific return from a particular mission and the cost of development. Requirements typically specify a certain probability level (6-level) for the prescribed ellipse, and frequently this latter requirement is taken at 36. However, searches for the justification of 36 as a robustness requirement suggest it is an empirical rule of thumb borrowed from non-aerospace fields. This paper presents an investigation into the sensitivity of trajectory performance to varying robustness (6-level) requirements. The treatment of robustness as a distinct objective is discussed, and an analysis framework is presented involving the manipulation of design variables to effect trades between performance and robustness objectives. The scenario for which this method is illustrated is the ballistic entry of an MSL-class Mars entry vehicle. Here, the design variable is entry flight path angle, and objectives are parachute deploy altitude performance and error ellipse robustness. Resulting plots show the sensitivities between these objectives and trends in the entry flight path angles required to design to these objectives. Relevance to the trajectory designer is discussed, as are potential steps for further development and use of this type of analysis.
DEFF Research Database (Denmark)
Kemmler, S.; Eifler, Tobias; Bertsche, B.
2015-01-01
products are and vice versa. For a comprehensive understanding and to use existing synergies between both domains, this paper discusses the basic principles of Reliability- and Robust Design theory. The development of a comprehensive model will enable an integrated consideration of both domains...
Adaptive robust Kalman filtering for precise point positioning
International Nuclear Information System (INIS)
Guo, Fei; Zhang, Xiaohong
2014-01-01
The optimality of precise point postioning (PPP) solution using a Kalman filter is closely connected to the quality of the a priori information about the process noise and the updated mesurement noise, which are sometimes difficult to obtain. Also, the estimation enviroment in the case of dynamic or kinematic applications is not always fixed but is subject to change. To overcome these problems, an adaptive robust Kalman filtering algorithm, the main feature of which introduces an equivalent covariance matrix to resist the unexpected outliers and an adaptive factor to balance the contribution of observational information and predicted information from the system dynamic model, is applied for PPP processing. The basic models of PPP including the observation model, dynamic model and stochastic model are provided first. Then an adaptive robust Kalmam filter is developed for PPP. Compared with the conventional robust estimator, only the observation with largest standardized residual will be operated by the IGG III function in each iteration to avoid reducing the contribution of the normal observations or even filter divergence. Finally, tests carried out in both static and kinematic modes have confirmed that the adaptive robust Kalman filter outperforms the classic Kalman filter by turning either the equivalent variance matrix or the adaptive factor or both of them. This becomes evident when analyzing the positioning errors in flight tests at the turns due to the target maneuvering and unknown process/measurement noises. (paper)
An Integrated Approach to Single-Leg Airline Revenue Management: The Role of Robust Optimization
Birbil, S.I.; Frenk, J.B.G.; Gromicho, J.A.S.; Zhang, S.
2006-01-01
textabstractIn this paper we introduce robust versions of the classical static and dynamic single leg seat allocation models as analyzed by Wollmer, and Lautenbacher and Stidham, respectively. These robust models take into account the inaccurate estimates of the underlying probability distributions. As observed by simulation experiments it turns out that for these robust versions the variability compared to their classical counter parts is considerably reduced with a negligible decrease of av...
New robust chaotic system with exponential quadratic term
International Nuclear Information System (INIS)
Bao Bocheng; Li Chunbiao; Liu Zhong; Xu Jianping
2008-01-01
This paper proposes a new robust chaotic system of three-dimensional quadratic autonomous ordinary differential equations by introducing an exponential quadratic term. This system can display a double-scroll chaotic attractor with only two equilibria, and can be found to be robust chaotic in a very wide parameter domain with positive maximum Lyapunov exponent. Some basic dynamical properties and chaotic behaviour of novel attractor are studied. By numerical simulation, this paper verifies that the three-dimensional system can also evolve into periodic and chaotic behaviours by a constant controller. (general)
Centrality Robustness and Link Prediction in Complex Social Networks
DEFF Research Database (Denmark)
Davidsen, Søren Atmakuri; Ortiz-Arroyo, Daniel
2012-01-01
. Secondly, we present a method to predict edges in dynamic social networks. Our experimental results indicate that the robustness of the centrality measures applied to more realistic social networks follows a predictable pattern and that the use of temporal statistics could improve the accuracy achieved......This chapter addresses two important issues in social network analysis that involve uncertainty. Firstly, we present am analysis on the robustness of centrality measures that extend the work presented in Borgati et al. using three types of complex network structures and one real social network...
Kumar, Akhil; Srivastava, Gaurava; Srivastava, Swati; Verma, Seema; Negi, Arvind S; Sharma, Ashok
2017-08-01
BACE-1 and GSK-3β are potential therapeutic drug targets for Alzheimer's disease. Recently, both the targets received attention for designing dual inhibitors for Alzheimer's disease. Until now, only two-scaffold triazinone and curcumin have been reported as BACE-1 and GSK-3β dual inhibitors. Docking, molecular dynamics, clustering, binding energy, and network analysis of triazinone derivatives with BACE-1 and GSK-3β was performed to get molecular insight into the first reported dual inhibitor. Further, we designed and evaluated a naphthofuran series for its ability to inhibit BACE-1 and GSK-3β with the computational approaches. Docking study of naphthofuran series showed a good binding affinity towards both the targets. Molecular dynamics, binding energy, and network analysis were performed to compare their binding with the targets and amino acids responsible for binding. Naphthofuran series derivatives showed good interaction within the active site residues of both of the targets. Hydrogen bond occupancy and binding energy suggested strong binding with the targets. Dual-inhibitor binding was mostly governed by the hydrophobic interactions for both of the targets. Per residue energy decomposition and network analysis identified the key residues involved in the binding and inhibiting BACE-1 and GSK-3β. The results indicated that naphthofuran series derivative 11 may be a promising first-in-class dual inhibitor against BACE-1 and GSK-3β. This naphthofuran series may be further explored to design better dual inhibitors. Graphical abstract Naphthofuran derivative as a dual inhibitor for BACE-1 and GSK-3β.
Quantum theory as the most robust description of reproducible experiments
De Raedt, Hans; Katsnelson, Mikhail I.; Michielsen, Kristel
2014-08-01
knowledge always starts from the middle, that is, from the world of macroscopic objects. According to Bohr, the quantum theoretical description crucially depends on the existence of macroscopic objects which can be used as measuring devices. For an extensive analysis of the quantum measurement process from a dynamical point of view see Ref. [51]. Most importantly, the description of the macroscopic level is robust, that is, essentially independent of the underlying "more fundamental" picture [2]. As will be seen later, formalizing the notion of "robustness" is key to derive the basic equations of quantum theory from the general framework of logical inference.Key assumptions of the deductive approach are that the mathematical description is a complete description of the experiment under consideration and that there is no uncertainty about the conditions under which the experiment is carried out. If the theory does not fully account for all the relevant aspects of the phenomenon that we wish to describe, the general rules by which we deduce whether a proposition is true or false can no longer be used. However, in these circumstances, we can still resort to logical inference [37-41] to find useful answers to unambiguous questions. Of course, in general it will no longer be possible to say whether a proposition is true or false, hence there will always remain a residue of doubt. However, as will be shown, the description obtained through logical inference may also be unambiguous and independent of the individual.In the present paper, we demonstrate that the basic equations of quantum theory directly follow from logical inference applied to experiments in which there is uncertainty about individual events, the stringent condition that certain properties of the collection of events are reproducible, meaning that they are robust with respect to small changes in the conditions under which the experiments are carried out.
Robust Watermarking of Video Streams
Directory of Open Access Journals (Sweden)
T. Polyák
2006-01-01
Full Text Available In the past few years there has been an explosion in the use of digital video data. Many people have personal computers at home, and with the help of the Internet users can easily share video files on their computer. This makes possible the unauthorized use of digital media, and without adequate protection systems the authors and distributors have no means to prevent it.Digital watermarking techniques can help these systems to be more effective by embedding secret data right into the video stream. This makes minor changes in the frames of the video, but these changes are almost imperceptible to the human visual system. The embedded information can involve copyright data, access control etc. A robust watermark is resistant to various distortions of the video, so it cannot be removed without affecting the quality of the host medium. In this paper I propose a video watermarking scheme that fulfills the requirements of a robust watermark.
Robust Decentralized Formation Flight Control
Directory of Open Access Journals (Sweden)
Zhao Weihua
2011-01-01
Full Text Available Motivated by the idea of multiplexed model predictive control (MMPC, this paper introduces a new framework for unmanned aerial vehicles (UAVs formation flight and coordination. Formulated using MMPC approach, the whole centralized formation flight system is considered as a linear periodic system with control inputs of each UAV subsystem as its periodic inputs. Divided into decentralized subsystems, the whole formation flight system is guaranteed stable if proper terminal cost and terminal constraints are added to each decentralized MPC formulation of the UAV subsystem. The decentralized robust MPC formulation for each UAV subsystem with bounded input disturbances and model uncertainties is also presented. Furthermore, an obstacle avoidance control scheme for any shape and size of obstacles, including the nonapriorily known ones, is integrated under the unified MPC framework. The results from simulations demonstrate that the proposed framework can successfully achieve robust collision-free formation flights.
Inefficient but robust public leadership.
Matsumura, Toshihiro; Ogawa, Akira
2014-01-01
We investigate endogenous timing in a mixed duopoly in a differentiated product market. We find that private leadership is better than public leadership from a social welfare perspective if the private firm is domestic, regardless of the degree of product differentiation. Nevertheless, the public leadership equilibrium is risk-dominant, and it is thus robust if the degree of product differentiation is high. We also find that regardless of the degree of product differentiation, the public lead...
Testing Heteroscedasticity in Robust Regression
Czech Academy of Sciences Publication Activity Database
Kalina, Jan
2011-01-01
Roč. 1, č. 4 (2011), s. 25-28 ISSN 2045-3345 Grant - others:GA ČR(CZ) GA402/09/0557 Institutional research plan: CEZ:AV0Z10300504 Keywords : robust regression * heteroscedasticity * regression quantiles * diagnostics Subject RIV: BB - Applied Statistics , Operational Research http://www.researchjournals.co.uk/documents/Vol4/06%20Kalina.pdf
Robust power system frequency control
Bevrani, Hassan
2014-01-01
This updated edition of the industry standard reference on power system frequency control provides practical, systematic and flexible algorithms for regulating load frequency, offering new solutions to the technical challenges introduced by the escalating role of distributed generation and renewable energy sources in smart electric grids. The author emphasizes the physical constraints and practical engineering issues related to frequency in a deregulated environment, while fostering a conceptual understanding of frequency regulation and robust control techniques. The resulting control strategi
Sensor-Based Activity Recognition with Dynamically Added Context
Directory of Open Access Journals (Sweden)
Jiahui Wen
2015-08-01
Full Text Available An activity recognition system essentially processes raw sensor data and maps them into latent activity classes. Most of the previous systems are built with supervised learning techniques and pre-defined data sources, and result in static models. However, in realistic and dynamic environments, original data sources may fail and new data sources become available, a robust activity recognition system should be able to perform evolution automatically with dynamic sensor availability in dynamic environments. In this paper, we propose methods that automatically incorporate dynamically available data sources to adapt and refine the recognition system at run-time. The system is built upon ensemble classifiers which can automatically choose the features with the most discriminative power. Extensive experimental results with publicly available datasets demonstrate the effectiveness of our methods.
Sternberg, Shlomo
2010-01-01
Celebrated mathematician Shlomo Sternberg, a pioneer in the field of dynamical systems, created this modern one-semester introduction to the subject for his classes at Harvard University. Its wide-ranging treatment covers one-dimensional dynamics, differential equations, random walks, iterated function systems, symbolic dynamics, and Markov chains. Supplementary materials offer a variety of online components, including PowerPoint lecture slides for professors and MATLAB exercises.""Even though there are many dynamical systems books on the market, this book is bound to become a classic. The the
An integrated approach to single-leg airline revenue management: The role of robust optimization
S.I. Birbil (Ilker); J.B.G. Frenk (Hans); J.A.S. Gromicho (Joaquim); S. Zhang (Shuzhong)
2006-01-01
textabstractIn this paper we introduce robust versions of the classical static and dynamic single leg seat allocation models as analyzed by Wollmer, and Lautenbacher and Stidham, respectively. These robust models take into account the inaccurate estimates of the underlying probability distributions.
Robust and accurate detection algorithm for multimode polymer optical FBG sensor system
DEFF Research Database (Denmark)
Ganziy, Denis; Jespersen, O.; Rose, B.
2015-01-01
We propose a novel dynamic gate algorithm (DGA) for robust and fast peak detection. The algorithm uses a threshold determined detection window and center of gravity algorithm with bias compensation. Our experiment demonstrates that the DGA method is fast and robust with better stability and accur...
Veldhoven, van R.H.M.; Roermund, van A.H.M.
2011-01-01
Sigma Delta converters are a very popular choice for the A/D converter in multi-standard, mobile and cellular receivers. Key A/D converter specifications are high dynamic range, robustness, scalability, low-power and low EMI. Robust Sigma Delta Converters presents a requirement derivation of a Sigma
An Integrated Approach to Single-Leg Airline Revenue Management: The Role of Robust Optimization
S.I. Birbil (Ilker); J.B.G. Frenk (Hans); J.A.S. Gromicho (Joaquim); S. Zhang (Shuzhong)
2006-01-01
textabstractIn this paper we introduce robust versions of the classical static and dynamic single leg seat allocation models as analyzed by Wollmer, and Lautenbacher and Stidham, respectively. These robust models take into account the inaccurate estimates of the underlying probability distributions.
Synchronizing a class of uncertain chaotic systems
International Nuclear Information System (INIS)
Chen Maoyin; Zhou Donghua; Shang Yun
2005-01-01
This Letter deals with the synchronization of a class of uncertain chaotic systems in the drive-response framework. A robust adaptive observer based response system is designed to synchronize a given chaotic system with unknown parameters and external disturbances. Lyapunov stability ensures the global synchronization between the drive and response systems even if Lipschitz constants on function matrices and bounds on uncertainties are unknown. Numerical simulation of Genesio-Tesi system verifies the effectiveness of this scheme
Exploiting short-term memory in soft body dynamics as a computational resource.
Nakajima, K; Li, T; Hauser, H; Pfeifer, R
2014-11-06
Soft materials are not only highly deformable, but they also possess rich and diverse body dynamics. Soft body dynamics exhibit a variety of properties, including nonlinearity, elasticity and potentially infinitely many degrees of freedom. Here, we demonstrate that such soft body dynamics can be employed to conduct certain types of computation. Using body dynamics generated from a soft silicone arm, we show that they can be exploited to emulate functions that require memory and to embed robust closed-loop control into the arm. Our results suggest that soft body dynamics have a short-term memory and can serve as a computational resource. This finding paves the way towards exploiting passive body dynamics for control of a large class of underactuated systems. © 2014 The Author(s) Published by the Royal Society. All rights reserved.
Name fashion dynamics and social class
Bloothooft, G.; Schraagen, M.P.
2011-01-01
Modern parents in The Netherlands choose the first names they like for their children. In this decision most follow fashion and as a typical property of fashion, many popular names now have a life cycle of only one generation. Some names show a symmetry between rise and fall of the name, but most
U.S. Environmental Protection Agency — A "Class 1" area is a geographic area recognized by the EPA as being of the highest environmental quality and requiring maximum protection. Class I areas are areas...
Town of Cary, North Carolina — This data is specific to Parks and Recreation classes, workshops, and activities within the course catalog. It contains an entry for upcoming classes.*This data set...
Observation Quality Control with a Robust Ensemble Kalman Filter
Roh, Soojin
2013-12-01
Current ensemble-based Kalman filter (EnKF) algorithms are not robust to gross observation errors caused by technical or human errors during the data collection process. In this paper, the authors consider two types of gross observational errors, additive statistical outliers and innovation outliers, and introduce a method to make EnKF robust to gross observation errors. Using both a one-dimensional linear system of dynamics and a 40-variable Lorenz model, the performance of the proposed robust ensemble Kalman filter (REnKF) was tested and it was found that the new approach greatly improves the performance of the filter in the presence of gross observation errors and leads to only a modest loss of accuracy with clean, outlier-free, observations.
Wavelet Filtering to Reduce Conservatism in Aeroservoelastic Robust Stability Margins
Brenner, Marty; Lind, Rick
1998-01-01
Wavelet analysis for filtering and system identification was used to improve the estimation of aeroservoelastic stability margins. The conservatism of the robust stability margins was reduced with parametric and nonparametric time-frequency analysis of flight data in the model validation process. Nonparametric wavelet processing of data was used to reduce the effects of external desirableness and unmodeled dynamics. Parametric estimates of modal stability were also extracted using the wavelet transform. Computation of robust stability margins for stability boundary prediction depends on uncertainty descriptions derived from the data for model validation. F-18 high Alpha Research Vehicle aeroservoelastic flight test data demonstrated improved robust stability prediction by extension of the stability boundary beyond the flight regime.
Reactive Robustness and Integrated Approaches for Railway Optimization Problems
DEFF Research Database (Denmark)
Haahr, Jørgen Thorlund
journeys helps the driver to drive efficiently and enhances robustness in a realistic (dynamic) environment. Four international scientific prizes have been awarded for distinct parts of the research during the course of this PhD project. The first prize was awarded for work during the \\2014 RAS Problem...... to absorb or withstand unexpected events such as delays. Making robust plans is central in order to maintain a safe and timely railway operation. This thesis focuses on reactive robustness, i.e., the ability to react once a plan is rendered infeasible in operation due to disruptions. In such time...... Solving Competition", where a freight yard optimization problem was considered. The second junior (PhD) prize was awared for the work performed in the \\ROADEF/EURO Challenge 2014: Trains don't vanish!", where the planning of rolling stock movements at a large station was considered. An honorable mention...
Robust Temperature Control of a Thermoelectric Cooler via μ -Synthesis
Kürkçü, Burak; Kasnakoğlu, Coşku
2018-02-01
In this work robust temperature control of a thermoelectric cooler (TEC) via μ -synthesis is studied. An uncertain dynamical model for the TEC that is suitable for robust control methods is derived. The model captures variations in operating point due to current, load and temperature changes. A temperature controller is designed utilizing μ -synthesis, a powerful method guaranteeing robust stability and performance. For comparison two well-known control methods, namely proportional-integral-derivative (PID) and internal model control (IMC), are also realized to benchmark the proposed approach. It is observed that the stability and performance on the nominal model are satisfactory for all cases. On the other hand, under perturbations the responses of PID and IMC deteriorate and even become unstable. In contrast, the μ -synthesis controller succeeds in keeping system stability and achieving good performance under all perturbations within the operating range, while at the same time providing good disturbance rejection.
Robust Model Predictive Control of a Wind Turbine
DEFF Research Database (Denmark)
Mirzaei, Mahmood; Poulsen, Niels Kjølstad; Niemann, Hans Henrik
2012-01-01
In this work the problem of robust model predictive control (robust MPC) of a wind turbine in the full load region is considered. A minimax robust MPC approach is used to tackle the problem. Nonlinear dynamics of the wind turbine are derived by combining blade element momentum (BEM) theory...... of the uncertain system is employed and a norm-bounded uncertainty model is used to formulate a minimax model predictive control. The resulting optimization problem is simplified by semidefinite relaxation and the controller obtained is applied on a full complexity, high fidelity wind turbine model. Finally...... and first principle modeling of the turbine flexible structure. Thereafter the nonlinear model is linearized using Taylor series expansion around system operating points. Operating points are determined by effective wind speed and an extended Kalman filter (EKF) is employed to estimate this. In addition...
Observation Quality Control with a Robust Ensemble Kalman Filter
Roh, Soojin; Genton, Marc G.; Jun, Mikyoung; Szunyogh, Istvan; Hoteit, Ibrahim
2013-01-01
Current ensemble-based Kalman filter (EnKF) algorithms are not robust to gross observation errors caused by technical or human errors during the data collection process. In this paper, the authors consider two types of gross observational errors, additive statistical outliers and innovation outliers, and introduce a method to make EnKF robust to gross observation errors. Using both a one-dimensional linear system of dynamics and a 40-variable Lorenz model, the performance of the proposed robust ensemble Kalman filter (REnKF) was tested and it was found that the new approach greatly improves the performance of the filter in the presence of gross observation errors and leads to only a modest loss of accuracy with clean, outlier-free, observations.
ADSL Transceivers Applying DSM and Their Nonstationary Noise Robustness
Directory of Open Access Journals (Sweden)
Bostoen Tom
2006-01-01
Full Text Available Dynamic spectrum management (DSM comprises a new set of techniques for multiuser power allocation and/or detection in digital subscriber line (DSL networks. At the Alcatel Research and Innovation Labs, we have recently developed a DSM test bed, which allows the performance of DSM algorithms to be evaluated in practice. With this test bed, we have evaluated the performance of a DSM level-1 algorithm known as iterative water-filling in an ADSL scenario. This paper describes the results of, on the one hand, the performance gains achieved with iterative water-filling, and, on the other hand, the nonstationary noise robustness of DSM-enabled ADSL modems. It will be shown that DSM trades off nonstationary noise robustness for performance improvements. A new bit swap procedure is then introduced to increase the noise robustness when applying DSM.
Employing Sensitivity Derivatives for Robust Optimization under Uncertainty in CFD
Newman, Perry A.; Putko, Michele M.; Taylor, Arthur C., III
2004-01-01
A robust optimization is demonstrated on a two-dimensional inviscid airfoil problem in subsonic flow. Given uncertainties in statistically independent, random, normally distributed flow parameters (input variables), an approximate first-order statistical moment method is employed to represent the Computational Fluid Dynamics (CFD) code outputs as expected values with variances. These output quantities are used to form the objective function and constraints. The constraints are cast in probabilistic terms; that is, the probability that a constraint is satisfied is greater than or equal to some desired target probability. Gradient-based robust optimization of this stochastic problem is accomplished through use of both first and second-order sensitivity derivatives. For each robust optimization, the effect of increasing both input standard deviations and target probability of constraint satisfaction are demonstrated. This method provides a means for incorporating uncertainty when considering small deviations from input mean values.
Class Notes for "Class-Y-News."
Stuart, Judy L.
1991-01-01
A self-contained class of students with mild to moderate disabilities published a monthly newsletter which was distributed to students' families. Students became involved in writing, typing, drawing, folding, basic editing, and disseminating. (JDD)
Analysis of robustness of urban bus network
Tao, Ren; Yi-Fan, Wang; Miao-Miao, Liu; Yan-Jie, Xu
2016-02-01
In this paper, the invulnerability and cascade failures are discussed for the urban bus network. Firstly, three static models(bus stop network, bus transfer network, and bus line network) are used to analyse the structure and invulnerability of urban bus network in order to understand the features of bus network comprehensively. Secondly, a new way is proposed to study the invulnerability of urban bus network by modelling two layered networks, i.e., the bus stop-line network and the bus line-transfer network and then the interactions between different models are analysed. Finally, by modelling a new layered network which can reflect the dynamic passenger flows, the cascade failures are discussed. Then a new load redistribution method is proposed to study the robustness of dynamic traffic. In this paper, the bus network of Shenyang City which is one of the biggest cities in China, is taken as a simulation example. In addition, some suggestions are given to improve the urban bus network and provide emergency strategies when traffic congestion occurs according to the numerical simulation results. Project supported by the National Natural Science Foundation of China (Grant Nos. 61473073, 61374178, 61104074, and 61203329), the Fundamental Research Funds for the Central Universities (Grant Nos. N130417006, L1517004), and the Program for Liaoning Excellent Talents in University (Grant No. LJQ2014028).
Robust Force Control of Series Elastic Actuators
Directory of Open Access Journals (Sweden)
Andrea Calanca
2014-07-01
Full Text Available Force-controlled series elastic actuators (SEA are widely used in novel human-robot interaction (HRI applications, such as assistive and rehabilitation robotics. These systems are characterized by the presence of the “human in the loop”, so that control response and stability depend on uncertain human dynamics, including reflexes and voluntary forces. This paper proposes a force control approach that guarantees the stability and robustness of the coupled human-robot system, based on sliding-mode control (SMC, considering the human dynamics as a disturbance to reject. We propose a chattering free solution that employs simple task models to obtain high performance, comparable with second order solutions. Theoretical stability is proven within the sliding mode framework, and predictability is reached by avoiding the reaching phase by design. Furthermore, safety is introduced by a proper design of the sliding surface. The practical feasibility of the approach is shown using an SEA prototype coupled with a human impedance in severe stress tests. To show the quality of the approach, we report a comparison with state-of-the-art second order SMC, passivity-based control and adaptive control solutions.
UAV Robust Strategy Control Based on MAS
Directory of Open Access Journals (Sweden)
Jian Han
2014-01-01
Full Text Available A novel multiagent system (MAS has been proposed to integrate individual UAV (unmanned aerial vehicle to form a UAV team which can accomplish complex missions with better efficiency and effect. The MAS based UAV team control is more able to conquer dynamic situations and enhance the performance of any single UAV. In this paper, the MAS proposed and established combines the reacting and thinking abilities to be an initiative and autonomous hybrid system which can solve missions involving coordinated flight and cooperative operation. The MAS uses BDI model to support its logical perception and to classify the different missions; then the missions will be allocated by utilizing auction mechanism after analyzing dynamic parameters. Prim potential algorithm, particle swarm algorithm, and reallocation mechanism are proposed to realize the rational decomposing and optimal allocation in order to reach the maximum profit. After simulation, the MAS has been proved to be able to promote the success ratio and raise the robustness, while realizing feasibility of coordinated flight and optimality of cooperative mission.
Classed identities in adolescence
Jay, Sarah
2015-01-01
peer-reviewed The central argument of this thesis is that social class remains a persistent system of inequality in education, health, life chances and opportunities. Therefore class matters. But why is it that so little attention has been paid to class in the psychological literature? Three papers are presented here which draw together theoretical advances in psychological understandings of group processes and sociological understandings of the complexity of class. As western labour marke...
Robust two degree of freedom vehicle steering control satisfying mixed sensitivity constraint
Aksun-Güvenc, B.; Güvenc, L.; Odenthal, D.; Bünte, T.
2001-01-01
Robust steering control is used here for improving the yaw dynamics of a passenger car. A specific two degree of freedom control structure is adapted to the vehicle yaw dynamics problem and shown to robustly improve performance. The design study is based on six operating conditions for vehicle speed and the coefficient of friction between the tires and the road representing the operating domain of the vehicle. The relevant design specifications are formulated as attaining Hurwitz stability a...
Robustness Analysis of Timber Truss Structure
DEFF Research Database (Denmark)
Rajčić, Vlatka; Čizmar, Dean; Kirkegaard, Poul Henning
2010-01-01
The present paper discusses robustness of structures in general and the robustness requirements given in the codes. Robustness of timber structures is also an issues as this is closely related to Working group 3 (Robustness of systems) of the COST E55 project. Finally, an example of a robustness...... evaluation of a widespan timber truss structure is presented. This structure was built few years ago near Zagreb and has a span of 45m. Reliability analysis of the main members and the system is conducted and based on this a robustness analysis is preformed....
Supervised linear dimensionality reduction with robust margins for object recognition
Dornaika, F.; Assoum, A.
2013-01-01
Linear Dimensionality Reduction (LDR) techniques have been increasingly important in computer vision and pattern recognition since they permit a relatively simple mapping of data onto a lower dimensional subspace, leading to simple and computationally efficient classification strategies. Recently, many linear discriminant methods have been developed in order to reduce the dimensionality of visual data and to enhance the discrimination between different groups or classes. Many existing linear embedding techniques relied on the use of local margins in order to get a good discrimination performance. However, dealing with outliers and within-class diversity has not been addressed by margin-based embedding method. In this paper, we explored the use of different margin-based linear embedding methods. More precisely, we propose to use the concepts of Median miss and Median hit for building robust margin-based criteria. Based on such margins, we seek the projection directions (linear embedding) such that the sum of local margins is maximized. Our proposed approach has been applied to the problem of appearance-based face recognition. Experiments performed on four public face databases show that the proposed approach can give better generalization performance than the classic Average Neighborhood Margin Maximization (ANMM). Moreover, thanks to the use of robust margins, the proposed method down-grades gracefully when label outliers contaminate the training data set. In particular, we show that the concept of Median hit was crucial in order to get robust performance in the presence of outliers.
Robust and Sparse Factor Modelling
DEFF Research Database (Denmark)
Croux, Christophe; Exterkate, Peter
Factor construction methods are widely used to summarize a large panel of variables by means of a relatively small number of representative factors. We propose a novel factor construction procedure that enjoys the properties of robustness to outliers and of sparsity; that is, having relatively few...... nonzero factor loadings. Compared to the traditional factor construction method, we find that this procedure leads to a favorable forecasting performance in the presence of outliers and to better interpretable factors. We investigate the performance of the method in a Monte Carlo experiment...
Robustness Evaluation of Timber Structures
DEFF Research Database (Denmark)
Kirkegaard, Poul Henning; Sørensen, John Dalsgaard; čizmar, D.
2010-01-01
The present paper outlines results from working group 3 (WG3) in the EU COST Action E55 – ‘Modelling of the performance of timber structures’. The objectives of the project are related to the three main research activities: the identification and modelling of relevant load and environmental...... exposure scenarios, the improvement of knowledge concerning the behaviour of timber structural elements and the development of a generic framework for the assessment of the life-cycle vulnerability and robustness of timber structures....
Sustainable Resilient, Robust & Resplendent Enterprises
DEFF Research Database (Denmark)
Edgeman, Rick
to their impact. Resplendent enterprises are introduced with resplendence referring not to some sort of public or private façade, but instead refers to organizations marked by dual brilliance and nobility of strategy, governance and comportment that yields superior and sustainable triple bottom line performance....... Herein resilience, robustness, and resplendence (R3) are integrated with sustainable enterprise excellence (Edgeman and Eskildsen, 2013) or SEE and social-ecological innovation (Eskildsen and Edgeman, 2012) to aid progress of a firm toward producing continuously relevant performance that proceed from...
Robust and efficient walking with spring-like legs
Energy Technology Data Exchange (ETDEWEB)
Rummel, J; Blum, Y; Seyfarth, A, E-mail: juergen.rummel@uni-jena.d, E-mail: andre.seyfarth@uni-jena.d [Lauflabor Locomotion Laboratory, University of Jena, Dornburger Strasse 23, 07743 Jena (Germany)
2010-12-15
The development of bipedal walking robots is inspired by human walking. A way of implementing walking could be performed by mimicking human leg dynamics. A fundamental model, representing human leg dynamics during walking and running, is the bipedal spring-mass model which is the basis for this paper. The aim of this study is the identification of leg parameters leading to a compromise between robustness and energy efficiency in walking. It is found that, compared to asymmetric walking, symmetric walking with flatter angles of attack reveals such a compromise. With increasing leg stiffness, energy efficiency increases continuously. However, robustness is the maximum at moderate leg stiffness and decreases slightly with increasing stiffness. Hence, an adjustable leg compliance would be preferred, which is adaptable to the environment. If the ground is even, a high leg stiffness leads to energy efficient walking. However, if external perturbations are expected, e.g. when the robot walks on uneven terrain, the leg should be softer and the angle of attack flatter. In the case of underactuated robots with constant physical springs, the leg stiffness should be larger than k-tilde = 14 in order to use the most robust gait. Soft legs, however, lack in both robustness and efficiency.
Robust and efficient walking with spring-like legs
International Nuclear Information System (INIS)
Rummel, J; Blum, Y; Seyfarth, A
2010-01-01
The development of bipedal walking robots is inspired by human walking. A way of implementing walking could be performed by mimicking human leg dynamics. A fundamental model, representing human leg dynamics during walking and running, is the bipedal spring-mass model which is the basis for this paper. The aim of this study is the identification of leg parameters leading to a compromise between robustness and energy efficiency in walking. It is found that, compared to asymmetric walking, symmetric walking with flatter angles of attack reveals such a compromise. With increasing leg stiffness, energy efficiency increases continuously. However, robustness is the maximum at moderate leg stiffness and decreases slightly with increasing stiffness. Hence, an adjustable leg compliance would be preferred, which is adaptable to the environment. If the ground is even, a high leg stiffness leads to energy efficient walking. However, if external perturbations are expected, e.g. when the robot walks on uneven terrain, the leg should be softer and the angle of attack flatter. In the case of underactuated robots with constant physical springs, the leg stiffness should be larger than k-tilde = 14 in order to use the most robust gait. Soft legs, however, lack in both robustness and efficiency.
Hybrid surface design for robust superhydrophobicity.
Dash, Susmita; Alt, Marie T; Garimella, Suresh V
2012-06-26
Surfaces may be rendered superhydrophobic by engineering the surface morphology to control the extent of the liquid-air interface and by the use of low-surface-energy coatings. The droplet state on a superhydrophobic surface under static and dynamic conditions may be explained in terms of the relative magnitudes of the wetting and antiwetting pressures acting at the liquid-air interface on the substrate. In this paper, we discuss the design and fabrication of hollow hybrid superhydrophobic surfaces which incorporate both communicating and noncommunicating air gaps. The surface design is analytically shown to exhibit higher capillary (or nonwetting) pressure compared to solid pillars with only communicating air gaps. Six hybrid surfaces are fabricated with different surface parameters selected such that the Cassie state of a droplet is energetically favorable. The robustness of the surfaces is tested under dynamic impingement conditions, and droplet dynamics are explained using pressure-based transitions between Cassie and Wenzel states. During droplet impingement, the effective water hammer pressure acting due to the sudden change in the velocity of the droplet is determined experimentally and is found to be at least 2 orders of magnitude less than values reported in the literature. The experiments show that the water hammer pressure depends on the surface morphology and capillary pressure of the surface. We propose that the observed reduction in shock pressure may be attributed to the presence of air gaps in the substrate. This feature allows liquid deformation and hence avoids the sudden stoppage of the droplet motion as opposed to droplet behavior on smooth surfaces.
Robust Instrumentation[Water treatment for power plant]; Robust Instrumentering
Energy Technology Data Exchange (ETDEWEB)
Wik, Anders [Vattenfall Utveckling AB, Stockholm (Sweden)
2003-08-01
Cementa Slite Power Station is a heat recovery steam generator (HRSG) with moderate steam data; 3.0 MPa and 420 deg C. The heat is recovered from Cementa, a cement industry, without any usage of auxiliary fuel. The Power station commenced operation in 2001. The layout of the plant is unusual, there are no similar in Sweden and very few world-wide, so the operational experiences are limited. In connection with the commissioning of the power plant a R and D project was identified with the objective to minimise the manpower needed for chemistry management of the plant. The lean chemistry management is based on robust instrumentation and chemical-free water treatment plant. The concept with robust instrumentation consists of the following components; choice of on-line instrumentation with a minimum of O and M and a chemical-free water treatment. The parameters are specific conductivity, cation conductivity, oxygen and pH. In addition to that, two fairly new on-line instruments were included; corrosion monitors and differential pH calculated from specific and cation conductivity. The chemical-free water treatment plant consists of softening, reverse osmosis and electro-deionisation. The operational experience shows that the cycle chemistry is not within the guidelines due to major problems with the operation of the power plant. These problems have made it impossible to reach steady state and thereby not viable to fully verify and validate the concept with robust instrumentation. From readings on the panel of the online analysers some conclusions may be drawn, e.g. the differential pH measurements have fulfilled the expectations. The other on-line analysers have been working satisfactorily apart from contamination with turbine oil, which has been noticed at least twice. The corrosion monitors seem to be working but the lack of trend curves from the mainframe computer system makes it hard to draw any clear conclusions. The chemical-free water treatment has met all
Robust Optimization of Fourth Party Logistics Network Design under Disruptions
Directory of Open Access Journals (Sweden)
Jia Li
2015-01-01
Full Text Available The Fourth Party Logistics (4PL network faces disruptions of various sorts under the dynamic and complex environment. In order to explore the robustness of the network, the 4PL network design with consideration of random disruptions is studied. The purpose of the research is to construct a 4PL network that can provide satisfactory service to customers at a lower cost when disruptions strike. Based on the definition of β-robustness, a robust optimization model of 4PL network design under disruptions is established. Based on the NP-hard characteristic of the problem, the artificial fish swarm algorithm (AFSA and the genetic algorithm (GA are developed. The effectiveness of the algorithms is tested and compared by simulation examples. By comparing the optimal solutions of the 4PL network for different robustness level, it is indicated that the robust optimization model can evade the market risks effectively and save the cost in the maximum limit when it is applied to 4PL network design.
Designing robust control-based HIV-treatment
Directory of Open Access Journals (Sweden)
Fredy Andrés Olarte Dussán
2008-05-01
Full Text Available Designing a robust control-based treatment for human immunodeficiency virus (HIV-infected patients was studied. The dynamics of the immune system’s response to infection was modelled using a 5th order nonlinear model with separate efficacy coefficients for protease inhibitor (PIs and reverse transcriptase inhibitors (RTIs. The immune res-ponse has been represented as an uncertain system due to errors in parameter estimation and the existence of un-modelled dynamics. A polytopic system was constructed incorporating all possible system parameter values. A con-trol system was designed using robust pole location techniques stabilising the polytopic system around an equilibrium point having a low viral load. Numerical simulation results (including the organism’s pharmacokinetical response to anti-retroviral drugs showed that the control law could lead to long-term stable conditions, even in extreme cases.
Robustness and Contingent History: From Prisoner's Dilemma to Gaia Theory.
Harvey, Inman
2018-01-01
In both social systems and ecosystems there is a need to resolve potential conflicts between the interests of individuals and the collective interest of the community. The collective interests need to survive the turbulent dynamics of social and ecological interactions. To see how different systems with different sets of interactions have different degrees of robustness, we need to look at their different contingent histories. We analyze abstract artificial life models of such systems, and note that some prominent examples rely on explicitly ahistorical frameworks; we point out where analyses that ignore a contingent historical context can be fatally flawed. The mathematical foundations of Gaia theory are presented in a form whose very basic and general assumptions point to wide applicability across complex dynamical systems. This highlights surprising connections between robustness and accumulated contingent happenstance, regardless of whether Darwinian evolution is or is not implicated. Real-life studies highlight the role of history, and artificial life studies should do likewise.