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Sample records for robust dynamic classes

  1. 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

  2. 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

  3. 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.

  4. 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

  5. Robustness analysis of uncertain dynamical neural networks with multiple time delays.

    Science.gov (United States)

    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.

  6. Nonlinear Dynamics in Gene Regulation Promote Robustness and Evolvability of Gene Expression Levels.

    Science.gov (United States)

    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

  7. 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

  8. 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.

  9. Robust uniform persistence in discrete and continuous dynamical systems using Lyapunov exponents.

    Science.gov (United States)

    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.

  10. 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.

  11. A New Class of Particle Filters for Random Dynamic Systems with Unknown Statistics

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    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.

  12. Superlinearly scalable noise robustness of redundant coupled dynamical systems.

    Science.gov (United States)

    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.

  13. Robustness of dynamic systems with parameter uncertainties

    CERN Document Server

    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...

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

    Science.gov (United States)

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

    2014-03-01

    In this paper, the robust exponential synchronization problem for a class of uncertain delayed master-slave dynamical system is investigated by using the adaptive control method. Different from some existing master-slave models, the considered master-slave system includes bounded unmodeled dynamics. In order to compensate the effect of unmodeled dynamics and effectively achieve synchronization, a novel adaptive controller with simple updated laws is proposed. Moreover, the results are given in terms of LMIs, which can be easily solved by LMI Toolbox in Matlab. A numerical example is given to illustrate the effectiveness of the method. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

  15. Robust control synthesis for uncertain dynamical systems

    Science.gov (United States)

    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.

  16. Robust input design for nonlinear dynamic modeling of AUV.

    Science.gov (United States)

    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.

  17. 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:.

  18. Robust Control Design for Uncertain Nonlinear Dynamic Systems

    Science.gov (United States)

    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.

  19. 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

  20. Non-robust dynamic inferences from macroeconometric models: Bifurcation stratification of confidence regions

    Science.gov (United States)

    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.

  1. 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.

  2. Model predictive control of hybrid systems : stability and robustness

    NARCIS (Netherlands)

    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

  3. 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 ...

  4. Feedforward/feedback control synthesis for performance and robustness

    Science.gov (United States)

    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.

  5. 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.

  6. 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.

  7. 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...

  8. Robust Structural Analysis and Design of Distributed Control Systems to Prevent Zero Dynamics Attacks

    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.

  9. Dynamic optimization of distributed biological systems using robust and efficient numerical techniques.

    Science.gov (United States)

    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

  10. Robust dynamic classes revealed by measuring the response function of a social system.

    Science.gov (United States)

    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.

  11. Fuzzy Counter Propagation Neural Network Control for a Class of Nonlinear Dynamical Systems.

    Science.gov (United States)

    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.

  12. Fuzzy Counter Propagation Neural Network Control for a Class of Nonlinear Dynamical Systems

    Directory of Open Access Journals (Sweden)

    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.

  13. 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.

  14. 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)

  15. 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...

  16. 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 ...

  17. 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....

  18. About a Class of Positive Hybrid Dynamic Linear Systems and an Associate Extended Kalman-Yakubovich-Popov Lemma

    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.

  19. 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.

  20. Robust Fault Detection for a Class of Uncertain Nonlinear Systems Based on Multiobjective Optimization

    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.

  1. 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.

  2. 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 ...

  3. The structural dynamics of social class.

    Science.gov (United States)

    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.

  4. Nonlinear robust control of hypersonic aircrafts with interactions between flight dynamics and propulsion systems.

    Science.gov (United States)

    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.

  5. How Robust is Your System Resilience?

    Science.gov (United States)

    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.

  6. Robust Estimation and Moment Selection in Dynamic Fixed-effects Panel Data Models

    NARCIS (Netherlands)

    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

  7. Attractive ellipsoids in robust control

    CERN Document Server

    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...

  8. 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.

  9. Robust w-Estimators for Cryo-EM Class Means

    Science.gov (United States)

    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

  10. 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.

  11. Stochastic Mesocortical Dynamics and Robustness of Working Memory during Delay-Period.

    Science.gov (United States)

    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.

  12. An Improved Generalized Predictive Control in a Robust Dynamic Partial Least Square Framework

    Directory of Open Access Journals (Sweden)

    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.

  13. 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

  14. Designing Dynamic Adaptive Policy Pathways using Many-Objective Robust Decision Making

    Science.gov (United States)

    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.

  15. 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.

  16. A class of convergent neural network dynamics

    Science.gov (United States)

    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.

  17. Dynamical class of a two-dimensional plasmonic Dirac system.

    Science.gov (United States)

    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.

  18. 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...

  19. 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.

  20. Robust control of uncertain dynamic systems a linear state space approach

    CERN Document Server

    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...

  1. Robustness and Vulnerability of Networks with Dynamical Dependency Groups.

    Science.gov (United States)

    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.

  2. 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...

  3. Design and evaluation of a robust dynamic neurocontroller for a multivariable aircraft control problem

    Science.gov (United States)

    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.

  4. Recurrent-Neural-Network-Based Multivariable Adaptive Control for a Class of Nonlinear Dynamic Systems With Time-Varying Delay.

    Science.gov (United States)

    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.

  5. 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.

  6. Kinematically Optimal Robust Control of Redundant Manipulators

    Science.gov (United States)

    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.

  7. 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

  8. Dynamic robustness of knowledge collaboration network of open source product development community

    Science.gov (United States)

    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.

  9. Dynamic optimization and robust explicit model predictive control of hydrogen storage tank

    KAUST Repository

    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.

  10. Dynamic optimization and robust explicit model predictive control of hydrogen storage tank

    KAUST Repository

    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.

  11. Robust estimation and moment selection in dynamic fixed-effects panel data models

    NARCIS (Netherlands)

    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

  12. Robust dynamical decoupling for quantum computing and quantum memory.

    Science.gov (United States)

    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.

  13. 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.

  14. Position-Invariant Robust Features for Long-Term Recognition of Dynamic Outdoor Scenes

    Science.gov (United States)

    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.

  15. Robust Synchronization of Delayed Chaotic FitzHugh-Nagumo Neurons under External Electrical Stimulation

    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.

  16. Robust output observer-based control of neutral uncertain systems with discrete and distributed time delays: LMI optimization approach

    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

  17. 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....

  18. 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

  19. 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

  20. 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

  1. Design and implementation of an e-class about continuous dynamical systems

    NARCIS (Netherlands)

    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

  2. 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.

  3. Adaptive dynamic inversion robust control for BTT missile based on wavelet neural network

    Science.gov (United States)

    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.

  4. 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.

  5. A Robust and Efficient Numerical Method for RNA-Mediated Viral Dynamics

    Directory of Open Access Journals (Sweden)

    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.

  6. 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.

  7. 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 ...

  8. Robust and efficient parameter estimation in dynamic models of biological systems.

    Science.gov (United States)

    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.

  9. Dynamic analysis of a hepatitis B model with three-age-classes

    Science.gov (United States)

    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.

  10. Robust Exponential Synchronization for a Class of Master-Slave Distributed Parameter Systems with Spatially Variable Coefficients and Nonlinear Perturbation

    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.

  11. 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...

  12. 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)

  13. Preparatory steps for a robust dynamic model for organically bound tritium dynamics in agricultural crops

    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.

  14. 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.

  15. Dynamic Written Corrective Feedback in Developmental Multilingual Writing Classes

    Science.gov (United States)

    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…

  16. Increasing the Robustness of Biometric Templates for Dynamic Signature Biometric Systems

    OpenAIRE

    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...

  17. Robust output synchronization of heterogeneous nonlinear agents in uncertain networks.

    Science.gov (United States)

    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.

  18. Robust immunohistochemical staining of several classes of proteins in tissues subjected to autolysis.

    Science.gov (United States)

    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.

  19. Robustly Fitting and Forecasting Dynamical Data With Electromagnetically Coupled Artificial Neural Network: A Data Compression Method.

    Science.gov (United States)

    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.

  20. 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.

  1. A new class of ensemble conserving algorithms for approximate quantum dynamics: Theoretical formulation and model problems

    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

  2. Robust Approaches to Forecasting

    OpenAIRE

    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...

  3. Robust Optimization Approach for Design for a Dynamic Cell Formation Considering Labor Utilization: Bi-objective Mathematical Mode

    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.

  4. Robustness of Structures

    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...

  5. 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...

  6. Robustness: confronting lessons from physics and biology.

    Science.gov (United States)

    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.

  7. Robust control and linear parameter varying approaches application to vehicle dynamics

    CERN Document Server

    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...

  8. 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.

  9. Dynamic fracture toughness of ASME SA508 Class 2a ASME SA533 grade A Class 2 base and heat affected zone material and applicable weld metals

    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

  10. Network robustness assessed within a dual connectivity framework: joint dynamics of the Active and Idle Networks.

    Science.gov (United States)

    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.

  11. Robust and distributed hypothesis testing

    CERN Document Server

    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...

  12. 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.

  13. Neural network-based robust actuator fault diagnosis for a non-linear multi-tank system.

    Science.gov (United States)

    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.

  14. Step Detection Robust against the Dynamics of Smartphones

    Science.gov (United States)

    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

  15. 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.

  16. Robust Adaptive Stabilization of Linear Time-Invariant Dynamic Systems by Using Fractional-Order Holds and Multirate Sampling Controls

    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.

  17. 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)

  18. Variable-structure approaches analysis, simulation, robust control and estimation of uncertain dynamic processes

    CERN Document Server

    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.

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

    Directory of Open Access Journals (Sweden)

    Zhaoxia Peng

    2014-01-01

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

  20. Robust image registration for multiple exposure high dynamic range image synthesis

    Science.gov (United States)

    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..

  1. Mutual Information Based Dynamic Integration of Multiple Feature Streams for Robust Real-Time LVCSR

    Science.gov (United States)

    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.

  2. Dynamic Programming Used to Align Protein Structures with a Spectrum Is Robust

    Directory of Open Access Journals (Sweden)

    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.

  3. Ins-Robust Primitive Words

    OpenAIRE

    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...

  4. 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

  5. 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 ...

  6. Complex Dynamic Systems View on Conceptual Change: How a Picture of Students' Intuitive Conceptions Accrue from Dynamically Robust Task Dependent Learning Outcomes

    Science.gov (United States)

    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…

  7. Robust intelligent sliding model control using recurrent cerebellar model articulation controller for uncertain nonlinear chaotic systems

    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

  8. 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.

  9. Extending dynamic segmentation with lead generation : A latent class Markov analysis of financial product portfolios

    NARCIS (Netherlands)

    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

  10. Passivity analysis of higher order evolutionary dynamics and population games

    KAUST Repository

    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.

  11. Robust fault detection of wind energy conversion systems based on dynamic neural networks.

    Science.gov (United States)

    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.

  12. Dynamic Output Feedback Robust MPC with Input Saturation Based on Zonotopic Set-Membership Estimation

    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.

  13. RSMDP-based Robust Q-learning for Optimal Path Planning in a Dynamic Environment

    Directory of Open Access Journals (Sweden)

    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.

  14. Effect of smoothing on robust chaos.

    Science.gov (United States)

    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.

  15. Robustness in econometrics

    CERN Document Server

    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.

  16. A rapid and robust gradient measurement technique using dynamic single-point imaging.

    Science.gov (United States)

    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.

  17. A Universal Concept for Robust Solving of Shortest Path Problems in Dynamically Reconfigurable Graphs

    Directory of Open Access Journals (Sweden)

    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.

  18. 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.

  19. 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

  20. 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.

  1. 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.

  2. 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...

  3. Robust Sensor Faults Reconstruction for a Class of Uncertain Linear Systems Using a Sliding Mode Observer: An LMI Approach

    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.

  4. Fast and robust wavelet-based dynamic range compression and contrast enhancement model with color restoration

    Science.gov (United States)

    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.

  5. Small Body GN&C Research Report: A Robust Model Predictive Control Algorithm with Guaranteed Resolvability

    Science.gov (United States)

    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.

  6. Muscle Synergy-Driven Robust Motion Control.

    Science.gov (United States)

    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

  7. Multi-Class Motor Imagery EEG Decoding for Brain-Computer Interfaces

    Science.gov (United States)

    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

  8. 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.

  9. Robust intelligent backstepping tracking control for uncertain non-linear chaotic systems using H∞ control technique

    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.

  10. Sufficient conditions for BIBO robust stabilization : given by the gap metric

    NARCIS (Netherlands)

    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

  11. Robust and Adaptive Control With Aerospace Applications

    CERN Document Server

    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 ...

  12. Robust LS-SVM-based adaptive constrained control for a class of uncertain nonlinear systems with time-varying predefined performance

    Science.gov (United States)

    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.

  13. Criteria for robustness of heteroclinic cycles in neural microcircuits

    Science.gov (United States)

    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

  14. Motion robust high resolution 3D free-breathing pulmonary MRI using dynamic 3D image self-navigator.

    Science.gov (United States)

    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.

  15. Identification of the dynamic operating envelope of HCCI engines using class imbalance learning.

    Science.gov (United States)

    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

  16. 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.

  17. Dynamic excitatory and inhibitory gain modulation can produce flexible, robust and optimal decision-making.

    Directory of Open Access Journals (Sweden)

    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

  18. Decomposition and Projection Methods for Distributed Robustness Analysis of Interconnected Uncertain Systems

    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...

  19. Robust state estimation for uncertain fuzzy bidirectional associative memory networks with time-varying delays

    Science.gov (United States)

    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.

  20. Robust state estimation for uncertain fuzzy bidirectional associative memory networks with time-varying delays

    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)

  1. PCBDDC: A Class of Robust Dual-Primal Methods in PETSc

    KAUST Repository

    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.

  2. PCBDDC: A Class of Robust Dual-Primal Methods in PETSc

    KAUST Repository

    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.

  3. On the robustness of two-stage estimators

    KAUST Repository

    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

  4. Measure of robustness for complex networks

    Science.gov (United States)

    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

  5. Virtual partitioning for robust resource sharing: computational techniques for heterogeneous traffic

    NARCIS (Netherlands)

    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

  6. Identifying Effective Enzyme Activity Targets for Recombinant Class I and Class II Collagenase for Successful Human Islet Isolation

    OpenAIRE

    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.

  7. Dynamic inventory rationing strategies for inventory systems with two demand classes, Poisson demand and backordering

    NARCIS (Netherlands)

    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

  8. 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.

  9. Slow dynamics in translation-invariant quantum lattice models

    Science.gov (United States)

    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.

  10. Robust Adaptive Dynamic Programming of Two-Player Zero-Sum Games for Continuous-Time Linear Systems.

    Science.gov (United States)

    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.

  11. Some fundamental considerations on the dynamics of class B laser threshold crossing

    OpenAIRE

    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...

  12. A Virtual Class Calculus

    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...

  13. Exploring the Impact of Network Structure and Demand Collaboration on the Dynamics of a Supply Chain Network Using a Robust Control Approach

    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.

  14. The role of robust optimization in single-leg airline revenue management

    NARCIS (Netherlands)

    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

  15. Robust estimation for ordinary differential equation models.

    Science.gov (United States)

    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.

  16. 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

  17. 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 ...

  18. Robust doubly charged nodal lines and nodal surfaces in centrosymmetric systems

    Science.gov (United States)

    Bzdušek, Tomáš; Sigrist, Manfred

    2017-10-01

    Weyl points in three spatial dimensions are characterized by a Z -valued charge—the Chern number—which makes them stable against a wide range of perturbations. A set of Weyl points can mutually annihilate only if their net charge vanishes, a property we refer to as robustness. While nodal loops are usually not robust in this sense, it has recently been shown using homotopy arguments that in the centrosymmetric extension of the AI symmetry class they nevertheless develop a Z2 charge analogous to the Chern number. Nodal loops carrying a nontrivial value of this Z2 charge are robust, i.e., they can be gapped out only by a pairwise annihilation and not on their own. As this is an additional charge independent of the Berry π -phase flowing along the band degeneracy, such nodal loops are, in fact, doubly charged. In this manuscript, we generalize the homotopy discussion to the centrosymmetric extensions of all Atland-Zirnbauer classes. We develop a tailored mathematical framework dubbed the AZ +I classification and show that in three spatial dimensions such robust and multiply charged nodes appear in four of such centrosymmetric extensions, namely, AZ +I classes CI and AI lead to doubly charged nodal lines, while D and BDI support doubly charged nodal surfaces. We remark that no further crystalline symmetries apart from the spatial inversion are necessary for their stability. We provide a description of the corresponding topological charges, and develop simple tight-binding models of various semimetallic and superconducting phases that exhibit these nodes. We also indicate how the concept of robust and multiply charged nodes generalizes to other spatial dimensions.

  19. The dynamics of student learning within a high school virtual reality design class

    Science.gov (United States)

    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.

  20. Effect of interaction strength on robustness of controlling edge dynamics in complex networks

    Science.gov (United States)

    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.

  1. A Robust and Self-Paced BCI System Based on a Four Class SSVEP Paradigm: Algorithms and Protocols for a High-Transfer-Rate Direct Brain Communication

    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.

  2. Robust Distributed Model Predictive Load Frequency Control of Interconnected Power System

    Directory of Open Access Journals (Sweden)

    Xiangjie Liu

    2013-01-01

    Full Text Available Considering the load frequency control (LFC of large-scale power system, a robust distributed model predictive control (RDMPC is presented. The system uncertainty according to power system parameter variation alone with the generation rate constraints (GRC is included in the synthesis procedure. The entire power system is composed of several control areas, and the problem is formulated as convex optimization problem with linear matrix inequalities (LMI that can be solved efficiently. It minimizes an upper bound on a robust performance objective for each subsystem. Simulation results show good dynamic response and robustness in the presence of power system dynamic uncertainties.

  3. 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.

  4. Emergence of robustness in networks of networks

    Science.gov (United States)

    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.

  5. Robust Nonlinear Regulation of Limit Cycle Oscillations in UAVs Using Synthetic Jet Actuators

    Directory of Open Access Journals (Sweden)

    Natalie Ramos Pedroza

    2014-09-01

    Full Text Available In this paper, a synthetic jet actuators (SJA-based nonlinear robust controller is developed, which is capable of completely suppressing limit cycle oscillations (LCO in UAV systems with parametric uncertainty in the SJA dynamics and unmodeled external disturbances. Specifically, the control law compensates for uncertainty in an input gain matrix, which results from the unknown airflow dynamics generated by the SJA. Challenges in the control design include compensation for input-multiplicative parametric uncertainty in the actuator dynamic model. The result was achieved via innovative algebraic manipulation in the error system development, along with a Lyapunov-based robust control law. A rigorous Lyapunov-based stability analysis is utilized to prove asymptotic LCO suppression, considering a detailed dynamic model of the pitching and plunging dynamics. Numerical simulation results are provided to demonstrate the robustness and practical performance of the proposed control law.

  6. Integrated direct/indirect adaptive robust motion trajectory tracking control of pneumatic cylinders

    Science.gov (United States)

    Meng, Deyuan; Tao, Guoliang; Zhu, Xiaocong

    2013-09-01

    This paper studies the precision motion trajectory tracking control of a pneumatic cylinder driven by a proportional-directional control valve. An integrated direct/indirect adaptive robust controller is proposed. The controller employs a physical model based indirect-type parameter estimation to obtain reliable estimates of unknown model parameters, and utilises a robust control method with dynamic compensation type fast adaptation to attenuate the effects of parameter estimation errors, unmodelled dynamics and disturbances. Due to the use of projection mapping, the robust control law and the parameter adaption algorithm can be designed separately. Since the system model uncertainties are unmatched, the recursive backstepping technology is adopted to design the robust control law. Extensive comparative experimental results are presented to illustrate the effectiveness of the proposed controller and its performance robustness to parameter variations and sudden disturbances.

  7. Exploiting short-term memory in soft body dynamics as a computational resource.

    Science.gov (United States)

    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.

  8. 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.

  9. Towards investigation of evolution of dynamical systems with independence of time accuracy: more classes of systems

    Science.gov (United States)

    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.

  10. Robustness of Visual Place Cells in Dynamic Indoor and Outdoor Environment

    Directory of Open Access Journals (Sweden)

    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.

  11. 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.

  12. 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.

  13. 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...

  14. Robust D-optimal designs under correlated error, applicable invariantly for some lifetime distributions

    International Nuclear Information System (INIS)

    Das, Rabindra Nath; Kim, Jinseog; Park, Jeong-Soo

    2015-01-01

    In quality engineering, the most commonly used lifetime distributions are log-normal, exponential, gamma and Weibull. Experimental designs are useful for predicting the optimal operating conditions of the process in lifetime improvement experiments. In the present article, invariant robust first-order D-optimal designs are derived for correlated lifetime responses having the above four distributions. Robust designs are developed for some correlated error structures. It is shown that robust first-order D-optimal designs for these lifetime distributions are always robust rotatable but the converse is not true. Moreover, it is observed that these designs depend on the respective error covariance structure but are invariant to the above four lifetime distributions. This article generalizes the results of Das and Lin [7] for the above four lifetime distributions with general (intra-class, inter-class, compound symmetry, and tri-diagonal) correlated error structures. - Highlights: • This paper presents invariant robust first-order D-optimal designs under correlated lifetime responses. • The results of Das and Lin [7] are extended for the four lifetime (log-normal, exponential, gamma and Weibull) distributions. • This paper also generalizes the results of Das and Lin [7] to more general correlated error structures

  15. 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.

  16. 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)

  17. Robust, nonlinear, high angle-of-attack control design for a supermaneuverable vehicle

    Science.gov (United States)

    Adams, Richard J.

    1993-01-01

    High angle-of-attack flight control laws are developed for a supermaneuverable fighter aircraft. The methods of dynamic inversion and structured singular value synthesis are combined into an approach which addresses both the nonlinearity and robustness problems of flight at extreme operating conditions. The primary purpose of the dynamic inversion control elements is to linearize the vehicle response across the flight envelope. Structured singular value synthesis is used to design a dynamic controller which provides robust tracking to pilot commands. The resulting control system achieves desired flying qualities and guarantees a large margin of robustness to uncertainties for high angle-of-attack flight conditions. The results of linear simulation and structured singular value stability analysis are presented to demonstrate satisfaction of the design criteria. High fidelity nonlinear simulation results show that the combined dynamics inversion/structured singular value synthesis control law achieves a high level of performance in a realistic environment.

  18. Robust Takagi-Sugeno Fuzzy Dynamic Regulator for Trajectory Tracking of a Pendulum-Cart System

    Directory of Open Access Journals (Sweden)

    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.

  19. 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.

  20. Robust Moving Horizon H∞ Control of Discrete Time-Delayed Systems with Interval Time-Varying Delays

    Directory of Open Access Journals (Sweden)

    F. Yıldız Tascikaraoglu

    2014-01-01

    Full Text Available In this study, design of a delay-dependent type moving horizon state-feedback control (MHHC is considered for a class of linear discrete-time system subject to time-varying state delays, norm-bounded uncertainties, and disturbances with bounded energies. The closed-loop robust stability and robust performance problems are considered to overcome the instability and poor disturbance rejection performance due to the existence of parametric uncertainties and time-delay appeared in the system dynamics. Utilizing a discrete-time Lyapunov-Krasovskii functional, some delay-dependent linear matrix inequality (LMI based conditions are provided. It is shown that if one can find a feasible solution set for these LMI conditions iteratively at each step of run-time, then we can construct a control law which guarantees the closed-loop asymptotic stability, maximum disturbance rejection performance, and closed-loop dissipativity in view of the actuator limitations. Two numerical examples with simulations on a nominal and uncertain discrete-time, time-delayed systems, are presented at the end, in order to demonstrate the efficiency of the proposed method.

  1. 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.

  2. Evolution of tripartite entangled states in a decohering environment and their experimental protection using dynamical decoupling

    Science.gov (United States)

    Singh, Harpreet; Arvind, Dorai, Kavita

    2018-02-01

    We embarked upon the task of experimental protection of different classes of tripartite entangled states, namely, the maximally entangled Greenberger-Horne-Zeilinger (GHZ) and W states and the tripartite entangled state called the W W ¯ state, using dynamical decoupling. The states were created on a three-qubit NMR quantum information processor and allowed to evolve in the naturally noisy NMR environment. Tripartite entanglement was monitored at each time instant during state evolution, using negativity as an entanglement measure. It was found that the W state is most robust while the GHZ-type states are most fragile against the natural decoherence present in the NMR system. The W W ¯ state, which is in the GHZ class yet stores entanglement in a manner akin to the W state, surprisingly turned out to be more robust than the GHZ state. The experimental data were best modeled by considering the main noise channel to be an uncorrelated phase damping channel acting independently on each qubit, along with a generalized amplitude damping channel. Using dynamical decoupling, we were able to achieve a significant protection of entanglement for GHZ states. There was a marginal improvement in the state fidelity for the W state (which is already robust against natural system decoherence), while the W W ¯ state showed a significant improvement in fidelity and protection against decoherence.

  3. Social affiliation in same-class and cross-class interactions.

    Science.gov (United States)

    Côté, Stéphane; Kraus, Michael W; Carpenter, Nichelle C; Piff, Paul K; Beermann, Ursula; Keltner, Dacher

    2017-02-01

    Historically high levels of economic inequality likely have important consequences for relationships between people of the same and different social class backgrounds. Here, we test the prediction that social affiliation among same-class partners is stronger at the extremes of the class spectrum, given that these groups are highly distinctive and most separated from others by institutional and economic forces. An internal meta-analysis of 4 studies (N = 723) provided support for this hypothesis. Participant and partner social class were interactively, rather than additively, associated with social affiliation, indexed by affiliative behaviors and emotions during structured laboratory interactions and in daily life. Further, response surface analyses revealed that paired upper or lower class partners generally affiliated more than average-class pairs. Analyses with separate class indices suggested that these patterns are driven more by parental income and subjective social class than by parental education. The findings illuminate the dynamics of same- and cross-class interactions, revealing that not all same-class interactions feature the same degree of affiliation. They also reveal the importance of studying social class from an intergroup perspective. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  4. Testing the robustness of deterministic models of optimal dynamic pricing and lot-sizing for deteriorating items under stochastic conditions

    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....

  5. Advanced neural network-based computational schemes for robust fault diagnosis

    CERN Document Server

    Mrugalski, Marcin

    2014-01-01

    The present book is devoted to problems of adaptation of artificial neural networks to robust fault diagnosis schemes. It presents neural networks-based modelling and estimation techniques used for designing robust fault diagnosis schemes for non-linear dynamic systems. A part of the book focuses on fundamental issues such as architectures of dynamic neural networks, methods for designing of neural networks and fault diagnosis schemes as well as the importance of robustness. The book is of a tutorial value and can be perceived as a good starting point for the new-comers to this field. The book is also devoted to advanced schemes of description of neural model uncertainty. In particular, the methods of computation of neural networks uncertainty with robust parameter estimation are presented. Moreover, a novel approach for system identification with the state-space GMDH neural network is delivered. All the concepts described in this book are illustrated by both simple academic illustrative examples and practica...

  6. Robust model predictive control for constrained continuous-time nonlinear systems

    Science.gov (United States)

    Sun, Tairen; Pan, Yongping; Zhang, Jun; Yu, Haoyong

    2018-02-01

    In this paper, a robust model predictive control (MPC) is designed for a class of constrained continuous-time nonlinear systems with bounded additive disturbances. The robust MPC consists of a nonlinear feedback control and a continuous-time model-based dual-mode MPC. The nonlinear feedback control guarantees the actual trajectory being contained in a tube centred at the nominal trajectory. The dual-mode MPC is designed to ensure asymptotic convergence of the nominal trajectory to zero. This paper extends current results on discrete-time model-based tube MPC and linear system model-based tube MPC to continuous-time nonlinear model-based tube MPC. The feasibility and robustness of the proposed robust MPC have been demonstrated by theoretical analysis and applications to a cart-damper springer system and a one-link robot manipulator.

  7. Robust control of drag and lateral dynamic response for road vehicles exposed to cross-wind gusts

    Science.gov (United States)

    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.

  8. 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....

  9. Temperature-dependent dynamical transitions of different classes of amino acid residue in a globular protein.

    Science.gov (United States)

    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.

  10. Robust digital processing of speech signals

    CERN Document Server

    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.

  11. 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...

  12. Dynamic Output Feedback Robust Model Predictive Control via Zonotopic Set-Membership Estimation for Constrained Quasi-LPV Systems

    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.

  13. Adaptive Neural Output-Feedback Control for a Class of Nonlower Triangular Nonlinear Systems With Unmodeled Dynamics.

    Science.gov (United States)

    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.

  14. 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.

  15. 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.

  16. 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.

  17. Robust-mode analysis of hydrodynamic flows

    Science.gov (United States)

    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.

  18. 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...

  19. Optimal interdependence enhances robustness of complex systems

    OpenAIRE

    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...

  20. 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.

  1. Discovery and dynamical characterization of the Amor-class asteroid 2012 XH16

    Science.gov (United States)

    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.

  2. Robust model predictive control of nonlinear systems with unmodeled dynamics and bounded uncertainties based on neural networks.

    Science.gov (United States)

    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.

  3. Robust control of an industrial boiler system; a comparison between two approaches: Sliding mode control and H∞ technique

    International Nuclear Information System (INIS)

    Moradi, Hamed; Bakhtiari-Nejad, Firooz; Saffar-Avval, Majid

    2009-01-01

    To achieve a good performance of the utility boiler, dynamic variables such as drum pressure, steam temperature and water level of drum must be controlled. In this paper, a linear time invariant (LTI) model of a boiler system is considered in which the input variables are feed-water and fuel mass rates. However this dynamic model may associate with uncertainties. With considering the uncertainties of the dynamic model, a sliding mode controller is designed. After representation of the uncertain dynamic system in general control configuration and modelling the parametric uncertainties, nominal performance, robust stability and robust performance are analyzed by the concept of structured singular value μ. Using an algorithm for μ-analysis and applying an inversed-base controller, robust stability and nominal performance are guaranteed but robust performance is not satisfied. Finally, an optimal robust controller is designed based on μ-synthesis with DK-iteration algorithm. Both optimal robust and sliding mode controllers guarantee robust performance of the system against the uncertainties and result in desired time responses of the output variables. By applying H ∞ robust control, system tracks the desire reference inputs in a less time and with smoother time responses. However, less control efforts, feedwater and fuel mass rates, are needed when the sliding mode controller is applied.

  4. On the Context-Aware, Dynamic Spectrum Access for Robust Intraplatoon Communications

    Directory of Open Access Journals (Sweden)

    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.

  5. Robust Model Predictive Control of Networked Control Systems under Input Constraints and Packet Dropouts

    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.

  6. Robust two degree of freedom vehicle steering control satisfying mixed sensitivity constraint

    OpenAIRE

    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...

  7. Nonequilibrium dynamic critical scaling of the quantum Ising chain.

    Science.gov (United States)

    Kolodrubetz, Michael; Clark, Bryan K; Huse, David A

    2012-07-06

    We solve for the time-dependent finite-size scaling functions of the one-dimensional transverse-field Ising chain during a linear-in-time ramp of the field through the quantum critical point. We then simulate Mott-insulating bosons in a tilted potential, an experimentally studied system in the same equilibrium universality class, and demonstrate that universality holds for the dynamics as well. We find qualitatively athermal features of the scaling functions, such as negative spin correlations, and we show that they should be robustly observable within present cold atom experiments.

  8. Pan-Antarctic analysis aggregating spatial estimates of Adélie penguin abundance reveals robust dynamics despite stochastic noise.

    Science.gov (United States)

    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.

  9. 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.

  10. Robust reconfigurable control for parametric and additive faults with FDI uncertainties

    DEFF Research Database (Denmark)

    Stoustrup, Jakob; Yang, Zhenyu

    2000-01-01

    From the system recoverable point of view, this paper discusses robust reconfigurable control synthesis for LTI systems and a class of nonlinear control systems with parametric and additive faults as well as derivations generated by FDI algorithms. By following the model-matching strategy......, an augmented optimal control problem is constructed based on the considered faulty and fictitious nominal systems, such that the robust control design techniques, such as H-infinity control and mu synthesis, can be employed for the reconfigurable control design....

  11. Phase transition universality classes of classical, nonequilibrium systems

    CERN Document Server

    Ódor, G

    2004-01-01

    In the first chapter I summarize the most important critical exponents and relations used in this work. In the second chapter I briefly address the question of scaling behavior at first order phase transitions.In chapter three I review dynamical extensions of basic static classes, show the effect of mixing dynamics and percolation behavior. The main body of this work is given in chapter four where genuine, dynamical universality classes specific to nonequilibrium systems are introduced. In chapter five I continue overviewing such nonequilibrium classes but in coupled, multi-component systems. Most of known transitions in low dimensional systems are between active and absorbing states of reaction-diffusion type systems, but I briefly introduce related classes that appear in interface growth models in chapter six. Some of them are related to critical behavior of coupled, multi-component systems. Finally in chapter seven I summarize families of absorbing state system classes, mean-field classes and the most freq...

  12. The robustness of two tomography reconstructing techniques with heavily noisy dynamical experimental data from a high speed gamma-ray tomograph

    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)

  13. Binding stability of peptides on major histocompatibility complex class I proteins: role of entropy and dynamics

    Science.gov (United States)

    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.

  14. Robust variable selection method for nonparametric differential equation models with application to nonlinear dynamic gene regulatory network analysis.

    Science.gov (United States)

    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.

  15. Sufficient conditions for robust BIBO stabilization : given by the gap metric

    NARCIS (Netherlands)

    Zhu, S.Q.; Hautus, M.L.J.; Praagman, C.

    1988-01-01

    A relation between coprime fractions and the gap metric is presented. Using this result we provide some sufficient conditions for robust BIBO stabilization for a wide class of systems. These conditions allow the plant and the compensator to be disturbed simultaneously.

  16. Research on robust optimization of emergency logistics network considering the time dependence characteristic

    Science.gov (United States)

    WANG, Qingrong; ZHU, Changfeng; LI, Ying; ZHANG, Zhengkun

    2017-06-01

    Considering the time dependence of emergency logistic network and complexity of the environment that the network exists in, in this paper the time dependent network optimization theory and robust discrete optimization theory are combined, and the emergency logistics dynamic network optimization model with characteristics of robustness is built to maximize the timeliness of emergency logistics. On this basis, considering the complexity of dynamic network and the time dependence of edge weight, an improved ant colony algorithm is proposed to realize the coupling of the optimization algorithm and the network time dependence and robustness. Finally, a case study has been carried out in order to testify validity of this robustness optimization model and its algorithm, and the value of different regulation factors was analyzed considering the importance of the value of the control factor in solving the optimal path. Analysis results show that this model and its algorithm above-mentioned have good timeliness and strong robustness.

  17. Robust-BD Estimation and Inference for General Partially Linear Models

    Directory of Open Access Journals (Sweden)

    Chunming Zhang

    2017-11-01

    Full Text Available The classical quadratic loss for the partially linear model (PLM and the likelihood function for the generalized PLM are not resistant to outliers. This inspires us to propose a class of “robust-Bregman divergence (BD” estimators of both the parametric and nonparametric components in the general partially linear model (GPLM, which allows the distribution of the response variable to be partially specified, without being fully known. Using the local-polynomial function estimation method, we propose a computationally-efficient procedure for obtaining “robust-BD” estimators and establish the consistency and asymptotic normality of the “robust-BD” estimator of the parametric component β o . For inference procedures of β o in the GPLM, we show that the Wald-type test statistic W n constructed from the “robust-BD” estimators is asymptotically distribution free under the null, whereas the likelihood ratio-type test statistic Λ n is not. This provides an insight into the distinction from the asymptotic equivalence (Fan and Huang 2005 between W n and Λ n in the PLM constructed from profile least-squares estimators using the non-robust quadratic loss. Numerical examples illustrate the computational effectiveness of the proposed “robust-BD” estimators and robust Wald-type test in the appearance of outlying observations.

  18. Modeling and Optimal Control of a Class of Warfare Hybrid Dynamic Systems Based on Lanchester (n,1) Attrition Model

    OpenAIRE

    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...

  19. Adaptive Critic Nonlinear Robust Control: A Survey.

    Science.gov (United States)

    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.

  20. 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...

  1. A robust nonlinear filter for image restoration.

    Science.gov (United States)

    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.

  2. 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...

  3. Robust Framework to Combine Diverse Classifiers Assigning Distributed Confidence to Individual Classifiers at Class Level

    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.

  4. Hawkes process as a model of social interactions: a view on video dynamics

    International Nuclear Information System (INIS)

    Mitchell, Lawrence; Cates, Michael E

    2010-01-01

    We study by computer simulation the 'Hawkes process' that was proposed in a recent paper by Crane and Sornette (2008 Proc. Natl Acad. Sci. USA 105 15649) as a plausible model for the dynamics of YouTube video viewing numbers. We test the claims made there that robust identification is possible for classes of dynamic response following activity bursts. Our simulated time series for the Hawkes process indeed fall into the different categories predicted by Crane and Sornette. However, the Hawkes process gives a much narrower spread of decay exponents than the YouTube data, suggesting limits to the universality of the Hawkes-based analysis.

  5. Hawkes process as a model of social interactions: a view on video dynamics

    Energy Technology Data Exchange (ETDEWEB)

    Mitchell, Lawrence; Cates, Michael E, E-mail: lawrence.mitchell@ed.ac.u [SUPA, School of Physics and Astronomy, University of Edinburgh, JCMB Kings Buildings, Mayfield Road, Edinburgh EH9 3JZ (United Kingdom)

    2010-01-29

    We study by computer simulation the 'Hawkes process' that was proposed in a recent paper by Crane and Sornette (2008 Proc. Natl Acad. Sci. USA 105 15649) as a plausible model for the dynamics of YouTube video viewing numbers. We test the claims made there that robust identification is possible for classes of dynamic response following activity bursts. Our simulated time series for the Hawkes process indeed fall into the different categories predicted by Crane and Sornette. However, the Hawkes process gives a much narrower spread of decay exponents than the YouTube data, suggesting limits to the universality of the Hawkes-based analysis.

  6. Hawkes process as a model of social interactions: a view on video dynamics

    Energy Technology Data Exchange (ETDEWEB)

    Mitchell, Lawrence; Cates, Michael E, E-mail: lawrence.mitchell@ed.ac.u [SUPA, School of Physics and Astronomy, University of Edinburgh, JCMB Kings Buildings, Mayfield Road, Edinburgh EH9 3JZ (United Kingdom)

    2010-01-29

    We study by computer simulation the 'Hawkes process' that was proposed in a recent paper by Crane and Sornette (2008 Proc. Natl Acad. Sci. USA 105 15649) as a plausible model for the dynamics of YouTube video viewing numbers. We test the claims made there that robust identification is possible for classes of dynamic response following activity bursts. Our simulated time series for the Hawkes process indeed fall into the different categories predicted by Crane and Sornette. However, the Hawkes process gives a much narrower spread of decay exponents than the YouTube data, suggesting limits to the universality of the Hawkes-based analysis.

  7. On the robustness of two-stage estimators

    KAUST Repository

    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.

  8. Improved Delay-Dependent Robust Stability Criteria for a Class of Uncertain Neutral Type Lur’e Systems with Discrete and Distributed Delays

    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.

  9. Robust and Effective Component-based Banknote Recognition by SURF Features.

    Science.gov (United States)

    Hasanuzzaman, Faiz M; Yang, Xiaodong; Tian, YingLi

    2011-01-01

    Camera-based computer vision technology is able to assist visually impaired people to automatically recognize banknotes. A good banknote recognition algorithm for blind or visually impaired people should have the following features: 1) 100% accuracy, and 2) robustness to various conditions in different environments and occlusions. Most existing algorithms of banknote recognition are limited to work for restricted conditions. In this paper we propose a component-based framework for banknote recognition by using Speeded Up Robust Features (SURF). The component-based framework is effective in collecting more class-specific information and robust in dealing with partial occlusion and viewpoint changes. Furthermore, the evaluation of SURF demonstrates its effectiveness in handling background noise, image rotation, scale, and illumination changes. To authenticate the robustness and generalizability of the proposed approach, we have collected a large dataset of banknotes from a variety of conditions including occlusion, cluttered background, rotation, and changes of illumination, scaling, and viewpoints. The proposed algorithm achieves 100% recognition rate on our challenging dataset.

  10. Robust filtering for uncertain systems a parameter-dependent approach

    CERN Document Server

    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; ·...

  11. 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...

  12. Robust stability of uncertain Markovian jumping Cohen-Grossberg neural networks with mixed time-varying delays

    International Nuclear Information System (INIS)

    Sheng Li; Yang Huizhong

    2009-01-01

    This paper considers the robust stability of a class of uncertain Markovian jumping Cohen-Grossberg neural networks (UMJCGNNs) with mixed time-varying delays. The parameter uncertainties are norm-bounded and the mixed time-varying delays comprise discrete and distributed time delays. Based on the Lyapunov stability theory and linear matrix inequality (LMI) technique, some robust stability conditions guaranteeing the global robust convergence of the equilibrium point are derived. An example is given to show the effectiveness of the proposed results.

  13. Universality Classes of Interaction Structures for NK Fitness Landscapes

    Science.gov (United States)

    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.

  14. Uncertainty quantification-based robust aerodynamic optimization of laminar flow nacelle

    Science.gov (United States)

    Xiong, Neng; Tao, Yang; Liu, Zhiyong; Lin, Jun

    2018-05-01

    The aerodynamic performance of laminar flow nacelle is highly sensitive to uncertain working conditions, especially the surface roughness. An efficient robust aerodynamic optimization method on the basis of non-deterministic computational fluid dynamic (CFD) simulation and Efficient Global Optimization (EGO)algorithm was employed. A non-intrusive polynomial chaos method is used in conjunction with an existing well-verified CFD module to quantify the uncertainty propagation in the flow field. This paper investigates the roughness modeling behavior with the γ-Ret shear stress transport model including modeling flow transition and surface roughness effects. The roughness effects are modeled to simulate sand grain roughness. A Class-Shape Transformation-based parametrical description of the nacelle contour as part of an automatic design evaluation process is presented. A Design-of-Experiments (DoE) was performed and surrogate model by Kriging method was built. The new design nacelle process demonstrates that significant improvements of both mean and variance of the efficiency are achieved and the proposed method can be applied to laminar flow nacelle design successfully.

  15. A robust bi-orthogonal/dynamically-orthogonal method using the covariance pseudo-inverse with application to stochastic flow problems

    Science.gov (United States)

    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

  16. A Novel Method of Robust Trajectory Linearization Control Based on Disturbance Rejection

    Directory of Open Access Journals (Sweden)

    Xingling Shao

    2014-01-01

    Full Text Available A novel method of robust trajectory linearization control for a class of nonlinear systems with uncertainties based on disturbance rejection is proposed. Firstly, on the basis of trajectory linearization control (TLC method, a feedback linearization based control law is designed to transform the original tracking error dynamics to the canonical integral-chain form. To address the issue of reducing the influence made by uncertainties, with tracking error as input, linear extended state observer (LESO is constructed to estimate the tracking error vector, as well as the uncertainties in an integrated manner. Meanwhile, the boundedness of the estimated error is investigated by theoretical analysis. In addition, decoupled controller (which has the characteristic of well-tuning and simple form based on LESO is synthesized to realize the output tracking for closed-loop system. The closed-loop stability of the system under the proposed LESO-based control structure is established. Also, simulation results are presented to illustrate the effectiveness of the control strategy.

  17. A robust model predictive control strategy for improving the control performance of air-conditioning systems

    International Nuclear Information System (INIS)

    Huang Gongsheng; Wang Shengwei; Xu Xinhua

    2009-01-01

    This paper presents a robust model predictive control strategy for improving the supply air temperature control of air-handling units by dealing with the associated uncertainties and constraints directly. This strategy uses a first-order plus time-delay model with uncertain time-delay and system gain to describe air-conditioning process of an air-handling unit usually operating at various weather conditions. The uncertainties of the time-delay and system gain, which imply the nonlinearities and the variable dynamic characteristics, are formulated using an uncertainty polytope. Based on this uncertainty formulation, an offline LMI-based robust model predictive control algorithm is employed to design a robust controller for air-handling units which can guarantee a good robustness subject to uncertainties and constraints. The proposed robust strategy is evaluated in a dynamic simulation environment of a variable air volume air-conditioning system in various operation conditions by comparing with a conventional PI control strategy. The robustness analysis of both strategies under different weather conditions is also presented.

  18. Trading Robustness Requirements in Mars Entry Trajectory Design

    Science.gov (United States)

    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.

  19. 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)

  20. Dynamic modelling and adaptive robust tracking control of a space robot with two-link flexible manipulators under unknown disturbances

    Science.gov (United States)

    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.

  1. Nonlinear dynamics of charged particles in the magnetotail

    Science.gov (United States)

    Chen, James

    1992-01-01

    An important region of the earth's magnetosphere is the nightside magnetotail, which is believed to play a significant role in energy storage and release associated with substorms. The magnetotail contains a current sheet which separates regions of oppositely directed magnetic field. Particle motion in the collisionless magnetotail has been a long-standing problem. Recent research from the dynamical point of view has yielded considerable new insights into the fundamental properties of orbits and of particle distribution functions. A new framework of understanding magnetospheric plasma properties is emerging. Some novel predictions based directly on nonlinear dynamics have proved to be robust and in apparent good agreement with observation. The earth's magnetotail may serve as a paradigm, one accessible by in situ observation, of a broad class of boundary regions with embedded current sheets. This article reviews the nonlinear dynamics of charged particles in the magnetotail configuration. The emphasis is on the relationships between the dynamics and physical observables. At the end of the introduction, sections containing basic material are indicated.

  2. Naïve and Robust: Class-Conditional Independence in Human Classification Learning

    Science.gov (United States)

    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…

  3. Bilinear Approximate Model-Based Robust Lyapunov Control for Parabolic Distributed Collectors

    KAUST Repository

    Elmetennani, Shahrazed

    2016-11-09

    This brief addresses the control problem of distributed parabolic solar collectors in order to maintain the field outlet temperature around a desired level. The objective is to design an efficient controller to force the outlet fluid temperature to track a set reference despite the unpredictable varying working conditions. In this brief, a bilinear model-based robust Lyapunov control is proposed to achieve the control objectives with robustness to the environmental changes. The bilinear model is a reduced order approximate representation of the solar collector, which is derived from the hyperbolic distributed equation describing the heat transport dynamics by means of a dynamical Gaussian interpolation. Using the bilinear approximate model, a robust control strategy is designed applying Lyapunov stability theory combined with a phenomenological representation of the system in order to stabilize the tracking error. On the basis of the error analysis, simulation results show good performance of the proposed controller, in terms of tracking accuracy and convergence time, with limited measurement even under unfavorable working conditions. Furthermore, the presented work is of interest for a large category of dynamical systems knowing that the solar collector is representative of physical systems involving transport phenomena constrained by unknown external disturbances.

  4. 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)

  5. Global robust stability of neural networks with multiple discrete delays and distributed delays

    International Nuclear Information System (INIS)

    Gao Ming; Cui Baotong

    2009-01-01

    The problem of global robust stability is investigated for a class of uncertain neural networks with both multiple discrete time-varying delays and distributed time-varying delays. The uncertainties are assumed to be of norm-bounded form and the activation functions are supposed to be bounded and globally Lipschitz continuous. Based on the Lyapunov stability theory and linear matrix inequality technique, some robust stability conditions guaranteeing the global robust convergence of the equilibrium point are derived. The proposed LMI-based criteria are computationally efficient as they can be easily checked by using recently developed algorithms in solving LMIs. Two examples are given to show the effectiveness of the proposed results.

  6. Stochastic Wilson–Cowan models of neuronal network dynamics with memory and delay

    International Nuclear Information System (INIS)

    Goychuk, Igor; Goychuk, Andriy

    2015-01-01

    We consider a simple Markovian class of the stochastic Wilson–Cowan type models of neuronal network dynamics, which incorporates stochastic delay caused by the existence of a refractory period of neurons. From the point of view of the dynamics of the individual elements, we are dealing with a network of non-Markovian stochastic two-state oscillators with memory, which are coupled globally in a mean-field fashion. This interrelation of a higher-dimensional Markovian and lower-dimensional non-Markovian dynamics is discussed in its relevance to the general problem of the network dynamics of complex elements possessing memory. The simplest model of this class is provided by a three-state Markovian neuron with one refractory state, which causes firing delay with an exponentially decaying memory within the two-state reduced model. This basic model is used to study critical avalanche dynamics (the noise sustained criticality) in a balanced feedforward network consisting of the excitatory and inhibitory neurons. Such avalanches emerge due to the network size dependent noise (mesoscopic noise). Numerical simulations reveal an intermediate power law in the distribution of avalanche sizes with the critical exponent around −1.16. We show that this power law is robust upon a variation of the refractory time over several orders of magnitude. However, the avalanche time distribution is biexponential. It does not reflect any genuine power law dependence. (paper)

  7. Nonlinear control for a class of hydraulic servo system.

    Science.gov (United States)

    Yu, Hong; Feng, Zheng-jin; Wang, Xu-yong

    2004-11-01

    The dynamics of hydraulic systems are highly nonlinear and the system may be subjected to non-smooth and discontinuous nonlinearities due to directional change of valve opening, friction, etc. Aside from the nonlinear nature of hydraulic dynamics, hydraulic servo systems also have large extent of model uncertainties. To address these challenging issues, a robust state-feedback controller is designed by employing backstepping design technique such that the system output tracks a given signal arbitrarily well, and all signals in the closed-loop system remain bounded. Moreover, a relevant disturbance attenuation inequality is satisfied by the closed-loop signals. Compared with previously proposed robust controllers, this paper's robust controller based on backstepping recursive design method is easier to design, and is more suitable for implementation.

  8. Predictive control and identification: Applications to steering dynamics

    DEFF Research Database (Denmark)

    Hansen, Anca Daniela

    1996-01-01

    and of the loss function, which defines the optimality of the control. Some guidelines on how to choose the design parameters, depending on the type of process to be controlled and on the required control performance, are presented. A predictive track keeping system for a Mariner Class Vessel is formulated based...... the under- standing of the connection between identification and control, analysed in Chapter 7. Chapter 7 focuses on how to make the on-line identification for predictive control more robust towards unmodelled dynamics. The theory is verified via simulation studies on a Mariner Class Vessel. The effects...... and the need of a prefilter in the estimation are analysed and illustrated. Based on the idea that the control criterion must be dual to the estimation criterion, an iterative optimal prefilter is designed. This seems to be an appealing way to tune the model towards the objective for which the model...

  9. 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...

  10. 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

  11. Robust fast controller design via nonlinear fractional differential equations.

    Science.gov (United States)

    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.

  12. Robust blood-glucose control using Mathematica.

    Science.gov (United States)

    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.

  13. Robust distributed model predictive control of linear systems with structured time-varying uncertainties

    Science.gov (United States)

    Zhang, Langwen; Xie, Wei; Wang, Jingcheng

    2017-11-01

    In this work, synthesis of robust distributed model predictive control (MPC) is presented for a class of linear systems subject to structured time-varying uncertainties. By decomposing a global system into smaller dimensional subsystems, a set of distributed MPC controllers, instead of a centralised controller, are designed. To ensure the robust stability of the closed-loop system with respect to model uncertainties, distributed state feedback laws are obtained by solving a min-max optimisation problem. The design of robust distributed MPC is then transformed into solving a minimisation optimisation problem with linear matrix inequality constraints. An iterative online algorithm with adjustable maximum iteration is proposed to coordinate the distributed controllers to achieve a global performance. The simulation results show the effectiveness of the proposed robust distributed MPC algorithm.

  14. Using a Virtual Class to Demonstrate Computer-Mediated Group Dynamics Concepts

    Science.gov (United States)

    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…

  15. 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

  16. Robustness analysis of bogie suspension components Pareto optimised values

    Science.gov (United States)

    Mousavi Bideleh, Seyed Milad

    2017-08-01

    Bogie suspension system of high speed trains can significantly affect vehicle performance. Multiobjective optimisation problems are often formulated and solved to find the Pareto optimised values of the suspension components and improve cost efficiency in railway operations from different perspectives. Uncertainties in the design parameters of suspension system can negatively influence the dynamics behaviour of railway vehicles. In this regard, robustness analysis of a bogie dynamics response with respect to uncertainties in the suspension design parameters is considered. A one-car railway vehicle model with 50 degrees of freedom and wear/comfort Pareto optimised values of bogie suspension components is chosen for the analysis. Longitudinal and lateral primary stiffnesses, longitudinal and vertical secondary stiffnesses, as well as yaw damping are considered as five design parameters. The effects of parameter uncertainties on wear, ride comfort, track shift force, stability, and risk of derailment are studied by varying the design parameters around their respective Pareto optimised values according to a lognormal distribution with different coefficient of variations (COVs). The robustness analysis is carried out based on the maximum entropy concept. The multiplicative dimensional reduction method is utilised to simplify the calculation of fractional moments and improve the computational efficiency. The results showed that the dynamics response of the vehicle with wear/comfort Pareto optimised values of bogie suspension is robust against uncertainties in the design parameters and the probability of failure is small for parameter uncertainties with COV up to 0.1.

  17. TS Fuzzy Model-Based Controller Design for a Class of Nonlinear Systems Including Nonsmooth Functions

    DEFF Research Database (Denmark)

    Vafamand, Navid; Asemani, Mohammad Hassan; Khayatiyan, Alireza

    2018-01-01

    This paper proposes a novel robust controller design for a class of nonlinear systems including hard nonlinearity functions. The proposed approach is based on Takagi-Sugeno (TS) fuzzy modeling, nonquadratic Lyapunov function, and nonparallel distributed compensation scheme. In this paper, a novel...... criterion, new robust controller design conditions in terms of linear matrix inequalities are derived. Three practical case studies, electric power steering system, a helicopter model and servo-mechanical system, are presented to demonstrate the importance of such class of nonlinear systems comprising...

  18. An integrated approach to single-leg airline revenue management: The role of robust optimization

    NARCIS (Netherlands)

    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.

  19. An Integrated Approach to Single-Leg Airline Revenue Management: The Role of Robust Optimization

    NARCIS (Netherlands)

    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.

  20. Static and dynamic characterization of robust superhydrophobic surfaces built from nano-flowers on silicon micro-post arrays

    KAUST Repository

    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.

  1. Machine learning-based kinetic modeling: a robust and reproducible solution for quantitative analysis of dynamic PET data.

    Science.gov (United States)

    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.

  2. Static and dynamic characterization of robust superhydrophobic surfaces built from nano-flowers on silicon micro-post arrays

    KAUST Repository

    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.

  3. Machine learning-based kinetic modeling: a robust and reproducible solution for quantitative analysis of dynamic PET data

    Science.gov (United States)

    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.

  4. 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....

  5. Robust adaptive controller design for a class of uncertain nonlinear systems using online T-S fuzzy-neural modeling approach.

    Science.gov (United States)

    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.

  6. Supervised linear dimensionality reduction with robust margins for object recognition

    Science.gov (United States)

    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.

  7. Model-reference robust tuning of PID controllers

    CERN Document Server

    Alfaro, Victor M

    2016-01-01

    This book presents a unified methodology for the design of PID controllers that encompasses the wide range of different dynamics to be found in industrial processes. This is extended to provide a coherent way of dealing with the tuning of PID controllers. The particular method at the core of the book is the so-called model-reference robust tuning (MoReRT), developed by the authors. MoReRT constitutes a novel and powerful way of thinking of a robust design and taking into account the usual design trade-offs encountered in any control design problem. The book starts by presenting the different two-degree-of-freedom PID control algorithm variations and their conversion relations as well as the indexes used for performance, robustness and fragility evaluation:the bases of the proposed model. Secondly, the MoReRT design methodology and normalized controlled process models and controllers used in the design are described in order to facilitate the formulation of the different design problems and subsequent derivati...

  8. Observation Quality Control with a Robust Ensemble Kalman Filter

    KAUST Repository

    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.

  9. Observation Quality Control with a Robust Ensemble Kalman Filter

    KAUST Repository

    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.

  10. 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.

  11. 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...

  12. Designing Robustness to Temperature in a Feedforward Loop Circuit

    OpenAIRE

    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...

  13. 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...

  14. Robustness of Supercavitating Vehicles Based on Multistability Analysis

    Directory of Open Access Journals (Sweden)

    Yipin Lv

    2017-01-01

    Full Text Available Supercavity can increase speed of underwater vehicles greatly. However, external interferences always lead to instability of vehicles. This paper focuses on robustness of supercavitating vehicles. Based on a 4-dimensional dynamic model, the existence of multistability is verified in supercavitating system through simulation, and the robustness of vehicles varying with parameters is analyzed by basins of attraction. Results of the research disclose that the supercavitating system has three stable states in some regions of parameters space, namely, stable, periodic, and chaotic states, while in other regions it has various multistability, such as coexistence of two types of stable equilibrium points, coexistence of a limit cycle with a chaotic attractor, and coexistence of 1-periodic cycle with 2-periodic cycle. Provided that cavitation number varies within a small range, with increase of the feedback control gain of fin deflection angle, size of basin of attraction becomes smaller and robustness of the system becomes weaker. In practical application, robustness of supercavitating vehicles can be improved by setting parameters of system or adjusting initial launching conditions.

  15. 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

  16. 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....

  17. 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.

  18. Robust sigma delta converters : and their application in low-power highly-digitized flexible receivers

    NARCIS (Netherlands)

    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

  19. Dynamics, integrability and topology for some classes of Kolmogorov Hamiltonian systems in R+4

    Science.gov (United States)

    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.

  20. On robust parameter estimation in brain-computer interfacing

    Science.gov (United States)

    Samek, Wojciech; Nakajima, Shinichi; Kawanabe, Motoaki; Müller, Klaus-Robert

    2017-12-01

    Objective. The reliable estimation of parameters such as mean or covariance matrix from noisy and high-dimensional observations is a prerequisite for successful application of signal processing and machine learning algorithms in brain-computer interfacing (BCI). This challenging task becomes significantly more difficult if the data set contains outliers, e.g. due to subject movements, eye blinks or loose electrodes, as they may heavily bias the estimation and the subsequent statistical analysis. Although various robust estimators have been developed to tackle the outlier problem, they ignore important structural information in the data and thus may not be optimal. Typical structural elements in BCI data are the trials consisting of a few hundred EEG samples and indicating the start and end of a task. Approach. This work discusses the parameter estimation problem in BCI and introduces a novel hierarchical view on robustness which naturally comprises different types of outlierness occurring in structured data. Furthermore, the class of minimum divergence estimators is reviewed and a robust mean and covariance estimator for structured data is derived and evaluated with simulations and on a benchmark data set. Main results. The results show that state-of-the-art BCI algorithms benefit from robustly estimated parameters. Significance. Since parameter estimation is an integral part of various machine learning algorithms, the presented techniques are applicable to many problems beyond BCI.

  1. Detecting dynamical boundaries from kinematic data in biomechanics

    Science.gov (United States)

    Ross, Shane D.; Tanaka, Martin L.; Senatore, Carmine

    2010-03-01

    Ridges in the state space distribution of finite-time Lyapunov exponents can be used to locate dynamical boundaries. We describe a method for obtaining dynamical boundaries using only trajectories reconstructed from time series, expanding on the current approach which requires a vector field in the phase space. We analyze problems in musculoskeletal biomechanics, considered as exemplars of a class of experimental systems that contain separatrix features. Particular focus is given to postural control and balance, considering both models and experimental data. Our success in determining the boundary between recovery and failure in human balance activities suggests this approach will provide new robust stability measures, as well as measures of fall risk, that currently are not available and may have benefits for the analysis and prevention of low back pain and falls leading to injury, both of which affect a significant portion of the population.

  2. 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...

  3. Optimal control of quantum systems: Origins of inherent robustness to control field fluctuations

    International Nuclear Information System (INIS)

    Rabitz, Herschel

    2002-01-01

    The impact of control field fluctuations on the optimal manipulation of quantum dynamics phenomena is investigated. The quantum system is driven by an optimal control field, with the physical focus on the evolving expectation value of an observable operator. A relationship is shown to exist between the system dynamics and the control field fluctuations, wherein the process of seeking optimal performance assures an inherent degree of system robustness to such fluctuations. The presence of significant field fluctuations breaks down the evolution of the observable expectation value into a sequence of partially coherent robust steps. Robustness occurs because the optimization process reduces sensitivity to noise-driven quantum system fluctuations by taking advantage of the observable expectation value being bilinear in the evolution operator and its adjoint. The consequences of this inherent robustness are discussed in the light of recent experiments and numerical simulations on the optimal control of quantum phenomena. The analysis in this paper bodes well for the future success of closed-loop quantum optimal control experiments, even in the presence of reasonable levels of field fluctuations

  4. Wavelet Filtering to Reduce Conservatism in Aeroservoelastic Robust Stability Margins

    Science.gov (United States)

    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.

  5. Adaptive integral robust control and application to electromechanical servo systems.

    Science.gov (United States)

    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.

  6. Optimal interdependence enhances the dynamical robustness of complex systems

    Science.gov (United States)

    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.

  7. An Integrated Approach to Single-Leg Airline Revenue Management: The Role of Robust Optimization

    OpenAIRE

    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...

  8. Robust and Air-Stable Sandwiched Organo-Lead Halide Perovskites for Photodetector Applications

    KAUST Repository

    Mohammed, Omar F.

    2016-02-25

    We report the simplest possible method to date for fabricating robust, air-stable, sandwiched perovskite photodetectors. Our proposed sandwiched structure is devoid of electron or hole transporting layers and also the expensive electrodes. These simpler architectures may have application in the perovskite-only class of solar cells scaling up towards commercialization.

  9. Robust stabilization of nonlinear systems: The LMI approach

    Directory of Open Access Journals (Sweden)

    Šiljak D. D.

    2000-01-01

    Full Text Available This paper presents a new approach to robust quadratic stabilization of nonlinear systems within the framework of Linear Matrix Inequalities (LMI. The systems are composed of a linear constant part perturbed by an additive nonlinearity which depends discontinuously on both time and state. The only information about the nonlinearity is that it satisfies a quadratic constraint. Our major objective is to show how linear constant feedback laws can be formulated to stabilize this type of systems and, at the same time, maximize the bounds on the nonlinearity which the system can tolerate without going unstable. We shall broaden the new setting to include design of decentralized control laws for robust stabilization of interconnected systems. Again, the LMI methods will be used to maximize the class of uncertain interconnections which leave the overall system connectively stable. It is useful to learn that the proposed LMI formulation “recognizes” the matching conditions by returning a feedback gain matrix for any prescribed bound on the interconnection terms. More importantly, the new formulation provides a suitable setting for robust stabilization of nonlinear systems where the nonlinear perturbations satisfy the generalized matching conditions.

  10. Unsteady Sail Dynamics in Olympic Class Sailboats

    Science.gov (United States)

    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.

  11. Robustness leads close to the edge of chaos in coupled map networks: toward the understanding of biological networks

    International Nuclear Information System (INIS)

    Saito, Nen; Kikuchi, Macoto

    2013-01-01

    Dynamics in biological networks are, in general, robust against several perturbations. We investigate a coupled map network as a model motivated by gene regulatory networks and design systems that are robust against phenotypic perturbations (perturbations in dynamics), as well as systems that are robust against mutation (perturbations in network structure). To achieve such a design, we apply a multicanonical Monte Carlo method. Analysis based on the maximum Lyapunov exponent and parameter sensitivity shows that systems with marginal stability, which are regarded as systems at the edge of chaos, emerge when robustness against network perturbations is required. This emergence of the edge of chaos is a self-organization phenomenon and does not need a fine tuning of parameters. (paper)

  12. Robust approximation-free prescribed performance control for nonlinear systems and its application

    Science.gov (United States)

    Sun, Ruisheng; Na, Jing; Zhu, Bin

    2018-02-01

    This paper presents a robust prescribed performance control approach and its application to nonlinear tail-controlled missile systems with unknown dynamics and uncertainties. The idea of prescribed performance function (PPF) is incorporated into the control design, such that both the steady-state and transient control performance can be strictly guaranteed. Unlike conventional PPF-based control methods, we further tailor a recently proposed systematic control design procedure (i.e. approximation-free control) using the transformed tracking error dynamics, which provides a proportional-like control action. Hence, the function approximators (e.g. neural networks, fuzzy systems) that are widely used to address the unknown nonlinearities in the nonlinear control designs are not needed. The proposed control design leads to a robust yet simplified function approximation-free control for nonlinear systems. The closed-loop system stability and the control error convergence are all rigorously proved. Finally, comparative simulations are conducted based on nonlinear missile systems to validate the improved response and the robustness of the proposed control method.

  13. A Combination of Central Pattern Generator-based and Reflex-based Neural Networks for Dynamic, Adaptive, Robust Bipedal Locomotion

    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...

  14. 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

  15. Peptide Binding to HLA Class I Molecules: Homogenous, High-Throughput Screening, and Affinity Assays

    DEFF Research Database (Denmark)

    Harndahl, Mikkel; Justesen, Sune Frederik Lamdahl; Lamberth, Kasper

    2009-01-01

    , better signal-to-background ratios, and a higher capacity. They also describe an efficient approach to screen peptides for binding to HLA molecules. For the occasional user, this will serve as a robust, simple peptide-HLA binding assay. For the more dedicated user, it can easily be performed in a high-throughput...... the luminescent oxygen channeling immunoassay technology (abbreviated LOCI and commercialized as AlphaScreen (TM)). Compared with an enzyme-linked immunosorbent assay-based peptide-HLA class I binding assay, the LOCI assay yields virtually identical affinity measurements, although having a broader dynamic range...... screening mode using standard liquid handling robotics and 384-well plates. We have successfully applied this assay to more than 60 different HLA molecules, leading to more than 2 million measurements. (Journal of Biomolecular Screening 2009: 173-180)...

  16. Robust design optimization using the price of robustness, robust least squares and regularization methods

    Science.gov (United States)

    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.

  17. Recursive Estimation for Dynamical Systems with Different Delay Rates Sensor Network and Autocorrelated Process Noises

    Directory of Open Access Journals (Sweden)

    Jianxin Feng

    2014-01-01

    Full Text Available The recursive estimation problem is studied for a class of uncertain dynamical systems with different delay rates sensor network and autocorrelated process noises. The process noises are assumed to be autocorrelated across time and the autocorrelation property is described by the covariances between different time instants. The system model under consideration is subject to multiplicative noises or stochastic uncertainties. The sensor delay phenomenon occurs in a random way and each sensor in the sensor network has an individual delay rate which is characterized by a binary switching sequence obeying a conditional probability distribution. By using the orthogonal projection theorem and an innovation analysis approach, the desired recursive robust estimators including recursive robust filter, predictor, and smoother are obtained. Simulation results are provided to demonstrate the effectiveness of the proposed approaches.

  18. Robust Trajectory Design in Highly Perturbed Environments Leveraging Continuation Methods, Phase I

    Data.gov (United States)

    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...

  19. Robust ℋ∞ Dynamic Output Feedback Control Synthesis with Pole Placement Constraints for Offshore Wind Turbine Systems

    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.

  20. Mathematical Relationships between Neuron Morphology and Neurite Growth Dynamics in Drosophila melanogaster Larva Class IV Sensory Neurons

    Science.gov (United States)

    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.

  1. Analysis and control of complex dynamical systems robust bifurcation, dynamic attractors, and network complexity

    CERN Document Server

    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.

  2. Study of Robust H∞ Filtering Application in Loosely Coupled INS/GPS System

    Directory of Open Access Journals (Sweden)

    Lin Zhao

    2014-01-01

    model, unstable model case is considered. We give an explanation for Kalman filter divergence under uncertain dynamic system and simultaneously investigate the relationship between H∞ filter and Kalman filter. A loosely coupled INS/GPS simulation system is given here to verify this application. Result shows that the robust H∞ filter has a better performance when system suffers uncertainty; also it is more robust compared to the conventional Kalman filter.

  3. Challenging the Black Church Narrative: Race, Class, and Homosexual Attitudes.

    Science.gov (United States)

    Irizarry, Yasmiyn A; Perry, Ravi K

    2018-01-01

    In recent years, scholars have pointed to the Black church as the driving force behind Blacks' more conservative lesbian, gay, bisexual, and transgendered (LGBT) attitudes. Although evidence suggests a robust association between religiosity and LGBT attitudes, contemporary scholarship has not examined the role of class or the extent to which religiosity actually explains these trends. Using the 2004-2014 waves of the General Social Survey, we find that class moderates in the effect of race on negative LGBT attitudes, resulting in a noticeably larger gap between middle-class Blacks and Whites than in the top or the bottom of the class distribution. Although religiosity and moralization explain a portion of racial differences in homosexual attitudes across class groups, we find that neither fully accounts for the more conservative attitudes of the Black middle class. We conclude by discussing the shortcomings of these narratives for understanding Blacks' more conservative LGBT attitudes.

  4. A robust multivariate long run analysis of European electricity prices

    OpenAIRE

    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...

  5. Robustness against parametric noise of nonideal holonomic gates

    International Nuclear Information System (INIS)

    Lupo, Cosmo; Aniello, Paolo; Napolitano, Mario; Florio, Giuseppe

    2007-01-01

    Holonomic gates for quantum computation are commonly considered to be robust against certain kinds of parametric noise, the cause of this robustness being the geometric character of the transformation achieved in the adiabatic limit. On the other hand, the effects of decoherence are expected to become more and more relevant when the adiabatic limit is approached. Starting from the system described by Florio et al. [Phys. Rev. A 73, 022327 (2006)], here we discuss the behavior of nonideal holonomic gates at finite operational time, i.e., long before the adiabatic limit is reached. We have considered several models of parametric noise and studied the robustness of finite-time gates. The results obtained suggest that the finite-time gates present some effects of cancellation of the perturbations introduced by the noise which mimic the geometrical cancellation effect of standard holonomic gates. Nevertheless, a careful analysis of the results leads to the conclusion that these effects are related to a dynamical instead of a geometrical feature

  6. Robustness against parametric noise of nonideal holonomic gates

    Science.gov (United States)

    Lupo, Cosmo; Aniello, Paolo; Napolitano, Mario; Florio, Giuseppe

    2007-07-01

    Holonomic gates for quantum computation are commonly considered to be robust against certain kinds of parametric noise, the cause of this robustness being the geometric character of the transformation achieved in the adiabatic limit. On the other hand, the effects of decoherence are expected to become more and more relevant when the adiabatic limit is approached. Starting from the system described by Florio [Phys. Rev. A 73, 022327 (2006)], here we discuss the behavior of nonideal holonomic gates at finite operational time, i.e., long before the adiabatic limit is reached. We have considered several models of parametric noise and studied the robustness of finite-time gates. The results obtained suggest that the finite-time gates present some effects of cancellation of the perturbations introduced by the noise which mimic the geometrical cancellation effect of standard holonomic gates. Nevertheless, a careful analysis of the results leads to the conclusion that these effects are related to a dynamical instead of a geometrical feature.

  7. 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.

  8. A Unifying Mathematical Framework for Genetic Robustness, Environmental Robustness, Network Robustness and their Trade-offs on Phenotype Robustness in Biological Networks. Part III: Synthetic Gene Networks in Synthetic Biology

    Science.gov (United States)

    Chen, Bor-Sen; Lin, Ying-Po

    2013-01-01

    Robust stabilization and environmental disturbance attenuation are ubiquitous systematic properties that are observed in biological systems at many different levels. The underlying principles for robust stabilization and environmental disturbance attenuation are universal to both complex biological systems and sophisticated engineering systems. In many biological networks, network robustness should be large enough to confer: intrinsic robustness for tolerating intrinsic parameter fluctuations; genetic robustness for buffering genetic variations; and environmental robustness for resisting environmental disturbances. Network robustness is needed so phenotype stability of biological network can be maintained, guaranteeing phenotype robustness. Synthetic biology is foreseen to have important applications in biotechnology and medicine; it is expected to contribute significantly to a better understanding of functioning of complex biological systems. This paper presents a unifying mathematical framework for investigating the principles of both robust stabilization and environmental disturbance attenuation for synthetic gene networks in synthetic biology. Further, from the unifying mathematical framework, we found that the phenotype robustness criterion for synthetic gene networks is the following: if intrinsic robustness + genetic robustness + environmental robustness ≦ network robustness, then the phenotype robustness can be maintained in spite of intrinsic parameter fluctuations, genetic variations, and environmental disturbances. Therefore, the trade-offs between intrinsic robustness, genetic robustness, environmental robustness, and network robustness in synthetic biology can also be investigated through corresponding phenotype robustness criteria from the systematic point of view. Finally, a robust synthetic design that involves network evolution algorithms with desired behavior under intrinsic parameter fluctuations, genetic variations, and environmental

  9. Transfer Learning for Class Imbalance Problems with Inadequate Data.

    Science.gov (United States)

    Al-Stouhi, Samir; Reddy, Chandan K

    2016-07-01

    A fundamental problem in data mining is to effectively build robust classifiers in the presence of skewed data distributions. Class imbalance classifiers are trained specifically for skewed distribution datasets. Existing methods assume an ample supply of training examples as a fundamental prerequisite for constructing an effective classifier. However, when sufficient data is not readily available, the development of a representative classification algorithm becomes even more difficult due to the unequal distribution between classes. We provide a unified framework that will potentially take advantage of auxiliary data using a transfer learning mechanism and simultaneously build a robust classifier to tackle this imbalance issue in the presence of few training samples in a particular target domain of interest. Transfer learning methods use auxiliary data to augment learning when training examples are not sufficient and in this paper we will develop a method that is optimized to simultaneously augment the training data and induce balance into skewed datasets. We propose a novel boosting based instance-transfer classifier with a label-dependent update mechanism that simultaneously compensates for class imbalance and incorporates samples from an auxiliary domain to improve classification. We provide theoretical and empirical validation of our method and apply to healthcare and text classification applications.

  10. Production and robustness of a Cacao agroecosystem: effects of two contrasting types of management strategies.

    Science.gov (United States)

    Sabatier, Rodolphe; Wiegand, Kerstin; Meyer, Katrin

    2013-01-01

    Ecological intensification, i.e. relying on ecological processes to replace chemical inputs, is often presented as the ideal alternative to conventional farming based on an intensive use of chemicals. It is said to both maintain high yield and provide more robustness to the agroecosystem. However few studies compared the two types of management with respect to their consequences for production and robustness toward perturbation. In this study our aim is to assess productive performance and robustness toward diverse perturbations of a Cacao agroecosystem managed with two contrasting groups of strategies: one group of strategies relying on a high level of pesticides and a second relying on low levels of pesticides. We conducted this study using a dynamical model of a Cacao agroecosystem that includes Cacao production dynamics, and dynamics of three insects: a pest (the Cacao Pod Borer, Conopomorpha cramerella) and two characteristic but unspecified beneficial insects (a pollinator of Cacao and a parasitoid of the Cacao Pod Borer). Our results showed two opposite behaviors of the Cacao agroecosystem depending on its management, i.e. an agroecosystem relying on a high input of pesticides and showing low ecosystem functioning and an agroecosystem with low inputs, relying on a high functioning of the ecosystem. From the production point of view, no type of management clearly outclassed the other and their ranking depended on the type of pesticide used. From the robustness point of view, the two types of managements performed differently when subjected to different types of perturbations. Ecologically intensive systems were more robust to pest outbreaks and perturbations related to pesticide characteristics while chemically intensive systems were more robust to Cacao production and management-related perturbation.

  11. Self-consistent residual dipolar coupling based model-free analysis for the robust determination of nanosecond to microsecond protein dynamics

    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

  12. 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...

  13. Robustness analysis method for orbit control

    Science.gov (United States)

    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.

  14. Generalized shortcuts to adiabaticity and enhanced robustness against decoherence

    Science.gov (United States)

    Santos, Alan C.; Sarandy, Marcelo S.

    2018-01-01

    Shortcuts to adiabaticity provide a general approach to mimic adiabatic quantum processes via arbitrarily fast evolutions in Hilbert space. For these counter-diabatic evolutions, higher speed comes at higher energy cost. Here, the counter-diabatic theory is employed as a minimal energy demanding scheme for speeding up adiabatic tasks. As a by-product, we show that this approach can be used to obtain infinite classes of transitionless models, including time-independent Hamiltonians under certain conditions over the eigenstates of the original Hamiltonian. We apply these results to investigate shortcuts to adiabaticity in decohering environments by introducing the requirement of a fixed energy resource. In this scenario, we show that generalized transitionless evolutions can be more robust against decoherence than their adiabatic counterparts. We illustrate this enhanced robustness both for the Landau-Zener model and for quantum gate Hamiltonians.

  15. Matlab as a robust control design tool

    Science.gov (United States)

    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.

  16. Electrically tunable robust edge states in graphene-based topological photonic crystal slabs

    Science.gov (United States)

    Song, Zidong; Liu, HongJun; Huang, Nan; Wang, ZhaoLu

    2018-03-01

    Topological photonic crystals are optical structures supporting topologically protected unidirectional edge states that exhibit robustness against defects. Here, we propose a graphene-based all-dielectric photonic crystal slab structure that supports two-dimensionally confined topological edge states. These topological edge states can be confined in the out-of-plane direction by two parallel graphene sheets. In the structure, the excitation frequency range of topological edge states can be dynamically and continuously tuned by varying bias voltage across the two parallel graphene sheets. Utilizing this kind of architecture, we construct Z-shaped channels to realize topological edge transmission with diffrerent frequencies. The proposal provides a new degree of freedom to dynamically control topological edge states and potential applications for robust integrated photonic devices and optical communication systems.

  17. Investigation on changes of modularity and robustness by edge-removal mutations in signaling networks.

    Science.gov (United States)

    Truong, Cong-Doan; Kwon, Yung-Keun

    2017-12-21

    Biological networks consisting of molecular components and interactions are represented by a graph model. There have been some studies based on that model to analyze a relationship between structural characteristics and dynamical behaviors in signaling network. However, little attention has been paid to changes of modularity and robustness in mutant networks. In this paper, we investigated the changes of modularity and robustness by edge-removal mutations in three signaling networks. We first observed that both the modularity and robustness increased on average in the mutant network by the edge-removal mutations. However, the modularity change was negatively correlated with the robustness change. This implies that it is unlikely that both the modularity and the robustness values simultaneously increase by the edge-removal mutations. Another interesting finding is that the modularity change was positively correlated with the degree, the number of feedback loops, and the edge betweenness of the removed edges whereas the robustness change was negatively correlated with them. We note that these results were consistently observed in randomly structure networks. Additionally, we identified two groups of genes which are incident to the highly-modularity-increasing and the highly-robustness-decreasing edges with respect to the edge-removal mutations, respectively, and observed that they are likely to be central by forming a connected component of a considerably large size. The gene-ontology enrichment of each of these gene groups was significantly different from the rest of genes. Finally, we showed that the highly-robustness-decreasing edges can be promising edgetic drug-targets, which validates the usefulness of our analysis. Taken together, the analysis of changes of robustness and modularity against edge-removal mutations can be useful to unravel novel dynamical characteristics underlying in signaling networks.

  18. Photonic circuits for iterative decoding of a class of low-density parity-check codes

    International Nuclear Information System (INIS)

    Pavlichin, Dmitri S; Mabuchi, Hideo

    2014-01-01

    Photonic circuits in which stateful components are coupled via guided electromagnetic fields are natural candidates for resource-efficient implementation of iterative stochastic algorithms based on propagation of information around a graph. Conversely, such message=passing algorithms suggest novel circuit architectures for signal processing and computation that are well matched to nanophotonic device physics. Here, we construct and analyze a quantum optical model of a photonic circuit for iterative decoding of a class of low-density parity-check (LDPC) codes called expander codes. Our circuit can be understood as an open quantum system whose autonomous dynamics map straightforwardly onto the subroutines of an LDPC decoding scheme, with several attractive features: it can operate in the ultra-low power regime of photonics in which quantum fluctuations become significant, it is robust to noise and component imperfections, it achieves comparable performance to known iterative algorithms for this class of codes, and it provides an instructive example of how nanophotonic cavity quantum electrodynamic components can enable useful new information technology even if the solid-state qubits on which they are based are heavily dephased and cannot support large-scale entanglement. (paper)

  19. Fractional-order sliding mode control for a class of uncertain nonlinear systems based on LQR

    Directory of Open Access Journals (Sweden)

    Dong Zhang

    2017-03-01

    Full Text Available This article presents a new fractional-order sliding mode control (FOSMC strategy based on a linear-quadratic regulator (LQR for a class of uncertain nonlinear systems. First, input/output feedback linearization is used to linearize the nonlinear system and decouple tracking error dynamics. Second, LQR is designed to ensure that the tracking error dynamics converges to the equilibrium point as soon as possible. Based on LQR, a novel fractional-order sliding surface is introduced. Subsequently, the FOSMC is designed to reject system uncertainties and reduce the magnitude of control chattering. Then, the global stability of the closed-loop control system is analytically proved using Lyapunov stability theory. Finally, a typical single-input single-output system and a typical multi-input multi-output system are simulated to illustrate the effectiveness and advantages of the proposed control strategy. The results of the simulation indicate that the proposed control strategy exhibits excellent performance and robustness with system uncertainties. Compared to conventional integer-order sliding mode control, the high-frequency chattering of the control input is drastically depressed.

  20. 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.

  1. Boundedness and global robust stability analysis of delayed complex-valued neural networks with interval parameter uncertainties.

    Science.gov (United States)

    Song, Qiankun; Yu, Qinqin; Zhao, Zhenjiang; Liu, Yurong; Alsaadi, Fuad E

    2018-07-01

    In this paper, the boundedness and robust stability for a class of delayed complex-valued neural networks with interval parameter uncertainties are investigated. By using Homomorphic mapping theorem, Lyapunov method and inequality techniques, sufficient condition to guarantee the boundedness of networks and the existence, uniqueness and global robust stability of equilibrium point is derived for the considered uncertain neural networks. The obtained robust stability criterion is expressed in complex-valued LMI, which can be calculated numerically using YALMIP with solver of SDPT3 in MATLAB. An example with simulations is supplied to show the applicability and advantages of the acquired result. Copyright © 2018 Elsevier Ltd. All rights reserved.

  2. Robust transient stabilisation problem for a synchronous generator in a power network

    Science.gov (United States)

    Verrelli, C. M.; Damm, G.

    2010-04-01

    The robust transient stabilisation problem (with stability proof€) of a synchronous generator in an uncertain power network with transfer conductances is rigorously formulated and solved. The generator angular speed and electrical power are required to be kept close, when mechanical and electrical perturbations occur, to the synchronous speed and mechanical input power, respectively, while the generator terminal voltage is to be regulated, when perturbations are removed, to its pre-fault reference constant value. A robust adaptive nonlinear feedback control algorithm is designed on the basis of a third-order model of the synchronous machine: only two system parameters (synchronous machine damping and inertia constants) along with upper and lower bounds on the remaining uncertain ones are supposed to be known. The conditions to be satisfied by the remote network dynamics for guaranteeing ℒ2 and ℒ∞ robustness and asymptotic relative speed and voltage regulation to zero are weaker than those required by the single machine-infinite bus approximation: dynamic interactions between the local deviations of the generator states from the corresponding equilibrium values and the remote generators states are allowed.

  3. Perceptual Robust Design

    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...

  4. 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...

  5. A class of stochastic games with infinitely many interacting agents related to Glauber dynamics on random graphs

    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

  6. Adaptive neural network output feedback control for stochastic nonlinear systems with unknown dead-zone and unmodeled dynamics.

    Science.gov (United States)

    Tong, Shaocheng; Wang, Tong; Li, Yongming; Zhang, Huaguang

    2014-06-01

    This paper discusses the problem of adaptive neural network output feedback control for a class of stochastic nonlinear strict-feedback systems. The concerned systems have certain characteristics, such as unknown nonlinear uncertainties, unknown dead-zones, unmodeled dynamics and without the direct measurements of state variables. In this paper, the neural networks (NNs) are employed to approximate the unknown nonlinear uncertainties, and then by representing the dead-zone as a time-varying system with a bounded disturbance. An NN state observer is designed to estimate the unmeasured states. Based on both backstepping design technique and a stochastic small-gain theorem, a robust adaptive NN output feedback control scheme is developed. It is proved that all the variables involved in the closed-loop system are input-state-practically stable in probability, and also have robustness to the unmodeled dynamics. Meanwhile, the observer errors and the output of the system can be regulated to a small neighborhood of the origin by selecting appropriate design parameters. Simulation examples are also provided to illustrate the effectiveness of the proposed approach.

  7. 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

  8. Robustness and Contingent History: From Prisoner's Dilemma to Gaia Theory.

    Science.gov (United States)

    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.

  9. Closed-Loop and Robust Control of Quantum Systems

    Directory of Open Access Journals (Sweden)

    Chunlin Chen

    2013-01-01

    Full Text Available For most practical quantum control systems, it is important and difficult to attain robustness and reliability due to unavoidable uncertainties in the system dynamics or models. Three kinds of typical approaches (e.g., closed-loop learning control, feedback control, and robust control have been proved to be effective to solve these problems. This work presents a self-contained survey on the closed-loop and robust control of quantum systems, as well as a brief introduction to a selection of basic theories and methods in this research area, to provide interested readers with a general idea for further studies. In the area of closed-loop learning control of quantum systems, we survey and introduce such learning control methods as gradient-based methods, genetic algorithms (GA, and reinforcement learning (RL methods from a unified point of view of exploring the quantum control landscapes. For the feedback control approach, the paper surveys three control strategies including Lyapunov control, measurement-based control, and coherent-feedback control. Then such topics in the field of quantum robust control as H∞ control, sliding mode control, quantum risk-sensitive control, and quantum ensemble control are reviewed. The paper concludes with a perspective of future research directions that are likely to attract more attention.

  10. Closed-loop and robust control of quantum systems.

    Science.gov (United States)

    Chen, Chunlin; Wang, Lin-Cheng; Wang, Yuanlong

    2013-01-01

    For most practical quantum control systems, it is important and difficult to attain robustness and reliability due to unavoidable uncertainties in the system dynamics or models. Three kinds of typical approaches (e.g., closed-loop learning control, feedback control, and robust control) have been proved to be effective to solve these problems. This work presents a self-contained survey on the closed-loop and robust control of quantum systems, as well as a brief introduction to a selection of basic theories and methods in this research area, to provide interested readers with a general idea for further studies. In the area of closed-loop learning control of quantum systems, we survey and introduce such learning control methods as gradient-based methods, genetic algorithms (GA), and reinforcement learning (RL) methods from a unified point of view of exploring the quantum control landscapes. For the feedback control approach, the paper surveys three control strategies including Lyapunov control, measurement-based control, and coherent-feedback control. Then such topics in the field of quantum robust control as H(∞) control, sliding mode control, quantum risk-sensitive control, and quantum ensemble control are reviewed. The paper concludes with a perspective of future research directions that are likely to attract more attention.

  11. Robust Control of Underactuated Systems: Higher Order Integral Sliding Mode Approach

    Directory of Open Access Journals (Sweden)

    Sami ud Din

    2016-01-01

    Full Text Available This paper presents a robust control design for the class of underactuated uncertain nonlinear systems. Either the nonlinear model of the underactuated systems is transformed into an input output form and then an integral manifold is devised for the control design purpose or an integral manifold is defined directly for the concerned class. Having defined the integral manifolds discontinuous control laws are designed which are capable of maintaining sliding mode from the very beginning. The closed loop stability of these systems is presented in an impressive way. The effectiveness and demand of the designed control laws are verified via the simulation and experimental results of ball and beam system.

  12. On the robustness of the fixed points for a dynamical performance characteristic - or: a closer look at the Langevin power curve

    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...

  13. Americans Still Overestimate Social Class Mobility: A Pre-Registered Self-Replication.

    Science.gov (United States)

    Kraus, Michael W

    2015-01-01

    Kraus and Tan (2015) hypothesized that Americans tend to overestimate social class mobility in society, and do so because they seek to protect the self. This paper reports a pre-registered exact replication of Study 3 from this original paper and finds, consistent with the original study, that Americans substantially overestimate social class mobility, that people provide greater overestimates when made while thinking of similar others, and that high perceived social class is related to greater overestimates. The current results provide additional evidence consistent with the idea that people overestimate class mobility to protect their beliefs in the promise of equality of opportunity. Discussion considers the utility of pre-registered self-replications as one tool for encouraging replication efforts and assessing the robustness of effect sizes.

  14. Ansatz for dynamical hierarchies

    DEFF Research Database (Denmark)

    Rasmussen, S.; Baas, N.A.; Mayer, B.

    2001-01-01

    Complex, robust functionalities can be generated naturally in at least two ways: by the assembly of structures and by the evolution of structures. This work is concerned with spontaneous formation of structures. We define the notion of dynamical hierarchies in natural systems and show...... the importance of this particular kind of organization for living systems. We then define a framework that enables us to formulate, investigate, and manipulate such dynamical hierarchies. This framework allows us to simultaneously investigate different levels of description together with them interrelationship...... three. Formulating this system as a simple two-dimensional molecular dynamics (MD) lattice gas allows us within one dynamical system to demonstrate the successive emergence of two higher levels (three levels all together) of robust structures with associated properties. Second, we demonstrate how...

  15. Social Class on Campus: Theories and Manifestations

    Science.gov (United States)

    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…

  16. Robust Bayesian decision theory applied to optimal dosage.

    Science.gov (United States)

    Abraham, Christophe; Daurès, Jean-Pierre

    2004-04-15

    We give a model for constructing an utility function u(theta,d) in a dose prescription problem. theta and d denote respectively the patient state of health and the dose. The construction of u is based on the conditional probabilities of several variables. These probabilities are described by logistic models. Obviously, u is only an approximation of the true utility function and that is why we investigate the sensitivity of the final decision with respect to the utility function. We construct a class of utility functions from u and approximate the set of all Bayes actions associated to that class. Then, we measure the sensitivity as the greatest difference between the expected utilities of two Bayes actions. Finally, we apply these results to weighing up a chemotherapy treatment of lung cancer. This application emphasizes the importance of measuring robustness through the utility of decisions rather than the decisions themselves. Copyright 2004 John Wiley & Sons, Ltd.

  17. Using a dynamic, introductory-level volcanoes class as a means to introduce non-science majors to the geosciences

    Science.gov (United States)

    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

  18. Robust multivariate analysis

    CERN Document Server

    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...

  19. Robust Visual Tracking via Online Discriminative and Low-Rank Dictionary Learning.

    Science.gov (United States)

    Zhou, Tao; Liu, Fanghui; Bhaskar, Harish; Yang, Jie

    2017-09-12

    In this paper, we propose a novel and robust tracking framework based on online discriminative and low-rank dictionary learning. The primary aim of this paper is to obtain compact and low-rank dictionaries that can provide good discriminative representations of both target and background. We accomplish this by exploiting the recovery ability of low-rank matrices. That is if we assume that the data from the same class are linearly correlated, then the corresponding basis vectors learned from the training set of each class shall render the dictionary to become approximately low-rank. The proposed dictionary learning technique incorporates a reconstruction error that improves the reliability of classification. Also, a multiconstraint objective function is designed to enable active learning of a discriminative and robust dictionary. Further, an optimal solution is obtained by iteratively computing the dictionary, coefficients, and by simultaneously learning the classifier parameters. Finally, a simple yet effective likelihood function is implemented to estimate the optimal state of the target during tracking. Moreover, to make the dictionary adaptive to the variations of the target and background during tracking, an online update criterion is employed while learning the new dictionary. Experimental results on a publicly available benchmark dataset have demonstrated that the proposed tracking algorithm performs better than other state-of-the-art trackers.

  20. Towards generalizing co-evolutionary dynamics of socio-hydrology: Theoretical frameworks of cultural evolution and robustness-fragility tradeoff

    Science.gov (United States)

    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.

  1. Cassie state robustness of plasma generated randomly nano-rough surfaces

    Energy Technology Data Exchange (ETDEWEB)

    Di Mundo, Rosa, E-mail: rosa.dimundo@poliba.it; Bottiglione, Francesco; Carbone, Giuseppe

    2014-10-15

    Graphical abstract: - Highlights: • Superhydrophobic randomly rough surfaces are generated by plasma etching. • Statistical analysis of roughness allows calculation of theWenzel roughness factor, r{sub W.} • A r{sub W} threshold is theoretically determined, above which superhydrophobicity is “robust”. • Dynamic wetting, e.g. with high speed impacting drops, confirms this prediction. - Abstract: Superhydrophobic surfaces are effective in practical applications provided they are “robust superhydrophobic”, i.e. able to retain the Cassie state, i.e. with water suspended onto the surface protrusions, even under severe conditions (high pressure, vibrations, high speed impact, etc.). We show that for randomly rough surfaces, given the Young angle, Cassie states are robust when a threshold value of the Wenzel roughness factor, r{sub W}, is exceeded. In particular, superhydrophobic nano-textured surfaces have been generated by self-masked plasma etching. In view of their random roughness, topography features, acquired by Atomic Force Microscopy, have been statistically analyzed in order to gain information on statistical parameters such as power spectral density, fractal dimension and Wenzel roughness factor (r{sub W}), which has been used to assess Cassie state robustness. Results indicate that randomly rough surfaces produced by plasma at high power or long treatment duration, which are also fractal self-affine, have a r{sub W} higher than the theoretical threshold, thus for them a robust superhydrophobicity is predicted. In agreement with this, under dynamic wetting conditionson these surfaces the most pronounced superhydrophobic character has been appreciated: they show the lowest contact angle hysteresis and result in the sharpest bouncing when hit by drops at high impact velocity.

  2. Adaptive Robust Online Constructive Fuzzy Control of a Complex Surface Vehicle System.

    Science.gov (United States)

    Wang, Ning; Er, Meng Joo; Sun, Jing-Chao; Liu, Yan-Cheng

    2016-07-01

    In this paper, a novel adaptive robust online constructive fuzzy control (AR-OCFC) scheme, employing an online constructive fuzzy approximator (OCFA), to deal with tracking surface vehicles with uncertainties and unknown disturbances is proposed. Significant contributions of this paper are as follows: 1) unlike previous self-organizing fuzzy neural networks, the OCFA employs decoupled distance measure to dynamically allocate discriminable and sparse fuzzy sets in each dimension and is able to parsimoniously self-construct high interpretable T-S fuzzy rules; 2) an OCFA-based dominant adaptive controller (DAC) is designed by employing the improved projection-based adaptive laws derived from the Lyapunov synthesis which can guarantee reasonable fuzzy partitions; 3) closed-loop system stability and robustness are ensured by stable cancelation and decoupled adaptive compensation, respectively, thereby contributing to an auxiliary robust controller (ARC); and 4) global asymptotic closed-loop system can be guaranteed by AR-OCFC consisting of DAC and ARC and all signals are bounded. Simulation studies and comprehensive comparisons with state-of-the-arts fixed- and dynamic-structure adaptive control schemes demonstrate superior performance of the AR-OCFC in terms of tracking and approximation accuracy.

  3. Dynamical Conductivity across the Disorder-Tuned Superconductor-Insulator Transition

    Directory of Open Access Journals (Sweden)

    Mason Swanson

    2014-04-01

    Full Text Available We calculate the dynamical conductivity σ(ω and the bosonic (pair spectral function P(ω from quantum Monte Carlo simulations across clean and disorder-driven superconductor-insulator transitions (SITs. We identify characteristic energy scales in the superconducting and insulating phases that vanish at the transition due to enhanced quantum fluctuations, despite the persistence of a robust fermionic gap across the SIT. Disorder leads to enhanced absorption in σ(ω at low frequencies compared to the SIT in a clean system. Disorder also expands the quantum critical region, due to a change in the universality class, with an underlying T=0 critical point with a universal low-frequency conductivity σ^{*}≃0.5(4e^{2}/h.

  4. Robust nonlinear control of nuclear reactors under model uncertainty

    International Nuclear Information System (INIS)

    Park, Moon Ghu

    1993-02-01

    A nonlinear model-based control method is developed for the robust control of a nuclear reactor. The nonlinear plant model is used to design a unique control law which covers a wide operating range. The robustness is a crucial factor for the fully automatic control of reactor power due to time-varying, uncertain parameters, and state estimation error, or unmodeled dynamics. A variable structure control (VSC) method is introduced which consists of an adaptive performance specification (fime control) after the tracking error reaches the narrow boundary-layer by a time-optimal control (coarse control). Variable structure control is a powerful method for nonlinear system controller design which has inherent robustness to parameter variations or external disturbances using the known uncertainty bounds, and it requires very low computational efforts. In spite of its desirable properties, conventional VSC presents several important drawbacks that limit its practical applicability. One of the most undesirable phenomena is chattering, which implies extremely high control activity and may excite high-frequency unmodeled dynamics. This problem is due to the neglected actuator time-delay or sampling effects. The problem was partially remedied by replacing chattering control by a smooth control inter-polation in a boundary layer neighnboring a time-varying sliding surface. But, for the nuclear reactor systems which has very fast dynamic response, the sampling effect may destroy the narrow boundary layer when a large uncertainty bound is used. Due to the very short neutron life time, large uncertainty bound leads to the high gain in feedback control. To resolve this problem, a derivative feedback is introduced that gives excellent performance by reducing the uncertainty bound. The stability of tracking error dynamics is guaranteed by the second method of Lyapunov using the two-level uncertainty bounds that are obtained from the knowledge of uncertainty bound and the estimated

  5. Nonlinear adaptive robust back stepping force control of hydraulic load simulator: Theory and experiments

    International Nuclear Information System (INIS)

    Yao, Jianyong; Jiao, Zongxia; Yao, Bin

    2014-01-01

    High performance robust force control of hydraulic load simulator with constant but unknown hydraulic parameters is considered. In contrast to the linear control based on hydraulic linearization equations, hydraulic inherent nonlinear properties and uncertainties make the conventional feedback proportional-integral-derivative (PID) control not yield to high performance requirements. Furthermore, the hydraulic system may be subjected to non-smooth and discontinuous nonlinearities due to the directional change of valve opening. In this paper, based on a nonlinear system model of hydraulic load simulator, a discontinuous projection-based nonlinear adaptive robust back stepping controller is developed with servo valve dynamics. The proposed controller constructs a novel stable adaptive controller and adaptation laws with additional pressure dynamic related unknown parameters, which can compensate for the system nonlinearities and uncertain parameters, meanwhile a well-designed robust controller is also synthesized to dominate the model uncertainties coming from both parametric uncertainties and uncertain nonlinearities including unmodeled and ignored system dynamics. The controller theoretically guarantee a prescribed transient performance and final tracking accuracy in presence of both parametric uncertainties and uncertain nonlinearities; while achieving asymptotic output tracking in the absence of unstructured uncertainties. The implementation issues are also discussed for controller simplification. Some comparative results are obtained to verify the high-performance nature of the proposed controller.

  6. Nonlinear adaptive robust back stepping force control of hydraulic load simulator: Theory and experiments

    Energy Technology Data Exchange (ETDEWEB)

    Yao, Jianyong [Nanjing University of Science and Technology, Nanjing (China); Jiao, Zongxia [Beihang University, Beijing (China); Yao, Bin [Purdue University, West Lafayette (United States)

    2014-04-15

    High performance robust force control of hydraulic load simulator with constant but unknown hydraulic parameters is considered. In contrast to the linear control based on hydraulic linearization equations, hydraulic inherent nonlinear properties and uncertainties make the conventional feedback proportional-integral-derivative (PID) control not yield to high performance requirements. Furthermore, the hydraulic system may be subjected to non-smooth and discontinuous nonlinearities due to the directional change of valve opening. In this paper, based on a nonlinear system model of hydraulic load simulator, a discontinuous projection-based nonlinear adaptive robust back stepping controller is developed with servo valve dynamics. The proposed controller constructs a novel stable adaptive controller and adaptation laws with additional pressure dynamic related unknown parameters, which can compensate for the system nonlinearities and uncertain parameters, meanwhile a well-designed robust controller is also synthesized to dominate the model uncertainties coming from both parametric uncertainties and uncertain nonlinearities including unmodeled and ignored system dynamics. The controller theoretically guarantee a prescribed transient performance and final tracking accuracy in presence of both parametric uncertainties and uncertain nonlinearities; while achieving asymptotic output tracking in the absence of unstructured uncertainties. The implementation issues are also discussed for controller simplification. Some comparative results are obtained to verify the high-performance nature of the proposed controller.

  7. Model predictive control classical, robust and stochastic

    CERN Document Server

    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...

  8. The Model Construction of English Ecological Class in the High School in China

    Science.gov (United States)

    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…

  9. 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...

  10. Robustness of Structures

    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...

  11. Americans Still Overestimate Social Class Mobility: A Pre-Registered Self-Replication

    Directory of Open Access Journals (Sweden)

    Michael W. Kraus

    2015-11-01

    Full Text Available Kraus and Tan (2015 hypothesized that Americans tend to overestimate social class mobility in society, and do so because they seek to protect the self. This paper reports a pre-registered exact replication of Study 3 from this original paper and finds, consistent with the original study, that Americans substantially overestimate social class mobility, that people provide greater overestimates when made while thinking of similar others, and that high perceived social class is related to greater overestimates. The current results provide additional evidence consistent with the idea that people overestimate class mobility to protect their beliefs in the promise of equality of opportunity. Discussion considers the utility of pre-registered self-replications as one tool for encouraging replication efforts and assessing the robustness of effect sizes.

  12. Robust passive control for Internet-based switching systems with time-delay

    Energy Technology Data Exchange (ETDEWEB)

    Guan Zhihong [Department of Control Science and Engineering, Huazhong University of Science and Technology, Wuhan, Hubei 430074 (China); Zhang Hao [Department of Control Science and Engineering, Huazhong University of Science and Technology, Wuhan, Hubei 430074 (China)], E-mail: ehao79@163.com; Yang Shuanghua [Department of Computer Science, Loughborough University, Loughborough LE11 3TU (United Kingdom)

    2008-04-15

    In this paper, based on remote control and local control strategy, a class of hybrid multi-rate control models with time-delay and switching controllers are formulated and the problem of robust passive control for this discrete system is investigated. By Lyapunov-Krasovskii function and applying it to a descriptor model transformation some new sufficient conditions in form of LMIs are derived. A numerical example is given to illustrate the effectiveness of the theoretical result.

  13. Employing Sensitivity Derivatives for Robust Optimization under Uncertainty in CFD

    Science.gov (United States)

    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.

  14. Robust fractional order differentiators using generalized modulating functions method

    KAUST Repository

    Liu, Dayan

    2015-02-01

    This paper aims at designing a fractional order differentiator for a class of signals satisfying a linear differential equation with unknown parameters. A generalized modulating functions method is proposed first to estimate the unknown parameters, then to derive accurate integral formulae for the left-sided Riemann-Liouville fractional derivatives of the studied signal. Unlike the improper integral in the definition of the left-sided Riemann-Liouville fractional derivative, the integrals in the proposed formulae can be proper and be considered as a low-pass filter by choosing appropriate modulating functions. Hence, digital fractional order differentiators applicable for on-line applications are deduced using a numerical integration method in discrete noisy case. Moreover, some error analysis are given for noise error contributions due to a class of stochastic processes. Finally, numerical examples are given to show the accuracy and robustness of the proposed fractional order differentiators.

  15. Robust fractional order differentiators using generalized modulating functions method

    KAUST Repository

    Liu, Dayan; Laleg-Kirati, Taous-Meriem

    2015-01-01

    This paper aims at designing a fractional order differentiator for a class of signals satisfying a linear differential equation with unknown parameters. A generalized modulating functions method is proposed first to estimate the unknown parameters, then to derive accurate integral formulae for the left-sided Riemann-Liouville fractional derivatives of the studied signal. Unlike the improper integral in the definition of the left-sided Riemann-Liouville fractional derivative, the integrals in the proposed formulae can be proper and be considered as a low-pass filter by choosing appropriate modulating functions. Hence, digital fractional order differentiators applicable for on-line applications are deduced using a numerical integration method in discrete noisy case. Moreover, some error analysis are given for noise error contributions due to a class of stochastic processes. Finally, numerical examples are given to show the accuracy and robustness of the proposed fractional order differentiators.

  16. Design and Implement a Digital H∞ Robust Controller for a MW-Class PMSG-Based Grid-Interactive Wind Energy Conversion System

    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.

  17. Alternative approaches for econometric analysis of panel count data using dynamic latent class models (with application to doctor visits data).

    Science.gov (United States)

    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.

  18. Robust Backstepping Control for Cold Rolling Main Drive System with Nonlinear Uncertainties

    Directory of Open Access Journals (Sweden)

    Xu Yang

    2013-01-01

    Full Text Available The nonlinear model of main drive system in cold rolling process, which considers the influence with parameter uncertainties such as clearance and variable friction coefficient, as well as external disturbance by roll eccentricity and variation of strip material quality, is built. By transformation, the lower triangular structure form of main drive system is obtained. The backstepping algorithm based on signal compensation is proposed to design a linear time-invariant (LTI robust controller, including a nominal controller and a robust compensator. A comparison with PI controller shows that the controller has better disturbance attenuation performance and tracking behaviors. Meanwhile, according to its LTI characteristic, the robust controller can be realized easily; therefore it is also appropriated to high speed dynamic rolling process.

  19. Assessing Disease Class-Specific Diagnostic Ability: A Practical Adaptive Test Approach.

    Science.gov (United States)

    Papa, Frank J.; Schumacker, Randall E.

    Measures of the robustness of disease class-specific diagnostic concepts could play a central role in training programs designed to assure the development of diagnostic competence. In the pilot study, the authors used disease/sign-symptom conditional probability estimates, Monte Carlo procedures, and artificial intelligence (AI) tools to create…

  20. A Robust Feedforward Model of the Olfactory System.

    Directory of Open Access Journals (Sweden)

    Yilun Zhang

    2016-04-01

    Full Text Available Most natural odors have sparse molecular composition. This makes the principles of compressed sensing potentially relevant to the structure of the olfactory code. Yet, the largely feedforward organization of the olfactory system precludes reconstruction using standard compressed sensing algorithms. To resolve this problem, recent theoretical work has shown that signal reconstruction could take place as a result of a low dimensional dynamical system converging to one of its attractor states. However, the dynamical aspects of optimization slowed down odor recognition and were also found to be susceptible to noise. Here we describe a feedforward model of the olfactory system that achieves both strong compression and fast reconstruction that is also robust to noise. A key feature of the proposed model is a specific relationship between how odors are represented at the glomeruli stage, which corresponds to a compression, and the connections from glomeruli to third-order neurons (neurons in the olfactory cortex of vertebrates or Kenyon cells in the mushroom body of insects, which in the model corresponds to reconstruction. We show that should this specific relationship hold true, the reconstruction will be both fast and robust to noise, and in particular to the false activation of glomeruli. The predicted connectivity rate from glomeruli to third-order neurons can be tested experimentally.

  1. 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

  2. Robust Economic Control Decision Method of Uncertain System on Urban Domestic Water Supply.

    Science.gov (United States)

    Li, Kebai; Ma, Tianyi; Wei, Guo

    2018-03-31

    As China quickly urbanizes, urban domestic water generally presents the circumstances of both rising tendency and seasonal cycle fluctuation. A robust economic control decision method for dynamic uncertain systems is proposed in this paper. It is developed based on the internal model principle and pole allocation method, and it is applied to an urban domestic water supply system with rising tendency and seasonal cycle fluctuation. To achieve this goal, first a multiplicative model is used to describe the urban domestic water demand. Then, a capital stock and a labor stock are selected as the state vector, and the investment and labor are designed as the control vector. Next, the compensator subsystem is devised in light of the internal model principle. Finally, by using the state feedback control strategy and pole allocation method, the multivariable robust economic control decision method is implemented. The implementation with this model can accomplish the urban domestic water supply control goal, with the robustness for the variation of parameters. The methodology presented in this study may be applied to the water management system in other parts of the world, provided all data used in this study are available. The robust control decision method in this paper is also applicable to deal with tracking control problems as well as stabilization control problems of other general dynamic uncertain systems.

  3. Adaptive robust PID controller design based on a sliding mode for uncertain chaotic systems

    International Nuclear Information System (INIS)

    Chang Weider; Yan Junjuh

    2005-01-01

    A robust adaptive PID controller design motivated from the sliding mode control is proposed for a class of uncertain chaotic systems in this paper. Three PID control gains, K p , K i , and K d , are adjustable parameters and will be updated online with an adequate adaptation mechanism to minimize a previously designed sliding condition. By introducing a supervisory controller, the stability of the closed-loop PID control system under with the plant uncertainty and external disturbance can be guaranteed. Finally, a well-known Duffing-Holmes chaotic system is used as an illustrative to show the effectiveness of the proposed robust adaptive PID controller

  4. 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

  5. Wind turbine inverter robust loop-shaping control subject to grid interaction effects

    DEFF Research Database (Denmark)

    Gryning, Mikkel Peter Sidoroff; Wu, Qiuwei; Blanke, Mogens

    2015-01-01

    the grid and the number of wind turbines connected. Power converter based turbines inject harmonic currents, which are attenuated by passive filters. A robust high order active filter controller is proposed to complement the passive filtering. The H∞ design of the control loop enables desired tracking......An H∞ robust control of wind turbine inverters employing an LCL filter is proposed in this paper. The controller dynamics are designed for selective harmonic filtering in an offshore transmission network subject to parameter perturbations. Parameter uncertainty in the network originates from...

  6. Adaptive observer based synchronization of a class of uncertain chaotic systems

    International Nuclear Information System (INIS)

    Bowong, S.; Yamapi, R.

    2005-05-01

    This study addresses the adaptive synchronization of a class of uncertain chaotic systems in the drive-response framework. For a class of uncertain chaotic systems with unknown parameters and external disturbances, a robust adaptive observer based response system is constructed to synchronize the uncertain chaotic system. Lyapunov stability theory and Barbalat lemma ensure 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 the Genesio-Tesi system verifies the effectiveness of the proposed method. (author)

  7. Robustness of third family solutions for hybrid stars against mixed phase effects

    Science.gov (United States)

    Ayriyan, A.; Bastian, N.-U.; Blaschke, D.; Grigorian, H.; Maslov, K.; Voskresensky, D. N.

    2018-04-01

    We investigate the robustness of third family solutions for hybrid compact stars with a quark matter core that correspond to the occurrence of high-mass twin stars against a softening of the phase transition by means of a construction that mimics the effects of pasta structures in the mixed phase. We consider a class of hybrid equations of state that exploits a relativistic mean-field model for the hadronic as well as for the quark matter phase. We present parametrizations that correspond to branches of high-mass twin star pairs with maximum masses between 2.05 M⊙ and 1.48 M⊙ having radius differences between 3.2 and 1.5 km, respectively. When compared to a Maxwell construction with a fixed value of critical pressure Pc, the effect of the mixed phase construction consists in the occurrence of a region of pressures around Pc belonging to the coexistence of hadronic and quark matter phases between the onset pressure at PH and the end of the transition at PQ. The maximum broadening which would still allow mass-twin compact stars is found to be (PQ-PH)max≈Pc for all parametrizations within the present class of models. At least the heavier of the neutron stars of the binary merger GW170817 could have been a member of the third family of hybrid stars. We present the example of another class of hybrid star equations of state for which the appearance of the third family branch is not as robust against mixed phase effects as that of the present work.

  8. Robust Satisficing Decision Making for Unmanned Aerial Vehicle Complex Missions under Severe Uncertainty.

    Directory of Open Access Journals (Sweden)

    Xiaoting Ji

    Full Text Available This paper presents a robust satisficing decision-making method for Unmanned Aerial Vehicles (UAVs executing complex missions in an uncertain environment. Motivated by the info-gap decision theory, we formulate this problem as a novel robust satisficing optimization problem, of which the objective is to maximize the robustness while satisfying some desired mission requirements. Specifically, a new info-gap based Markov Decision Process (IMDP is constructed to abstract the uncertain UAV system and specify the complex mission requirements with the Linear Temporal Logic (LTL. A robust satisficing policy is obtained to maximize the robustness to the uncertain IMDP while ensuring a desired probability of satisfying the LTL specifications. To this end, we propose a two-stage robust satisficing solution strategy which consists of the construction of a product IMDP and the generation of a robust satisficing policy. In the first stage, a product IMDP is constructed by combining the IMDP with an automaton representing the LTL specifications. In the second, an algorithm based on robust dynamic programming is proposed to generate a robust satisficing policy, while an associated robustness evaluation algorithm is presented to evaluate the robustness. Finally, through Monte Carlo simulation, the effectiveness of our algorithms is demonstrated on an UAV search mission under severe uncertainty so that the resulting policy can maximize the robustness while reaching the desired performance level. Furthermore, by comparing the proposed method with other robust decision-making methods, it can be concluded that our policy can tolerate higher uncertainty so that the desired performance level can be guaranteed, which indicates that the proposed method is much more effective in real applications.

  9. Defining robustness protocols: a method to include and evaluate robustness in clinical plans

    International Nuclear Information System (INIS)

    McGowan, S E; Albertini, F; Lomax, A J; Thomas, S J

    2015-01-01

    We aim to define a site-specific robustness protocol to be used during the clinical plan evaluation process. Plan robustness of 16 skull base IMPT plans to systematic range and random set-up errors have been retrospectively and systematically analysed. This was determined by calculating the error-bar dose distribution (ebDD) for all the plans and by defining some metrics used to define protocols aiding the plan assessment. Additionally, an example of how to clinically use the defined robustness database is given whereby a plan with sub-optimal brainstem robustness was identified. The advantage of using different beam arrangements to improve the plan robustness was analysed. Using the ebDD it was found range errors had a smaller effect on dose distribution than the corresponding set-up error in a single fraction, and that organs at risk were most robust to the range errors, whereas the target was more robust to set-up errors. A database was created to aid planners in terms of plan robustness aims in these volumes. This resulted in the definition of site-specific robustness protocols. The use of robustness constraints allowed for the identification of a specific patient that may have benefited from a treatment of greater individuality. A new beam arrangement showed to be preferential when balancing conformality and robustness for this case. The ebDD and error-bar volume histogram proved effective in analysing plan robustness. The process of retrospective analysis could be used to establish site-specific robustness planning protocols in proton therapy. These protocols allow the planner to determine plans that, although delivering a dosimetrically adequate dose distribution, have resulted in sub-optimal robustness to these uncertainties. For these cases the use of different beam start conditions may improve the plan robustness to set-up and range uncertainties. (paper)

  10. Defining robustness protocols: a method to include and evaluate robustness in clinical plans

    Science.gov (United States)

    McGowan, S. E.; Albertini, F.; Thomas, S. J.; Lomax, A. J.

    2015-04-01

    We aim to define a site-specific robustness protocol to be used during the clinical plan evaluation process. Plan robustness of 16 skull base IMPT plans to systematic range and random set-up errors have been retrospectively and systematically analysed. This was determined by calculating the error-bar dose distribution (ebDD) for all the plans and by defining some metrics used to define protocols aiding the plan assessment. Additionally, an example of how to clinically use the defined robustness database is given whereby a plan with sub-optimal brainstem robustness was identified. The advantage of using different beam arrangements to improve the plan robustness was analysed. Using the ebDD it was found range errors had a smaller effect on dose distribution than the corresponding set-up error in a single fraction, and that organs at risk were most robust to the range errors, whereas the target was more robust to set-up errors. A database was created to aid planners in terms of plan robustness aims in these volumes. This resulted in the definition of site-specific robustness protocols. The use of robustness constraints allowed for the identification of a specific patient that may have benefited from a treatment of greater individuality. A new beam arrangement showed to be preferential when balancing conformality and robustness for this case. The ebDD and error-bar volume histogram proved effective in analysing plan robustness. The process of retrospective analysis could be used to establish site-specific robustness planning protocols in proton therapy. These protocols allow the planner to determine plans that, although delivering a dosimetrically adequate dose distribution, have resulted in sub-optimal robustness to these uncertainties. For these cases the use of different beam start conditions may improve the plan robustness to set-up and range uncertainties.

  11. Robust Adaptive Speed Control of Induction Motor Drives

    DEFF Research Database (Denmark)

    Bidstrup, N.

    This thesis concerns speed control of current vector controlled induction motor drives (CVC drives). The CVC drive is an existing prototype drive developed by Danfoss A/S, Transmission Division. Practical tests have revealed that the open loop dynamical properties of the CVC drive are highly......, (LS) identification and generalized predictive control (GPC) has been implemented and tested on the CVC drive. Allthough GPC is a robust control method, it was not possible to maintain specified controller performance in the entire operating range. This was the main reason for investigating truly...... and measurement noise in general, were the major reasons for the drifting parameters. Two approaches was proposed to robustify MASTR2 against the output noise. The first approach consists of filtering the output. Output filtering had a significant effect in simulations, but the robustness against the output noise...

  12. Nonrobustness of the Carryover Effects of Small Classes in Project STAR

    Science.gov (United States)

    Sohn, Kitae

    2015-01-01

    Background: Class size reduction (CSR) is an enduring school reform undertaken in an effort to improve academic achievement and has been widely encouraged in the United States. Supporters of CSR often cite the positive contemporaneous and carryover effects of Project STAR. Much has been discussed regarding the robustness of the contemporaneous…

  13. Robust synchronization of unified chaotic systems via sliding mode control

    International Nuclear Information System (INIS)

    Yan Junjuh; Yang Yisung; Chiang Tsungying; Chen Chingyuan

    2007-01-01

    This paper investigates the chaos synchronization problem for a class of uncertain master-slave unified chaotic systems. Based on the sliding mode control technique, a robust control scheme is established which guarantees the occurrence of a sliding motion of error states even when the parameter uncertainty and external perturbation are present. Furthermore, a novel proportional-integral (PI) switching surface is introduced for determining the synchronization performance of systems in the sliding mode motion. Simulation results are proposed to demonstrate the effectiveness of the method

  14. Optimal and robust control of a class of nonlinear systems using dynamically re-optimised single network adaptive critic design

    Science.gov (United States)

    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.

  15. Signaling mechanisms underlying the robustness and tunability of the plant immune network

    Science.gov (United States)

    Kim, Yungil; Tsuda, Kenichi; Igarashi, Daisuke; Hillmer, Rachel A.; Sakakibara, Hitoshi; Myers, Chad L.; Katagiri, Fumiaki

    2014-01-01

    Summary How does robust and tunable behavior emerge in a complex biological network? We sought to understand this for the signaling network controlling pattern-triggered immunity (PTI) in Arabidopsis. A dynamic network model containing four major signaling sectors, the jasmonate, ethylene, PAD4, and salicylate sectors, which together explain up to 80% of the PTI level, was built using data for dynamic sector activities and PTI levels under exhaustive combinatorial sector perturbations. Our regularized multiple regression model had a high level of predictive power and captured known and unexpected signal flows in the network. The sole inhibitory sector in the model, the ethylene sector, was central to the network robustness via its inhibition of the jasmonate sector. The model's multiple input sites linked specific signal input patterns varying in strength and timing to different network response patterns, indicating a mechanism enabling tunability. PMID:24439900

  16. Neural robust stabilization via event-triggering mechanism and adaptive learning technique.

    Science.gov (United States)

    Wang, Ding; Liu, Derong

    2018-06-01

    The robust control synthesis of continuous-time nonlinear systems with uncertain term is investigated via event-triggering mechanism and adaptive critic learning technique. We mainly focus on combining the event-triggering mechanism with adaptive critic designs, so as to solve the nonlinear robust control problem. This can not only make better use of computation and communication resources, but also conduct controller design from the view of intelligent optimization. Through theoretical analysis, the nonlinear robust stabilization can be achieved by obtaining an event-triggered optimal control law of the nominal system with a newly defined cost function and a certain triggering condition. The adaptive critic technique is employed to facilitate the event-triggered control design, where a neural network is introduced as an approximator of the learning phase. The performance of the event-triggered robust control scheme is validated via simulation studies and comparisons. The present method extends the application domain of both event-triggered control and adaptive critic control to nonlinear systems possessing dynamical uncertainties. Copyright © 2018 Elsevier Ltd. All rights reserved.

  17. Robust Temperature Control of a Thermoelectric Cooler via μ -Synthesis

    Science.gov (United States)

    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.

  18. The Robust Control Mixer Method for Reconfigurable Control Design By Using Model Matching Strategy

    DEFF Research Database (Denmark)

    Yang, Z.; Blanke, Mogens; Verhagen, M.

    2001-01-01

    This paper proposes a robust reconfigurable control synthesis method based on the combination of the control mixer method and robust H1 con- trol techniques through the model-matching strategy. The control mixer modules are extended from the conventional matrix-form into the LTI sys- tem form....... By regarding the nominal control system as the desired model, an augmented control system is constructed through the model-matching formulation, such that the current robust control techniques can be usedto synthesize these dynamical modules. One extension of this method with respect to the performance...... recovery besides the functionality recovery is also discussed under this framework. Comparing with the conventional control mixer method, the proposed method considers the recon gured system's stability, performance and robustness simultaneously. Finally, the proposed method is illustrated by a case study...

  19. z-CLASSES IN FINITE GROUPS OF CONJUGATE TYPE (n,1) 1 ...

    Indian Academy of Sciences (India)

    37

    Following this motivation to use the z-classes to classify. “dynamical types” of transformations, the z-classes of real hyperbolic isometries have been classified and counted by Gongopadhyay and Kulkarni [GK09]. Apart from geometric motivations, the z-classes are important objects in their own right. Characterizations of the ...

  20. 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.

  1. Robust multi-model control of an autonomous wind power system

    Energy Technology Data Exchange (ETDEWEB)

    Cutululis, Nicolas Antonio; Hansen, Anca Daniela; Soerensen, Poul [Risoe National Lab., Wind Energy Dept., Roskilde (Denmark); Ceanga, Emil [' Dunarea de Jos' Univ., Faculty of Electrical Engineering, Galati (Romania)

    2006-07-01

    This article presents a robust multi-model control structure for a wind power system that uses a variable speed wind turbine (VSWT) driving a permanent magnet synchronous generator (PMSG) connected to a local grid. The control problem consists in maximizing the energy captured from the wind for varying wind speeds. The VSWT-PMSG linearized model analysis reveals the resonant nature of its dynamic at points on the optimal regimes characteristic (ORC). The natural frequency of the system and the damping factor are strongly dependent on the operating point on the ORC. Under these circumstances a robust multi-model control structure is designed. The simulation results prove the viability of the proposed control structure. (Author)

  2. Robust multi-model control of an autonomous wind power system

    Science.gov (United States)

    Cutululis, Nicolas Antonio; Ceanga, Emil; Hansen, Anca Daniela; Sørensen, Poul

    2006-09-01

    This article presents a robust multi-model control structure for a wind power system that uses a variable speed wind turbine (VSWT) driving a permanent magnet synchronous generator (PMSG) connected to a local grid. The control problem consists in maximizing the energy captured from the wind for varying wind speeds. The VSWT-PMSG linearized model analysis reveals the resonant nature of its dynamic at points on the optimal regimes characteristic (ORC). The natural frequency of the system and the damping factor are strongly dependent on the operating point on the ORC. Under these circumstances a robust multi-model control structure is designed. The simulation results prove the viability of the proposed control structure. Copyright

  3. SparCLeS: dynamic l₁ sparse classifiers with level sets for robust beard/moustache detection and segmentation.

    Science.gov (United States)

    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.

  4. Methods for robustness programming

    NARCIS (Netherlands)

    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

  5. Integrating Globality and Locality for Robust Representation Based Classification

    Directory of Open Access Journals (Sweden)

    Zheng Zhang

    2014-01-01

    Full Text Available The representation based classification method (RBCM has shown huge potential for face recognition since it first emerged. Linear regression classification (LRC method and collaborative representation classification (CRC method are two well-known RBCMs. LRC and CRC exploit training samples of each class and all the training samples to represent the testing sample, respectively, and subsequently conduct classification on the basis of the representation residual. LRC method can be viewed as a “locality representation” method because it just uses the training samples of each class to represent the testing sample and it cannot embody the effectiveness of the “globality representation.” On the contrary, it seems that CRC method cannot own the benefit of locality of the general RBCM. Thus we propose to integrate CRC and LRC to perform more robust representation based classification. The experimental results on benchmark face databases substantially demonstrate that the proposed method achieves high classification accuracy.

  6. Robust Solvers for Symmetric Positive Definite Operators and Weighted Poincaré Inequalities

    KAUST Repository

    Efendiev, Yalchin

    2012-01-01

    An abstract setting for robustly preconditioning symmetric positive definite (SPD) operators is presented. The term "robust" refers to the property of the condition numbers of the preconditioned systems being independent of mesh parameters and problem parameters. Important instances of such problem parameters are in particular (highly varying) coefficients. The method belongs to the class of additive Schwarz preconditioners. The paper gives an overview of the results obtained in a recent paper by the authors. It, furthermore, focuses on the importance of weighted Poincaré inequalities, whose notion is extended to general SPD operators, for the analysis of stable decompositions. To demonstrate the applicability of the abstract preconditioner the scalar elliptic equation and the stream function formulation of Brinkman\\'s equations in two spatial dimensions are considered. Several numerical examples are presented. © 2012 Springer-Verlag.

  7. Molecular dynamics-assisted pharmacophore modeling of caspase-3-isatin sulfonamide complex: Recognizing essential intermolecular contacts and features of sulfonamide inhibitor class for caspase-3 binding.

    Science.gov (United States)

    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.

  8. 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...

  9. Robust control design for the plasma horizontal position control on J-TEXT Tokamak

    International Nuclear Information System (INIS)

    Yu, W.Z.; Chen, Z.P.; Zhuang, G.; Wang, Z.J.

    2013-01-01

    It is extremely important for tokamak to control the plasma position during routine discharge. However, the model of plasma in tokamak usually contains much of the uncertainty, such as structured uncertainties and unmodeled dynamics. Compared with the traditional PID control approach, robust control theory is more suitable to handle this problem. In the paper, we propose a H ∞ robust control scheme to control the horizontal position of plasma during the flat-top phase of discharge on Joint Texas Experimental Tokamak (J-TEXT) tokamak. First, the model of our plant for plasma horizontal position control is obtained from the position equilibrium equations. Then the H ∞ robust control framework is used to synthesize the controller. Based on this, an H ∞ controller is designed to minimize the regulation/tracking error. Finally, a comparison study is conducted between the optimized H ∞ robust controller and the traditional PID controller in simulations. The simulation results of the H ∞ robust controller show a significant improvement of the performance with respect to those obtained with traditional PID controller, which is currently used on our machine

  10. Robustness in laying hens

    NARCIS (Netherlands)

    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

  11. A robust H∞ control-based hierarchical mode transition control system for plug-in hybrid electric vehicle

    Science.gov (United States)

    Yang, Chao; Jiao, Xiaohong; Li, Liang; Zhang, Yuanbo; Chen, Zheng

    2018-01-01

    To realize a fast and smooth operating mode transition process from electric driving mode to engine-on driving mode, this paper presents a novel robust hierarchical mode transition control method for a plug-in hybrid electric bus (PHEB) with pre-transmission parallel hybrid powertrain. Firstly, the mode transition process is divided into five stages to clearly describe the powertrain dynamics. Based on the dynamics models of powertrain and clutch actuating mechanism, a hierarchical control structure including two robust H∞ controllers in both upper layer and lower layer is proposed. In upper layer, the demand clutch torque can be calculated by a robust H∞controller considering the clutch engaging time and the vehicle jerk. While in lower layer a robust tracking controller with L2-gain is designed to perform the accurate position tracking control, especially when the parameters uncertainties and external disturbance occur in the clutch actuating mechanism. Simulation and hardware-in-the-loop (HIL) test are carried out in a traditional driving condition of PHEB. Results show that the proposed hierarchical control approach can obtain the good control performance: mode transition time is greatly reduced with the acceptable jerk. Meanwhile, the designed control system shows the obvious robustness with the uncertain parameters and disturbance. Therefore, the proposed approach may offer a theoretical reference for the actual vehicle controller.

  12. Truly random dynamics generated by autonomous dynamical systems

    Science.gov (United States)

    González, J. A.; Reyes, L. I.

    2001-09-01

    We investigate explicit functions that can produce truly random numbers. We use the analytical properties of the explicit functions to show that a certain class of autonomous dynamical systems can generate random dynamics. This dynamics presents fundamental differences with the known chaotic systems. We present real physical systems that can produce this kind of random time-series. Some applications are discussed.

  13. Robust H∞ Filtering for Uncertain Neutral Stochastic Systems with Markovian Jumping Parameters and Time Delay

    Directory of Open Access Journals (Sweden)

    Yajun Li

    2015-01-01

    Full Text Available This paper deals with the robust H∞ filter design problem for a class of uncertain neutral stochastic systems with Markovian jumping parameters and time delay. Based on the Lyapunov-Krasovskii theory and generalized Finsler Lemma, a delay-dependent stability condition is proposed to ensure not only that the filter error system is robustly stochastically stable but also that a prescribed H∞ performance level is satisfied for all admissible uncertainties. All obtained results are expressed in terms of linear matrix inequalities which can be easily solved by MATLAB LMI toolbox. Numerical examples are given to show that the results obtained are both less conservative and less complicated in computation.

  14. Robust solid polymer electrolyte for conducting IPN actuators

    Science.gov (United States)

    Festin, Nicolas; Maziz, Ali; Plesse, Cédric; Teyssié, Dominique; Chevrot, Claude; Vidal, Frédéric

    2013-10-01

    Interpenetrating polymer networks (IPNs) based on nitrile butadiene rubber (NBR) as first component and poly(ethylene oxide) (PEO) as second component were synthesized and used as a solid polymer electrolyte film in the design of a mechanically robust conducting IPN actuator. IPN mechanical properties and morphologies were mainly investigated by dynamic mechanical analysis and transmission electron microscopy. For 1-ethyl-3-methylimidazolium bis-(trifluoromethylsulfonyl)-imide (EMITFSI) swollen IPNs, conductivity values are close to 1 × 10-3 S cm-1 at 25 ° C. Conducting IPN actuators have been synthesized by chemical polymerization of 3,4-ethylenedioxythiophene (EDOT) within the PEO/NBR IPN. A pseudo-trilayer configuration has been obtained with PEO/NBR IPN sandwiched between two interpenetrated PEDOT electrodes. The robust conducting IPN actuators showed a free strain of 2.4% and a blocking force of 30 mN for a low applied potential of ±2 V.

  15. A New Robust Tracking Control Design for Turbofan Engines: H∞/Leitmann Approach

    Directory of Open Access Journals (Sweden)

    Muxuan Pan

    2017-04-01

    Full Text Available In this paper, a H ∞ /Leitmann approach to the robust tracking control design is presented for an uncertain dynamic system. This new method is developed in the following two steps. Firstly, a tracking dynamic system with simultaneous consideration of parameter uncertainty and noise is modeled based on a linear system and a reference model. Accordingly, a “nominal system” from the tracking system is defined and controlled by a H ∞ control to obtain the asymptotical stability and noise resistance. Secondly, by making use of a Lyapunov function and the norm boundedness, a new robust control with the “Leitmann approach” is designed to cope with the uncertainty. The two controls collaborate with each other to achieve “uniform tracking boundedness” and “uniform ultimate tracking boundedness”. The new approach is then applied to an aircraft turbofan control design, and the numerical simulation results show the prescribed performances of the closed-loop system and the advantage of the developed approach.

  16. Robust model-based analysis of single-particle tracking experiments with Spot-On

    Science.gov (United States)

    Grimm, Jonathan B; Lavis, Luke D

    2018-01-01

    Single-particle tracking (SPT) has become an important method to bridge biochemistry and cell biology since it allows direct observation of protein binding and diffusion dynamics in live cells. However, accurately inferring information from SPT studies is challenging due to biases in both data analysis and experimental design. To address analysis bias, we introduce ‘Spot-On’, an intuitive web-interface. Spot-On implements a kinetic modeling framework that accounts for known biases, including molecules moving out-of-focus, and robustly infers diffusion constants and subpopulations from pooled single-molecule trajectories. To minimize inherent experimental biases, we implement and validate stroboscopic photo-activation SPT (spaSPT), which minimizes motion-blur bias and tracking errors. We validate Spot-On using experimentally realistic simulations and show that Spot-On outperforms other methods. We then apply Spot-On to spaSPT data from live mammalian cells spanning a wide range of nuclear dynamics and demonstrate that Spot-On consistently and robustly infers subpopulation fractions and diffusion constants. PMID:29300163

  17. 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.

  18. Robust flight control using incremental nonlinear dynamic inversion and angular acceleration prediction

    NARCIS (Netherlands)

    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

  19. Human Relations Class. A Syllabus.

    Science.gov (United States)

    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;…

  20. Focused Crawling of the Deep Web Using Service Class Descriptions

    Energy Technology Data Exchange (ETDEWEB)

    Rocco, D; Liu, L; Critchlow, T

    2004-06-21

    Dynamic Web data sources--sometimes known collectively as the Deep Web--increase the utility of the Web by providing intuitive access to data repositories anywhere that Web access is available. Deep Web services provide access to real-time information, like entertainment event listings, or present a Web interface to large databases or other data repositories. Recent studies suggest that the size and growth rate of the dynamic Web greatly exceed that of the static Web, yet dynamic content is often ignored by existing search engine indexers owing to the technical challenges that arise when attempting to search the Deep Web. To address these challenges, we present DynaBot, a service-centric crawler for discovering and clustering Deep Web sources offering dynamic content. DynaBot has three unique characteristics. First, DynaBot utilizes a service class model of the Web implemented through the construction of service class descriptions (SCDs). Second, DynaBot employs a modular, self-tuning system architecture for focused crawling of the DeepWeb using service class descriptions. Third, DynaBot incorporates methods and algorithms for efficient probing of the Deep Web and for discovering and clustering Deep Web sources and services through SCD-based service matching analysis. Our experimental results demonstrate the effectiveness of the service class discovery, probing, and matching algorithms and suggest techniques for efficiently managing service discovery in the face of the immense scale of the Deep Web.

  1. Robust sliding mode control for uncertain servo system using friction observer and recurrent fuzzy neural networks

    International Nuclear Information System (INIS)

    Han, Seong Ik; Jeong, Chan Se; Yang, Soon Yong

    2012-01-01

    A robust positioning control scheme has been developed using friction parameter observer and recurrent fuzzy neural networks based on the sliding mode control. As a dynamic friction model, the LuGre model is adopted for handling friction compensation because it has been known to capture sufficiently the properties of a nonlinear dynamic friction. A developed friction parameter observer has a simple structure and also well estimates friction parameters of the LuGre friction model. In addition, an approximation method for the system uncertainty is developed using recurrent fuzzy neural networks technology to improve the precision positioning degree. Some simulation and experiment provide the verification on the performance of a proposed robust control scheme

  2. Robust sliding mode control for uncertain servo system using friction observer and recurrent fuzzy neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Han, Seong Ik [Pusan National University, Busan (Korea, Republic of); Jeong, Chan Se; Yang, Soon Yong [University of Ulsan, Ulsan (Korea, Republic of)

    2012-04-15

    A robust positioning control scheme has been developed using friction parameter observer and recurrent fuzzy neural networks based on the sliding mode control. As a dynamic friction model, the LuGre model is adopted for handling friction compensation because it has been known to capture sufficiently the properties of a nonlinear dynamic friction. A developed friction parameter observer has a simple structure and also well estimates friction parameters of the LuGre friction model. In addition, an approximation method for the system uncertainty is developed using recurrent fuzzy neural networks technology to improve the precision positioning degree. Some simulation and experiment provide the verification on the performance of a proposed robust control scheme.

  3. RNAi dynamics in Juvenile Fasciola spp. Liver flukes reveals the persistence of gene silencing in vitro.

    Directory of Open Access Journals (Sweden)

    Paul McVeigh

    2014-09-01

    Full Text Available Fasciola spp. liver fluke cause pernicious disease in humans and animals. Whilst current control is unsustainable due to anthelmintic resistance, gene silencing (RNA interference, RNAi has the potential to contribute to functional validation of new therapeutic targets. The susceptibility of juvenile Fasciola hepatica to double stranded (dsRNA-induced RNAi has been reported. To exploit this we probe RNAi dynamics, penetrance and persistence with the aim of building a robust platform for reverse genetics in liver fluke. We describe development of standardised RNAi protocols for a commercially-available liver fluke strain (the US Pacific North West Wild Strain, validated via robust transcriptional silencing of seven virulence genes, with in-depth experimental optimisation of three: cathepsin L (FheCatL and B (FheCatB cysteine proteases, and a σ-class glutathione transferase (FheσGST.Robust transcriptional silencing of targets in both F. hepatica and Fasciola gigantica juveniles is achievable following exposure to long (200-320 nt dsRNAs or 27 nt short interfering (siRNAs. Although juveniles are highly RNAi-susceptible, they display slower transcript and protein knockdown dynamics than those reported previously. Knockdown was detectable following as little as 4h exposure to trigger (target-dependent and in all cases silencing persisted for ≥25 days following long dsRNA exposure. Combinatorial silencing of three targets by mixing multiple long dsRNAs was similarly efficient. Despite profound transcriptional suppression, we found a significant time-lag before the occurrence of protein suppression; FheσGST and FheCatL protein suppression were only detectable after 9 and 21 days, respectively.In spite of marked variation in knockdown dynamics, we find that a transient exposure to long dsRNA or siRNA triggers robust RNAi penetrance and persistence in liver fluke NEJs supporting the development of multiple-throughput phenotypic screens for control

  4. Periodicity of a class of nonlinear fuzzy systems with delays

    International Nuclear Information System (INIS)

    Yu Jiali; Yi Zhang; Zhang Lei

    2009-01-01

    The well known Takagi-Sugeno (T-S) model gives an effective method to combine some simple local systems with their linguistic description to represent complex nonlinear dynamic systems. By using the T-S method, a class of local nonlinear systems having nice dynamic properties can be employed to represent some global complex nonlinear systems. This paper proposes to study the periodicity of a class of global nonlinear fuzzy systems with delays by using T-S method. Conditions for guaranteeing periodicity are derived. Examples are employed to illustrate the theory.

  5. Comprehensive Lipidome-Wide Profiling Reveals Dynamic Changes of Tea Lipids during Manufacturing Process of Black Tea.

    Science.gov (United States)

    Li, Jia; Hua, Jinjie; Zhou, Qinghua; Dong, Chunwang; Wang, Jinjin; Deng, Yuliang; Yuan, Haibo; Jiang, Yongwen

    2017-11-22

    As important biomolecules in Camellia sinensis L., lipids undergo substantial changes during black tea manufacture, which is considered to contribute to tea sensory quality. However, limited by analytical capacity, detailed lipid composition and its dynamic changes during black tea manufacture remain unclear. Herein, we performed tea lipidome profiling using high resolution liquid chromatography coupled to mass spectrometry (LC-MS), which allows simultaneous and robust analysis of 192 individual lipid species in black tea, covering 17 (sub)classes. Furthermore, dynamic changes of tea lipids during black tea manufacture were investigated. Significant alterations of lipid pattern were revealed, involved with chlorophyll degradation, metabolic pathways of glycoglycerolipids, and other extraplastidial membrane lipids. To our knowledge, this report presented most comprehensive coverage of lipid species in black tea. This study provides a global and in-depth metabolic map of tea lipidome during black tea manufacture.

  6. Class Energy Image Analysis for Video Sensor-Based Gait Recognition: A Review

    Directory of Open Access Journals (Sweden)

    Zhuowen Lv

    2015-01-01

    Full Text Available Gait is a unique perceptible biometric feature at larger distances, and the gait representation approach plays a key role in a video sensor-based gait recognition system. Class Energy Image is one of the most important gait representation methods based on appearance, which has received lots of attentions. In this paper, we reviewed the expressions and meanings of various Class Energy Image approaches, and analyzed the information in the Class Energy Images. Furthermore, the effectiveness and robustness of these approaches were compared on the benchmark gait databases. We outlined the research challenges and provided promising future directions for the field. To the best of our knowledge, this is the first review that focuses on Class Energy Image. It can provide a useful reference in the literature of video sensor-based gait representation approach.

  7. A new look at the robust control of discrete-time Markov jump linear systems

    Science.gov (United States)

    Todorov, M. G.; Fragoso, M. D.

    2016-03-01

    In this paper, we make a foray in the role played by a set of four operators on the study of robust H2 and mixed H2/H∞ control problems for discrete-time Markov jump linear systems. These operators appear in the study of mean square stability for this class of systems. By means of new linear matrix inequality (LMI) characterisations of controllers, which include slack variables that, to some extent, separate the robustness and performance objectives, we introduce four alternative approaches to the design of controllers which are robustly stabilising and at the same time provide a guaranteed level of H2 performance. Since each operator provides a different degree of conservatism, the results are unified in the form of an iterative LMI technique for designing robust H2 controllers, whose convergence is attained in a finite number of steps. The method yields a new way of computing mixed H2/H∞ controllers, whose conservatism decreases with iteration. Two numerical examples illustrate the applicability of the proposed results for the control of a small unmanned aerial vehicle, and for an underactuated robotic arm.

  8. Robust set-point regulation for ecological models with multiple management goals.

    Science.gov (United States)

    Guiver, Chris; Mueller, Markus; Hodgson, Dave; Townley, Stuart

    2016-05-01

    Population managers will often have to deal with problems of meeting multiple goals, for example, keeping at specific levels both the total population and population abundances in given stage-classes of a stratified population. In control engineering, such set-point regulation problems are commonly tackled using multi-input, multi-output proportional and integral (PI) feedback controllers. Building on our recent results for population management with single goals, we develop a PI control approach in a context of multi-objective population management. We show that robust set-point regulation is achieved by using a modified PI controller with saturation and anti-windup elements, both described in the paper, and illustrate the theory with examples. Our results apply more generally to linear control systems with positive state variables, including a class of infinite-dimensional systems, and thus have broader appeal.

  9. Robust motion control of oscillatory-base manipulators h∞-control and sliding-mode-control-based approaches

    CERN Document Server

    Toda, Masayoshi

    2016-01-01

    This book provides readers with alternative robust approaches to control design for an important class of systems characteristically associated with ocean-going vessels and structures. These systems, which include crane vessels, on-board cranes, radar gimbals, and a conductivity temperature and depth winch, are modelled as manipulators with oscillating bases. One design approach is based on the H-infinity control framework exploiting an effective combination of PD control, an extended matrix polytope and a robust stability analysis method with a state-dependent coefficient form. The other is based on sliding-mode control using some novel nonlinear sliding surfaces. The model demonstrates how successful motion control can be achieved by suppressing base oscillations and in the presence of uncertainties. This is important not only for ocean engineering systems in which the problems addressed here originate but more generally as a benchmark platform for robust motion control with disturbance rejection. Researche...

  10. A new robust adaptive controller for vibration control of active engine mount subjected to large uncertainties

    International Nuclear Information System (INIS)

    Fakhari, Vahid; Choi, Seung-Bok; Cho, Chang-Hyun

    2015-01-01

    This work presents a new robust model reference adaptive control (MRAC) for vibration control caused from vehicle engine using an electromagnetic type of active engine mount. Vibration isolation performances of the active mount associated with the robust controller are evaluated in the presence of large uncertainties. As a first step, an active mount with linear solenoid actuator is prepared and its dynamic model is identified via experimental test. Subsequently, a new robust MRAC based on the gradient method with σ-modification is designed by selecting a proper reference model. In designing the robust adaptive control, structured (parametric) uncertainties in the stiffness of the passive part of the mount and in damping ratio of the active part of the mount are considered to investigate the robustness of the proposed controller. Experimental and simulation results are presented to evaluate performance focusing on the robustness behavior of the controller in the face of large uncertainties. The obtained results show that the proposed controller can sufficiently provide the robust vibration control performance even in the presence of large uncertainties showing an effective vibration isolation. (paper)

  11. Robust anti-windup control for marine cyber-physical systems

    Directory of Open Access Journals (Sweden)

    Kakanov Mikhail

    2018-01-01

    Full Text Available In this paper the robust output control with anti-windup compensation and its implementation to the robotic boat are addressed. The detailed control design and stability analysis of the closed-loop systems are provided in the work. Extensive experimental verification of the dynamic positioning system based on various modifications of the basic controller is carried out by means of robotic boat. The corresponding experimental results are presented and analysed.

  12. Robust sampled-data control of hydraulic flight control actuators

    OpenAIRE

    Kliffken, Markus Gustav

    1997-01-01

    In todays flight-by-wire systems the primary flight control surfaces of modern commercial and transport aircraft are driven by electro hydraulic linear actuators. Changing flight conditions as well as nonlinear actuator dynamics may be interpreted as parameter uncertainties of the linear actuator model. This demands a robust design for the controller. Here the parameter space design is used for the direct sampled-data controller synthesis. Therefore, a static output controller is choosen, the...

  13. Birds achieve high robustness in uneven terrain through active control of landing conditions.

    Science.gov (United States)

    Birn-Jeffery, Aleksandra V; Daley, Monica A

    2012-06-15

    We understand little about how animals adjust locomotor behaviour to negotiate uneven terrain. The mechanical demands and constraints of such behaviours likely differ from uniform terrain locomotion. Here we investigated how common pheasants negotiate visible obstacles with heights from 10 to 50% of leg length. Our goal was to determine the neuro-mechanical strategies used to achieve robust stability, and address whether strategies vary with obstacle height. We found that control of landing conditions was crucial for minimising fluctuations in stance leg loading and work in uneven terrain. Variation in touchdown leg angle (θ(TD)) was correlated with the orientation of ground force during stance, and the angle between the leg and body velocity vector at touchdown (β(TD)) was correlated with net limb work. Pheasants actively targeted obstacles to control body velocity and leg posture at touchdown to achieve nearly steady dynamics on the obstacle step. In the approach step to an obstacle, the birds produced net positive limb work to launch themselves upward. On the obstacle, body dynamics were similar to uniform terrain. Pheasants also increased swing leg retraction velocity during obstacle negotiation, which we suggest is an active strategy to minimise fluctuations in peak force and leg posture in uneven terrain. Thus, pheasants appear to achieve robustly stable locomotion through a combination of path planning using visual feedback and active adjustment of leg swing dynamics to control landing conditions. We suggest that strategies for robust stability are context specific, depending on the quality of sensory feedback available, especially visual input.

  14. Learning Wellness: A Water Exercise Class in Zagreb, Croatia

    Science.gov (United States)

    Roberson, Donald N., Jr.

    2007-01-01

    The research reported in this article investigated the dynamics of a water exercise class with older adults in Zagreb, Croatia. It focused on 3 classes of older swimmers at a community exercise center. A total of 105 participants were asked to complete a short questionnaire. The questionnaire contained items on demographics, use of free time, and…

  15. Robust control for constant thrust rendezvous under thrust failure

    Directory of Open Access Journals (Sweden)

    Qi Yongqiang

    2015-04-01

    Full Text Available A robust constant thrust rendezvous approach under thrust failure is proposed based on the relative motion dynamic model. Firstly, the design problem is cast into a convex optimization problem by introducing a Lyapunov function subject to linear matrix inequalities. Secondly, the robust controllers satisfying the requirements can be designed by solving this optimization problem. Then, a new algorithm of constant thrust fitting is proposed through the impulse compensation and the fuel consumption under the theoretical continuous thrust and the actual constant thrust is calculated and compared by using the method proposed in this paper. Finally, the proposed method having the advantage of saving fuel is proved and the actual constant thrust switch control laws are obtained through the isochronous interpolation method, meanwhile, an illustrative example is provided to show the effectiveness of the proposed control design method.

  16. Microgrid Stability Controller Based on Adaptive Robust Total SMC

    DEFF Research Database (Denmark)

    Su, Xiaoling; Han, Minxiao; Guerrero, Josep M.

    2015-01-01

    This paper presents a microgrid stability controller (MSC) in order to provide existing DGs the additional functionality of working in islanding mode without changing their control strategies in grid-connected mode and to enhance the stability of the microgrid. Microgrid operating characteristics....... The MSC provides fast dynamic response and robustness to the microgrid. When the system is operating in grid-connected mode, it is able to improve the controllability of the exchanged power between the microgrid and the utility grid, while smoothing DG’s output power. When the microgrid is operating...... and mathematical models of the MSC indicate that the system is inherently nonlinear and time-variable. Therefore, this paper proposes an adaptive robust total sliding-mode control (ARTSMC) system for the MSC. It is proved that the ARTSMC system is insensitive to parametric uncertainties and external disturbances...

  17. Robust chaotic control of Lorenz system by backstepping design

    International Nuclear Information System (INIS)

    Peng, C.-C.; Chen, C.-L.

    2008-01-01

    This work presents a robust chaotic control strategy for the Lorenz chaos via backstepping design. Backstepping technique is a systematic tool of control law design to provide Lyapunov stability. The concept of extended system is used such that a continuous sliding mode control (SMC) effort is generated using backstepping scheme. In the proposed control algorithm, an adaptation law is applied to estimate the system parameter and the SMC offers the robustness to model uncertainties and external disturbances so that the asymptotical convergence of tracking error can be achieved. Regarding the SMC, an equivalent control algorithm is chosen based on the selection of Lyapunov stability criterion during backstepping approach. The converging rate of error state is relative to the corresponding dynamics of sliding surface. Numerical simulations demonstrate its advantages to a regulation problem and an orbit tracking problem of the Lorenz chaos

  18. A new robust control for minirotorcraft unmanned aerial vehicles.

    Science.gov (United States)

    Mokhtari, M Rida; Cherki, Brahim

    2015-05-01

    This paper presents a new robust control based on finite-time Lyapunov stability controller and proved with backstepping method for the position and the attitude of a small rotorcraft unmanned aerial vehicle subjected to bounded uncertainties and disturbances. The dynamical motion equations are obtained by the Newton-Euler formalism. The proposed controller combines the advantage of the backstepping approach with finite-time convergence techniques to generate a control laws to guarantee the faster convergence of the state variables to their desired values in short time and compensate for the bounded disturbances. A formal proof of the closed-loop stability and finite-time convergence of tracking errors is derived using the Lyapunov function technique. Simulation results are presented to corroborate the effectiveness and the robustness of the proposed control method. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

  19. A Class of Generalized Gough-Stewart Platforms Used for Effectively Obtaining Dynamic Isotropy – An Analytical Study

    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.

  20. Kilowatt-Class Fission Power Systems for Science and Human Precursor Missions

    Science.gov (United States)

    Mason, Lee S.; Gibson, Marc Andrew; Poston, Dave

    2013-01-01

    Nuclear power provides an enabling capability for NASA missions that might otherwise be constrained by power availability, mission duration, or operational robustness. NASA and the Department of Energy (DOE) are developing fission power technology to serve a wide range of future space uses. Advantages include lower mass, longer life, and greater mission flexibility than competing power system options. Kilowatt-class fission systems, designated "Kilopower," were conceived to address the need for systems to fill the gap above the current 100-W-class radioisotope power systems being developed for science missions and below the typical 100-k We-class reactor power systems being developed for human exploration missions. This paper reviews the current fission technology project and examines some Kilopower concepts that could be used to support future science missions or human precursors.

  1. A New Fast Nonsingular Terminal Sliding Mode Control for a Class of Second-Order Uncertain Systems

    Directory of Open Access Journals (Sweden)

    Linjie Xin

    2016-01-01

    Full Text Available This paper considers the robust and adaptive nonsingular terminal sliding mode (NTSM control for a class of second-order uncertain systems. First, a new fast NTSM was proposed which had global fast convergence rate in the sliding phase. Then, a new form of robust NTSM controller was designed to handle a wider class of second-order uncertain systems. Moreover, an exponential-decline switching gain was introduced for chattering suppression. After that, a double sliding surfaces control scheme was constructed to combine the NTSM control with the adaptive technique. The benefit is that a strict demonstration can be given for the stagnation problem in the stability analysis of NTSM. Finally, a case study for tracking control of a variable-length pendulum was performed to verify the proposed controllers.

  2. Robust Growth Determinants

    OpenAIRE

    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 ...

  3. Effects of traffic generation patterns on the robustness of complex networks

    Science.gov (United States)

    Wu, Jiajing; Zeng, Junwen; Chen, Zhenhao; Tse, Chi K.; Chen, Bokui

    2018-02-01

    Cascading failures in communication networks with heterogeneous node functions are studied in this paper. In such networks, the traffic dynamics are highly dependent on the traffic generation patterns which are in turn determined by the locations of the hosts. The data-packet traffic model is applied to Barabási-Albert scale-free networks to study the cascading failures in such networks and to explore the effects of traffic generation patterns on network robustness. It is found that placing the hosts at high-degree nodes in a network can make the network more robust against both intentional attacks and random failures. It is also shown that the traffic generation pattern plays an important role in network design.

  4. Origins of robustness in translational control via eukaryotic translation initiation factor (eIF) 2.

    Science.gov (United States)

    Khan, Mohammad Farhan; Spurgeon, Sarah; von der Haar, Tobias

    2018-05-14

    Phosphorylation of eukaryotic translation initiation factor 2 (eIF2) is one of the best studied and most widely used means for regulating protein synthesis activity in eukaryotic cells. This pathway regulates protein synthesis in response to stresses, viral infections, and nutrient depletion, among others. We present analyses of an ordinary differential equation-based model of this pathway, which aim to identify its principal robustness-conferring features. Our analyses indicate that robustness is a distributed property, rather than arising from the properties of any one individual pathway species. However, robustness-conferring properties are unevenly distributed between the different species, and we identify a guanine nucleotide dissociation inhibitor (GDI) complex as a species that likely contributes strongly to the robustness of the pathway. Our analyses make further predictions on the dynamic response to different types of kinases that impinge on eIF2. Copyright © 2018 Elsevier Ltd. All rights reserved.

  5. Robust solid polymer electrolyte for conducting IPN actuators

    International Nuclear Information System (INIS)

    Festin, Nicolas; Maziz, Ali; Plesse, Cédric; Teyssié, Dominique; Chevrot, Claude; Vidal, Frédéric

    2013-01-01

    Interpenetrating polymer networks (IPNs) based on nitrile butadiene rubber (NBR) as first component and poly(ethylene oxide) (PEO) as second component were synthesized and used as a solid polymer electrolyte film in the design of a mechanically robust conducting IPN actuator. IPN mechanical properties and morphologies were mainly investigated by dynamic mechanical analysis and transmission electron microscopy. For 1-ethyl-3-methylimidazolium bis-(trifluoromethylsulfonyl)-imide (EMITFSI) swollen IPNs, conductivity values are close to 1 × 10 −3 S cm −1 at 25 ° C. Conducting IPN actuators have been synthesized by chemical polymerization of 3,4-ethylenedioxythiophene (EDOT) within the PEO/NBR IPN. A pseudo-trilayer configuration has been obtained with PEO/NBR IPN sandwiched between two interpenetrated PEDOT electrodes. The robust conducting IPN actuators showed a free strain of 2.4% and a blocking force of 30 mN for a low applied potential of ±2 V. (paper)

  6. Dynamic range of Nef-mediated evasion of HLA class II-restricted immune responses in early HIV-1 infection.

    Science.gov (United States)

    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.

  7. MHC class II tetramers made from isolated recombinant α and β chains refolded with affinity-tagged peptides

    DEFF Research Database (Denmark)

    Braendstrup, Peter; Justesen, Sune Frederik Lamdahl; Osterbye, Thomas

    2013-01-01

    Targeting CD4+ T cells through their unique antigen-specific, MHC class II-restricted T cell receptor makes MHC class II tetramers an attractive strategy to identify, validate and manipulate these cells at the single cell level. Currently, generating class II tetramers is a specialized undertaking...... effectively limiting their use and emphasizing the need for improved methods of production. Using class II chains expressed individually in E. coli as versatile recombinant reagents, we have previously generated peptide-MHC class II monomers, but failed to generate functional class II tetramers. Adding...... a monomer purification principle based upon affinity-tagged peptides, we here provide a robust method to produce class II tetramers and demonstrate staining of antigen-specific CD4+ T cells. We also provide evidence that both MHC class II and T cell receptor molecules largely accept affinity-tagged peptides...

  8. A Modified LQG Algorithm (MLQG for Robust Control of Nonlinear Multivariable Systems

    Directory of Open Access Journals (Sweden)

    Jens G. Balchen

    1993-07-01

    Full Text Available The original LQG algorithm is often characterized for its lack of robustness. This is because in the design of the estimator (Kalman filter the process disturbance is assumed to be white noise. If the estimator is to give good estimates, the Kalman gain is increased which means that the estimator fails to become robust. A solution to this problem is to replace the proportional Kalman gain matrix by a dynamic PI algorithm and the proportional LQ feedback gain matrix by a PI algorithm. A tuning method is developed which facilitates the tuning of a modified LQG control system (MLQG by only two tuning parameters.

  9. 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.

  10. 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

  11. Multivariable Super Twisting Based Robust Trajectory Tracking Control for Small Unmanned Helicopter

    Directory of Open Access Journals (Sweden)

    Xing Fang

    2015-01-01

    Full Text Available This paper presents a highly robust trajectory tracking controller for small unmanned helicopter with model uncertainties and external disturbances. First, a simplified dynamic model is developed, where the model uncertainties and external disturbances are treated as compounded disturbances. Then the system is divided into three interconnected subsystems: altitude subsystem, yaw subsystem, and horizontal subsystem. Second, a disturbance observer based controller (DOBC is designed based upon backstepping and multivariable super twisting control algorithm to obtain robust trajectory tracking property. A sliding mode observer works as an estimator of the compounded disturbances. In order to lessen calculative burden, a first-order exact differentiator is employed to estimate the time derivative of the virtual control. Moreover, proof of the stability of the closed-loop system based on Lyapunov method is given. Finally, simulation results are presented to illustrate the effectiveness and robustness of the proposed flight control scheme.

  12. Robust Stabilization of Nonlinear Systems with Uncertain Varying Control Coefficient

    Directory of Open Access Journals (Sweden)

    Zaiyue Yang

    2014-01-01

    Full Text Available This paper investigates the stabilization problem for a class of nonlinear systems, whose control coefficient is uncertain and varies continuously in value and sign. The study emphasizes the development of a robust control that consists of a modified Nussbaum function to tackle the uncertain varying control coefficient. By such a method, the finite-time escape phenomenon has been prevented when the control coefficient is crossing zero and varying its sign. The proposed control guarantees the asymptotic stabilization of the system and boundedness of all closed-loop signals. The control performance is illustrated by a numerical simulation.

  13. Increasing average period lengths by switching of robust chaos maps in finite precision

    Science.gov (United States)

    Nagaraj, N.; Shastry, M. C.; Vaidya, P. G.

    2008-12-01

    Grebogi, Ott and Yorke (Phys. Rev. A 38, 1988) have investigated the effect of finite precision on average period length of chaotic maps. They showed that the average length of periodic orbits (T) of a dynamical system scales as a function of computer precision (ɛ) and the correlation dimension (d) of the chaotic attractor: T ˜ɛ-d/2. In this work, we are concerned with increasing the average period length which is desirable for chaotic cryptography applications. Our experiments reveal that random and chaotic switching of deterministic chaotic dynamical systems yield higher average length of periodic orbits as compared to simple sequential switching or absence of switching. To illustrate the application of switching, a novel generalization of the Logistic map that exhibits Robust Chaos (absence of attracting periodic orbits) is first introduced. We then propose a pseudo-random number generator based on chaotic switching between Robust Chaos maps which is found to successfully pass stringent statistical tests of randomness.

  14. A Data-Driven Frequency-Domain Approach for Robust Controller Design via Convex Optimization

    CERN Document Server

    AUTHOR|(CDS)2092751; Martino, Michele

    The objective of this dissertation is to develop data-driven frequency-domain methods for designing robust controllers through the use of convex optimization algorithms. Many of today's industrial processes are becoming more complex, and modeling accurate physical models for these plants using first principles may be impossible. Albeit a model may be available; however, such a model may be too complex to consider for an appropriate controller design. With the increased developments in the computing world, large amounts of measured data can be easily collected and stored for processing purposes. Data can also be collected and used in an on-line fashion. Thus it would be very sensible to make full use of this data for controller design, performance evaluation, and stability analysis. The design methods imposed in this work ensure that the dynamics of a system are captured in an experiment and avoids the problem of unmodeled dynamics associated with parametric models. The devised methods consider robust designs...

  15. Robust Weak Chimeras in Oscillator Networks with Delayed Linear and Quadratic Interactions

    Science.gov (United States)

    Bick, Christian; Sebek, Michael; Kiss, István Z.

    2017-10-01

    We present an approach to generate chimera dynamics (localized frequency synchrony) in oscillator networks with two populations of (at least) two elements using a general method based on a delayed interaction with linear and quadratic terms. The coupling design yields robust chimeras through a phase-model-based design of the delay and the ratio of linear and quadratic components of the interactions. We demonstrate the method in the Brusselator model and experiments with electrochemical oscillators. The technique opens the way to directly bridge chimera dynamics in phase models and real-world oscillator networks.

  16. Robust Control Mixer Method for Reconfigurable Control Design Using Model Matching Strategy

    DEFF Research Database (Denmark)

    Yang, Zhenyu; Blanke, Mogens; Verhagen, Michel

    2007-01-01

    A novel control mixer method for recon¯gurable control designs is developed. The proposed method extends the matrix-form of the conventional control mixer concept into a LTI dynamic system-form. The H_inf control technique is employed for these dynamic module designs after an augmented control...... system is constructed through a model-matching strategy. The stability, performance and robustness of the reconfigured system can be guaranteed when some conditions are satisfied. To illustrate the effectiveness of the proposed method, a robot system subjected to failures is used to demonstrate...

  17. Robustness of structures

    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....

  18. ROBUST ALGORITHMS OF PARAMETRIC ESTIMATION IN SOME STABILIZATION PROBLEMS

    Directory of Open Access Journals (Sweden)

    A.A. Vedyakov

    2016-07-01

    Full Text Available Subject of Research.The tasks of dynamic systems provision in the stable state by means of ensuring of trite solution stability for various dynamic systems in the education regime with the aid of their parameters tuning are considered. Method. The problems are solved by application of ideology of the robust finitely convergent algorithms creation. Main Results. The concepts of parametric algorithmization of stability and steady asymptotic stability are introduced and the results are presented on synthesis of coarsed gradient algorithms solving the proposed tasks for finite number of iterations with the purpose of the posed problems decision. Practical Relevance. The article results may be called for decision of practical stabilization tasks in the process of various engineering constructions and devices operation.

  19. Robust, synergistic regulation of human gene expression using TALE activators.

    Science.gov (United States)

    Maeder, Morgan L; Linder, Samantha J; Reyon, Deepak; Angstman, James F; Fu, Yanfang; Sander, Jeffry D; Joung, J Keith

    2013-03-01

    Artificial activators designed using transcription activator-like effector (TALE) technology have broad utility, but previous studies suggest that these monomeric proteins often exhibit low activities. Here we demonstrate that TALE activators can robustly function individually or in synergistic combinations to increase expression of endogenous human genes over wide dynamic ranges. These findings will encourage applications of TALE activators for research and therapy, and guide design of monomeric TALE-based fusion proteins.

  20. Virtual Class Support at the Virtual Machine Level

    DEFF Research Database (Denmark)

    Nielsen, Anders Bach; Ernst, Erik

    2009-01-01

    This paper describes how virtual classes can be supported in a virtual machine.  Main-stream virtual machines such as the Java Virtual Machine and the .NET platform dominate the world today, and many languages are being executed on these virtual machines even though their embodied design choices...... conflict with the design choices of the virtual machine.  For instance, there is a non-trivial mismatch between the main-stream virtual machines mentioned above and dynamically typed languages.  One language concept that creates an even greater mismatch is virtual classes, in particular because fully...... general support for virtual classes requires generation of new classes at run-time by mixin composition.  Languages like CaesarJ and ObjectTeams can express virtual classes restricted to the subset that does not require run-time generation of classes, because of the restrictions imposed by the Java...

  1. On the Robustness of Hysteretic Second-Order Systems with PID : iISS approach

    NARCIS (Netherlands)

    Ouyang, Ruiyue; Jayawardhana, Bayu; Andrieu, Vincent

    2012-01-01

    In this paper, we study the robustness property of a second-order linear plant controlled by a proportional, integral and derivative (PID) controller with a hysteretic actuator. The hysteretic actuator is modeled by a Duhem model that exhibits clockwise (CW) input-output (I/O) dynamics (such as the

  2. Peri-dynamics

    International Nuclear Information System (INIS)

    Littlewood, D.

    2015-01-01

    Peri-dynamics, a nonlocal extension of continuum mechanics, is a natural framework for capturing constitutive response and modelling pervasive material failure and fracture. Unlike classical approaches incorporating partial derivatives, the peri-dynamic governing equations utilise integral expressions that remain valid in the presence of discontinuities such as cracks. The mathematical theory of peri-dynamics unifies the mechanics of continuous media, cracks, and discrete particles. The result is a consistent framework for capturing a wide range of constitutive responses, including inelasticity, in combination with robust material failure laws. Peri-dynamics has been implemented in a number of computational simulation codes, including the open source code Peridigm and the Sierra/SolidMechanics analysis code at Sandia National Laboratories. (author)

  3. 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.

  4. Quantification of parameter uncertainty for robust control of shape memory alloy bending actuators

    International Nuclear Information System (INIS)

    Crews, John H; McMahan, Jerry A; Smith, Ralph C; Hannen, Jennifer C

    2013-01-01

    In this paper, we employ Bayesian parameter estimation techniques to derive gains for robust control of smart materials. Specifically, we demonstrate the feasibility of utilizing parameter uncertainty estimation provided by Markov chain Monte Carlo (MCMC) methods to determine controller gains for a shape memory alloy bending actuator. We treat the parameters in the equations governing the actuator’s temperature dynamics as uncertain and use the MCMC method to construct the probability densities for these parameters. The densities are then used to derive parameter bounds for robust control algorithms. For illustrative purposes, we construct a sliding mode controller based on the homogenized energy model and experimentally compare its performance to a proportional-integral controller. While sliding mode control is used here, the techniques described in this paper provide a useful starting point for many robust control algorithms. (paper)

  5. Robust coordinated control of a dual-arm space robot

    Science.gov (United States)

    Shi, Lingling; Kayastha, Sharmila; Katupitiya, Jay

    2017-09-01

    Dual-arm space robots are more capable of implementing complex space tasks compared with single arm space robots. However, the dynamic coupling between the arms and the base will have a serious impact on the spacecraft attitude and the hand motion of each arm. Instead of considering one arm as the mission arm and the other as the balance arm, in this work two arms of the space robot perform as mission arms aimed at accomplishing secure capture of a floating target. The paper investigates coordinated control of the base's attitude and the arms' motion in the task space in the presence of system uncertainties. Two types of controllers, i.e. a Sliding Mode Controller (SMC) and a nonlinear Model Predictive Controller (MPC) are verified and compared with a conventional Computed-Torque Controller (CTC) through numerical simulations in terms of control accuracy and system robustness. Both controllers eliminate the need to linearly parameterize the dynamic equations. The MPC has been shown to achieve performance with higher accuracy than CTC and SMC in the absence of system uncertainties under the condition that they consume comparable energy. When the system uncertainties are included, SMC and CTC present advantageous robustness than MPC. Specifically, in a case where system inertia increases, SMC delivers higher accuracy than CTC and costs the least amount of energy.

  6. Robust Switched Predictive Braking Control for Rollover Prevention in Wheeled Vehicles

    Directory of Open Access Journals (Sweden)

    Martín Antonio Rodríguez Licea

    2014-01-01

    Full Text Available The aim of this paper is to propose a differential braking rollover mitigation strategy for wheeled vehicles. The strategy makes use of a polytopic (piecewise linear description of the vehicle and includes translational and rotational dynamics, as well as suspension effects. The braking controller is robust and the system states are predicted to estimate the rollover risk up to a given time horizon. In contrast to existing works, the switched predictive nature of the control allows it to be applied only when risk of rollover is foreseen, interfering a minimum with driver’s actions. The stability of the strategy is analyzed and its robustness is illustrated via numerical simulations using CarSim for a variety of vehicles.

  7. Guidance Preconditioning by an Impulse Sequence for Robust Residual Vibration Suppression

    Directory of Open Access Journals (Sweden)

    I. Antoniadis

    1999-01-01

    Full Text Available In order to suppress residual vibrations, a general method is presented for preconditioning any guidance function prior to its application to a dynamic system, by convolving it with a sequence of impulses. The approach includes first the development of the necessary design specifications for the impulse sequence, so that the robustness properties cover the widest possible variation of the system natural frequencies. Three solution methods are proposed then, with special emphasis in the achievement of the minimum possible duration time of the impulse sequence. Numerical experiments verify the effectiveness of the robustness, not only with respect to variations of the natural frequency, but also with respect to variations of a range of other linear and non-linear variables.

  8. Aspiration dynamics of multi-player games in finite populations.

    Science.gov (United States)

    Du, Jinming; Wu, Bin; Altrock, Philipp M; Wang, Long

    2014-05-06

    On studying strategy update rules in the framework of evolutionary game theory, one can differentiate between imitation processes and aspiration-driven dynamics. In the former case, individuals imitate the strategy of a more successful peer. In the latter case, individuals adjust their strategies based on a comparison of their pay-offs from the evolutionary game to a value they aspire, called the level of aspiration. Unlike imitation processes of pairwise comparison, aspiration-driven updates do not require additional information about the strategic environment and can thus be interpreted as being more spontaneous. Recent work has mainly focused on understanding how aspiration dynamics alter the evolutionary outcome in structured populations. However, the baseline case for understanding strategy selection is the well-mixed population case, which is still lacking sufficient understanding. We explore how aspiration-driven strategy-update dynamics under imperfect rationality influence the average abundance of a strategy in multi-player evolutionary games with two strategies. We analytically derive a condition under which a strategy is more abundant than the other in the weak selection limiting case. This approach has a long-standing history in evolutionary games and is mostly applied for its mathematical approachability. Hence, we also explore strong selection numerically, which shows that our weak selection condition is a robust predictor of the average abundance of a strategy. The condition turns out to differ from that of a wide class of imitation dynamics, as long as the game is not dyadic. Therefore, a strategy favoured under imitation dynamics can be disfavoured under aspiration dynamics. This does not require any population structure, and thus highlights the intrinsic difference between imitation and aspiration dynamics.

  9. A Robust Dynamic Heart-Rate Detection Algorithm Framework During Intense Physical Activities Using Photoplethysmographic Signals

    Directory of Open Access Journals (Sweden)

    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.

  10. Are white evangelical Protestants lower class? A partial test of church-sect theory.

    Science.gov (United States)

    Schwadel, Philip

    2014-07-01

    Testing hypotheses derived from church-sect theory and contemporary research about changes in evangelical Protestants' social status, I use repeated cross-sectional survey data spanning almost four decades to examine changes in the social-class hierarchy of American religious traditions. While there is little change in the social-class position of white evangelical Protestants from the early 1970s to 2010, there is considerable change across birth cohorts. Results from hierarchical age-period-cohort models show: (1) robust, across-cohort declines in social-class differences between white evangelical Protestants and liberal Protestants, affiliates of "other" religions, and the unaffiliated, (2) stability in social-class differences between white evangelical Protestants and moderate, Pentecostal, and nondenominational Protestants, (3) moderate across-cohort growth in social-class differences between white evangelical Protestants and Catholics, and (4) these patterns vary across indicators of social class. The findings in this article provide partial support for church-sect theory as well as other theories of social change that emphasize the pivotal role of generations. Copyright © 2014 Elsevier Inc. All rights reserved.

  11. H pylori receptor MHC class II contributes to the dynamic gastric epithelial apoptotic response

    Science.gov (United States)

    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

  12. Improving boiler unit performance using an optimum robust minimum-order observer

    International Nuclear Information System (INIS)

    Moradi, Hamed; Bakhtiari-Nejad, Firooz

    2011-01-01

    Research highlights: → Multivariable model of a boiler unit with uncertainty. → Design of a robust minimum-order observer. → Developing an optimal functional code in MATLAB environment. → Finding optimum region of observer-based controller poles. → Guarantee of robust performance in the presence of parametric uncertainties. - Abstract: To achieve a good performance of the utility boiler, dynamic variables such as drum pressure, steam temperature and water level of drum must be controlled. In this paper, a linear time invariant (LTI) model of a boiler system is considered in which the input variables are feed-water and fuel mass rates. Due to the inaccessibility of some state variables of boiler system, a minimum-order observer is designed based on Luenberger's model to gain an estimate state x-tilde of the true state x. Low cost of design and high accuracy of states estimation are the main advantages of the minimum-order observer; in comparison with previous designed full-order observers. By applying the observer on the closed-loop system, a regulator system is designed. Using an optimal functional code developed in MATLAB environment, desired observer poles are found such that suitable time response specifications of the boiler system are achieved and the gain and phase margin values are adjusted in an acceptable range. However, the real dynamic model may associate with parametric uncertainties. In that case, optimum region of poles of observer-based controller are found such that the robust performance of the boiler system against model uncertainties is guaranteed.

  13. Robust control of dielectric elastomer diaphragm actuator for human pulse signal tracking

    Science.gov (United States)

    Ye, Zhihang; Chen, Zheng; Asmatulu, Ramazan; Chan, Hoyin

    2017-08-01

    Human pulse signal tracking is an emerging technology that is needed in traditional Chinese medicine. However, soft actuation with multi-frequency tracking capability is needed for tracking human pulse signal. Dielectric elastomer (DE) is one type of soft actuating that has great potential in human pulse signal tracking. In this paper, a DE diaphragm actuator was designed and fabricated to track human pulse pressure signal. A physics-based and control-oriented model has been developed to capture the dynamic behavior of DE diaphragm actuator. Using the physical model, an H-infinity robust control was designed for the actuator to reject high-frequency sensing noises and disturbances. The robust control was then implemented in real-time to track a multi-frequency signal, which verified the tracking capability and robustness of the control system. In the human pulse signal tracking test, a human pulse signal was measured at the City University of Hong Kong and then was tracked using DE actuator at Wichita State University in the US. Experimental results have verified that the DE actuator with its robust control is capable of tracking human pulse signal.

  14. Evaluation of Structural Robustness against Column Loss: Methodology and Application to RC Frame Buildings.

    Science.gov (United States)

    Bao, Yihai; Main, Joseph A; Noh, Sam-Young

    2017-08-01

    A computational methodology is presented for evaluating structural robustness against column loss. The methodology is illustrated through application to reinforced concrete (RC) frame buildings, using a reduced-order modeling approach for three-dimensional RC framing systems that includes the floor slabs. Comparisons with high-fidelity finite-element model results are presented to verify the approach. Pushdown analyses of prototype buildings under column loss scenarios are performed using the reduced-order modeling approach, and an energy-based procedure is employed to account for the dynamic effects associated with sudden column loss. Results obtained using the energy-based approach are found to be in good agreement with results from direct dynamic analysis of sudden column loss. A metric for structural robustness is proposed, calculated by normalizing the ultimate capacities of the structural system under sudden column loss by the applicable service-level gravity loading and by evaluating the minimum value of this normalized ultimate capacity over all column removal scenarios. The procedure is applied to two prototype 10-story RC buildings, one employing intermediate moment frames (IMFs) and the other employing special moment frames (SMFs). The SMF building, with its more stringent seismic design and detailing, is found to have greater robustness.

  15. Nonfragile Robust Model Predictive Control for Uncertain Constrained Systems with Time-Delay Compensation

    Directory of Open Access Journals (Sweden)

    Wei Jiang

    2016-01-01

    Full Text Available This study investigates the problem of asymptotic stabilization for a class of discrete-time linear uncertain time-delayed systems with input constraints. Parametric uncertainty is assumed to be structured, and delay is assumed to be known. In Lyapunov stability theory framework, two synthesis schemes of designing nonfragile robust model predictive control (RMPC with time-delay compensation are put forward, where the additive and the multiplicative gain perturbations are, respectively, considered. First, by designing appropriate Lyapunov-Krasovskii (L-K functions, the robust performance index is defined as optimization problems that minimize upper bounds of infinite horizon cost function. Then, to guarantee closed-loop stability, the sufficient conditions for the existence of desired nonfragile RMPC are obtained in terms of linear matrix inequalities (LMIs. Finally, two numerical examples are provided to illustrate the effectiveness of the proposed approaches.

  16. Transient scenarios for robust climate change adaptation illustrated for water manegement in the Netherlands

    NARCIS (Netherlands)

    Haasnoot, Marjolijn; Schellekens, J.; Beersma, J.; Middelkoop, H.; Kwadijk, Jacob Cornelis Jan

    2015-01-01

    Climate scenarios are used to explore impacts of possible future climates and to assess the robustness of adaptation actions across a range of futures. Time-dependent climate scenarios are commonly used in mitigation studies. However, despite the dynamic nature of adaptation, most scenarios for

  17. Robust Contextual Bandit via the Capped-$\\ell_{2}$ norm

    OpenAIRE

    Zhu, Feiyun; Zhu, Xinliang; Wang, Sheng; Yao, Jiawen; Huang, Junzhou

    2017-01-01

    This paper considers the actor-critic contextual bandit for the mobile health (mHealth) intervention. The state-of-the-art decision-making methods in mHealth generally assume that the noise in the dynamic system follows the Gaussian distribution. Those methods use the least-square-based algorithm to estimate the expected reward, which is prone to the existence of outliers. To deal with the issue of outliers, we propose a novel robust actor-critic contextual bandit method for the mHealth inter...

  18. Managing Student Self-Disclosure in Class Settings: Lessons from Feminist Pedagogy

    Science.gov (United States)

    Borshuk, Catherine

    2017-01-01

    This article describes difficulties and opportunities associated with students' disclosure of their personal experiences in university class settings. In classes that deal with topics such as violence, racism, family dynamics, mental health or social justice, students with first-hand experience of these topics can bring valuable real-life…

  19. Histone Variant HTZ1 Shows Extensive Epistasis with, but Does Not Increase Robustness to, New Mutations

    Science.gov (United States)

    Richardson, Joshua B.; Uppendahl, Locke D.; Traficante, Maria K.; Levy, Sasha F.; Siegal, Mark L.

    2013-01-01

    Biological systems produce phenotypes that appear to be robust to perturbation by mutations and environmental variation. Prior studies identified genes that, when impaired, reveal previously cryptic genetic variation. This result is typically interpreted as evidence that the disrupted gene normally increases robustness to mutations, as such robustness would allow cryptic variants to accumulate. However, revelation of cryptic genetic variation is not necessarily evidence that a mutationally robust state has been made less robust. Demonstrating a difference in robustness requires comparing the ability of each state (with the gene perturbed or intact) to suppress the effects of new mutations. Previous studies used strains in which the existing genetic variation had been filtered by selection. Here, we use mutation accumulation (MA) lines that have experienced minimal selection, to test the ability of histone H2A.Z (HTZ1) to increase robustness to mutations in the yeast Saccharomyces cerevisiae. HTZ1, a regulator of chromatin structure and gene expression, represents a class of genes implicated in mutational robustness. It had previously been shown to increase robustness of yeast cell morphology to fluctuations in the external or internal microenvironment. We measured morphological variation within and among 79 MA lines with and without HTZ1. Analysis of within-line variation confirms that HTZ1 increases microenvironmental robustness. Analysis of between-line variation shows the morphological effects of eliminating HTZ1 to be highly dependent on the line, which implies that HTZ1 interacts with mutations that have accumulated in the lines. However, lines without HTZ1 are, as a group, not more phenotypically diverse than lines with HTZ1 present. The presence of HTZ1, therefore, does not confer greater robustness to mutations than its absence. Our results provide experimental evidence that revelation of cryptic genetic variation cannot be assumed to be caused by loss of

  20. Histone variant HTZ1 shows extensive epistasis with, but does not increase robustness to, new mutations.

    Directory of Open Access Journals (Sweden)

    Joshua B Richardson

    Full Text Available Biological systems produce phenotypes that appear to be robust to perturbation by mutations and environmental variation. Prior studies identified genes that, when impaired, reveal previously cryptic genetic variation. This result is typically interpreted as evidence that the disrupted gene normally increases robustness to mutations, as such robustness would allow cryptic variants to accumulate. However, revelation of cryptic genetic variation is not necessarily evidence that a mutationally robust state has been made less robust. Demonstrating a difference in robustness requires comparing the ability of each state (with the gene perturbed or intact to suppress the effects of new mutations. Previous studies used strains in which the existing genetic variation had been filtered by selection. Here, we use mutation accumulation (MA lines that have experienced minimal selection, to test the ability of histone H2A.Z (HTZ1 to increase robustness to mutations in the yeast Saccharomyces cerevisiae. HTZ1, a regulator of chromatin structure and gene expression, represents a class of genes implicated in mutational robustness. It had previously been shown to increase robustness of yeast cell morphology to fluctuations in the external or internal microenvironment. We measured morphological variation within and among 79 MA lines with and without HTZ1. Analysis of within-line variation confirms that HTZ1 increases microenvironmental robustness. Analysis of between-line variation shows the morphological effects of eliminating HTZ1 to be highly dependent on the line, which implies that HTZ1 interacts with mutations that have accumulated in the lines. However, lines without HTZ1 are, as a group, not more phenotypically diverse than lines with HTZ1 present. The presence of HTZ1, therefore, does not confer greater robustness to mutations than its absence. Our results provide experimental evidence that revelation of cryptic genetic variation cannot be assumed to be

  1. Robust output-feedback control to eliminate stick-slip oscillations in drill-string systems

    NARCIS (Netherlands)

    Vromen, T.G.M.; Dai, C.H.; van de Wouw, N.; Oomen, T.A.E.; Astrid, P.; Nijmeijer, H.

    2015-01-01

    The aim of this paper is to design a robust output-feedback controller to eliminate torsional stick-slip vibrations. A multi-modal model of the torsional dynamics with a nonlinear bit-rock interaction model is used. The controller design is based on skewed-μ DK-iteration and the stability of the

  2. Robust Predictive Functional Control for Flight Vehicles Based on Nonlinear Disturbance Observer

    Directory of Open Access Journals (Sweden)

    Yinhui Zhang

    2015-01-01

    Full Text Available A novel robust predictive functional control based on nonlinear disturbance observer is investigated in order to address the control system design for flight vehicles with significant uncertainties, external disturbances, and measurement noise. Firstly, the nonlinear longitudinal dynamics of the flight vehicle are transformed into linear-like state-space equations with state-dependent coefficient matrices. And then the lumped disturbances are considered in the linear structure predictive model of the predictive functional control to increase the precision of the predictive output and resolve the intractable mismatched disturbance problem. As the lumped disturbances cannot be derived or measured directly, the nonlinear disturbance observer is applied to estimate the lumped disturbances, which are then introduced to the predictive functional control to replace the unknown actual lumped disturbances. Consequently, the robust predictive functional control for the flight vehicle is proposed. Compared with the existing designs, the effectiveness and robustness of the proposed flight control are illustrated and validated in various simulation conditions.

  3. Mediator facilitates transcriptional activation and dynamic long-range contacts at the IgH locus during class switch recombination.

    Science.gov (United States)

    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.

  4. Design and Implement a Digital H{sub {infinity}}Robust Controller for a MW-Class PMSG-Based Grid-Interactive Wind Energy Conversion System

    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.

  5. A robust sound perception model suitable for neuromorphic implementation.

    Science.gov (United States)

    Coath, Martin; Sheik, Sadique; Chicca, Elisabetta; Indiveri, Giacomo; Denham, Susan L; Wennekers, Thomas

    2013-01-01

    We have recently demonstrated the emergence of dynamic feature sensitivity through exposure to formative stimuli in a real-time neuromorphic system implementing a hybrid analog/digital network of spiking neurons. This network, inspired by models of auditory processing in mammals, includes several mutually connected layers with distance-dependent transmission delays and learning in the form of spike timing dependent plasticity, which effects stimulus-driven changes in the network connectivity. Here we present results that demonstrate that the network is robust to a range of variations in the stimulus pattern, such as are found in naturalistic stimuli and neural responses. This robustness is a property critical to the development of realistic, electronic neuromorphic systems. We analyze the variability of the response of the network to "noisy" stimuli which allows us to characterize the acuity in information-theoretic terms. This provides an objective basis for the quantitative comparison of networks, their connectivity patterns, and learning strategies, which can inform future design decisions. We also show, using stimuli derived from speech samples, that the principles are robust to other challenges, such as variable presentation rate, that would have to be met by systems deployed in the real world. Finally we demonstrate the potential applicability of the approach to real sounds.

  6. A Robust Sound Perception Model Suitable for Neuromorphic Implementation

    Directory of Open Access Journals (Sweden)

    Martin eCoath

    2014-01-01

    Full Text Available We have recently demonstrated the emergence of dynamic feature sensitivity through exposure to formative stimuli in a real-time neuromorphic system implementing a hybrid analogue/digital network of spiking neurons. This network, inspired by models of auditory processing in mammals, includes several mutually connected layers with distance-dependent transmission delays and learning in the form of spike timing dependent plasticity, which effects stimulus-driven changes in the network connectivity.Here we present results that demonstrate that the network is robust to a range of variations in the stimulus pattern, such as are found in naturalistic stimuli and neural responses. This robustness is a property critical to the development of realistic, electronic neuromorphic systems.We analyse the variability of the response of the network to `noisy' stimuli which allows us to characterize the acuity in information-theoretic terms. This provides an objective basis for the quantitative comparison of networks, their connectivity patterns, and learning strategies, which can inform future design decisions. We also show, using stimuli derived from speech samples, that the principles are robust to other challenges, such as variable presentation rate, that would have to be met by systems deployed in the real world. Finally we demonstrate the potential applicability of the approach to real sounds.

  7. Robust Monotonically Convergent Iterative Learning Control for Discrete-Time Systems via Generalized KYP Lemma

    Directory of Open Access Journals (Sweden)

    Jian Ding

    2014-01-01

    Full Text Available This paper addresses the problem of P-type iterative learning control for a class of multiple-input multiple-output linear discrete-time systems, whose aim is to develop robust monotonically convergent control law design over a finite frequency range. It is shown that the 2 D iterative learning control processes can be taken as 1 D state space model regardless of relative degree. With the generalized Kalman-Yakubovich-Popov lemma applied, it is feasible to describe the monotonically convergent conditions with the help of linear matrix inequality technique and to develop formulas for the control gain matrices design. An extension to robust control law design against systems with structured and polytopic-type uncertainties is also considered. Two numerical examples are provided to validate the feasibility and effectiveness of the proposed method.

  8. Design of Nonlinear Robust Rotor Current Controller for DFIG Based on Terminal Sliding Mode Control and Extended State Observer

    Directory of Open Access Journals (Sweden)

    Guowei Cai

    2014-01-01

    Full Text Available As to strong nonlinearity of doubly fed induction generators (DFIG and uncertainty of its model, a novel rotor current controller with nonlinearity and robustness is proposed to enhance fault ride-though (FRT capacities of grid-connected DFIG. Firstly, the model error, external disturbances, and the uncertain factors were estimated by constructing extended state observer (ESO so as to achieve linearization model, which is compensated dynamically from nonlinear model. And then rotor current controller of DFIG is designed by using terminal sliding mode variable structure control theory (TSMC. The controller has superior dynamic performance and strong robustness. The simulation results show that the proposed control approach is effective.

  9. Robust Model Predictive Control of a Nonlinear System with Known Scheduling Variable and Uncertain Gain

    DEFF Research Database (Denmark)

    Mirzaei, Mahmood; Poulsen, Niels Kjølstad; Niemann, Hans Henrik

    2012-01-01

    Robust model predictive control (RMPC) of a class of nonlinear systems is considered in this paper. We will use Linear Parameter Varying (LPV) model of the nonlinear system. By taking the advantage of having future values of the scheduling variable, we will simplify state prediction. Because...... of the special structure of the problem, uncertainty is only in the B matrix (gain) of the state space model. Therefore by taking advantage of this structure, we formulate a tractable minimax optimization problem to solve robust model predictive control problem. Wind turbine is chosen as the case study and we...... choose wind speed as the scheduling variable. Wind speed is measurable ahead of the turbine, therefore the scheduling variable is known for the entire prediction horizon....

  10. Dynamical systems

    CERN Document Server

    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

  11. 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.

  12. Robust quasi NID current and flux control of an induction motor for position control

    NARCIS (Netherlands)

    van Duijnhoven, M.; Blachuta, M.J.

    1999-01-01

    In the paper, a new control design method called Dynamic Contraction method is applied to the flux and quadrature current robust control of an induction motor operated using the field orientation principle. The resulting input-output decoupled and linearized drive is then used for time-optimal

  13. Dynamic characterizers of spatiotemporal intermittency

    OpenAIRE

    Gupte, Neelima; Jabeen, Zahera

    2006-01-01

    Systems of coupled sine circle maps show regimes of spatiotemporally intermittent behaviour with associated scaling exponents which belong to the DP class, as well as regimes of spatially intermittent behaviour (with associated regular dynamical behaviour) which do not belong to the DP class. Both types of behaviour are seen along the bifurcation boundaries of the synchronized solutions, and contribute distinct signatures to the dynamical characterizers of the system, viz. the distribution of...

  14. Image Alignment for Multiple Camera High Dynamic Range Microscopy.

    Science.gov (United States)

    Eastwood, Brian S; Childs, Elisabeth C

    2012-01-09

    This paper investigates the problem of image alignment for multiple camera high dynamic range (HDR) imaging. HDR imaging combines information from images taken with different exposure settings. Combining information from multiple cameras requires an alignment process that is robust to the intensity differences in the images. HDR applications that use a limited number of component images require an alignment technique that is robust to large exposure differences. We evaluate the suitability for HDR alignment of three exposure-robust techniques. We conclude that image alignment based on matching feature descriptors extracted from radiant power images from calibrated cameras yields the most accurate and robust solution. We demonstrate the use of this alignment technique in a high dynamic range video microscope that enables live specimen imaging with a greater level of detail than can be captured with a single camera.

  15. Robust adaptive backstepping neural networks control for spacecraft rendezvous and docking with input saturation.

    Science.gov (United States)

    Xia, Kewei; Huo, Wei

    2016-05-01

    This paper presents a robust adaptive neural networks control strategy for spacecraft rendezvous and docking with the coupled position and attitude dynamics under input saturation. Backstepping technique is applied to design a relative attitude controller and a relative position controller, respectively. The dynamics uncertainties are approximated by radial basis function neural networks (RBFNNs). A novel switching controller consists of an adaptive neural networks controller dominating in its active region combined with an extra robust controller to avoid invalidation of the RBFNNs destroying stability of the system outside the neural active region. An auxiliary signal is introduced to compensate the input saturation with anti-windup technique, and a command filter is employed to approximate derivative of the virtual control in the backstepping procedure. Globally uniformly ultimately bounded of the relative states is proved via Lyapunov theory. Simulation example demonstrates effectiveness of the proposed control scheme. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

  16. Robust Fault Detection for Switched Fuzzy Systems With Unknown Input.

    Science.gov (United States)

    Han, Jian; Zhang, Huaguang; Wang, Yingchun; Sun, Xun

    2017-10-03

    This paper investigates the fault detection problem for a class of switched nonlinear systems in the T-S fuzzy framework. The unknown input is considered in the systems. A novel fault detection unknown input observer design method is proposed. Based on the proposed observer, the unknown input can be removed from the fault detection residual. The weighted H∞ performance level is considered to ensure the robustness. In addition, the weighted H₋ performance level is introduced, which can increase the sensibility of the proposed detection method. To verify the proposed scheme, a numerical simulation example and an electromechanical system simulation example are provided at the end of this paper.

  17. Structural robustness with suboptimal responses for linear state space model

    Science.gov (United States)

    Keel, L. H.; Lim, Kyong B.; Juang, Jer-Nan

    1989-01-01

    A relationship between the closed-loop eigenvalues and the amount of perturbations in the open-loop matrix is addressed in the context of performance robustness. If the allowable perturbation ranges of elements of the open-loop matrix A and the desired tolerance of the closed-loop eigenvalues are given such that max(j) of the absolute value of Delta-lambda(j) (A+BF) should be less than some prescribed value, what is a state feedback controller F which satisfies the closed-loop eigenvalue perturbation-tolerance requirement for a class of given perturbation in A? The paper gives an algorithm to design such a controller. Numerical examples are included for illustration.

  18. Robust On-Demand Multipath Routing with Dynamic Path Upgrade for Delay-Sensitive Data over Ad Hoc Networks

    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.

  19. MetrIntSimil—An Accurate and Robust Metric for Comparison of Similarity in Intelligence of Any Number of Cooperative Multiagent Systems

    Directory of Open Access Journals (Sweden)

    Laszlo Barna Iantovics

    2018-02-01

    Full Text Available Intelligent cooperative multiagent systems are applied for solving a large range of real-life problems, including in domains like biology and healthcare. There are very few metrics able to make an effective measure of the machine intelligence quotient. The most important drawbacks of the designed metrics presented in the scientific literature consist in the limitation in universality, accuracy, and robustness. In this paper, we propose a novel universal metric called MetrIntSimil capable of making an accurate and robust symmetric comparison of the similarity in intelligence of any number of cooperative multiagent systems specialized in difficult problem solving. The universality is an important necessary property based on the large variety of designed intelligent systems. MetrIntSimil makes a comparison by taking into consideration the variability in intelligence in the problem solving of the compared cooperative multiagent systems. It allows a classification of the cooperative multiagent systems based on their similarity in intelligence. A cooperative multiagent system has variability in the problem solving intelligence, and it can manifest lower or higher intelligence in different problem solving tasks. More cooperative multiagent systems with similar intelligence can be included in the same class. For the evaluation of the proposed metric, we conducted a case study for more intelligent cooperative multiagent systems composed of simple computing agents applied for solving the Symmetric Travelling Salesman Problem (STSP that is a class of NP-hard problems. STSP is the problem of finding the shortest Hamiltonian cycle/tour in a weighted undirected graph that does not have loops or multiple edges. The distance between two cities is the same in each opposite direction. Two classes of similar intelligence denoted IntClassA and IntClassB were identified. The experimental results show that the agent belonging to IntClassA intelligence class is less

  20. Applications of Functional Amyloids from Fungi: Surface Modification by Class I Hydrophobins

    Directory of Open Access Journals (Sweden)

    Alessandra Piscitelli

    2017-06-01

    Full Text Available Class I hydrophobins produced from fungi are amongst the first proteins recognized as functional amyloids. They are amphiphilic proteins involved in the formation of aerial structures such as spores or fruiting bodies. They form chemically robust layers which can only be dissolved in strong acids. These layers adhere to different surfaces, changing their wettability, and allow the binding of other proteins. Herein, the modification of diverse types of surfaces with Class I hydrophobins is reported, highlighting the applications of the coated surfaces. Indeed, these coatings can be exploited in several fields, spanning from biomedical to industrial applications, which include biosensing and textile manufacturing.