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作者： Mobayen, Saleh Yazdanpanah, Mohammad Javad Majd, Vahid Johari Intelligent Control Systems Lab. School of Electrical and Computer Engineering Tarbiat Modares University Tehran Iran Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Iran

ISBN: (纸本)9781457700804

A novel recursive singularity free FTSM (Fast Terminal Sliding Mode) strategy for finite time tracking control of nonholonomic systems is proposed. As a result, the singularity problem around the origin resulting from the fractional power of conventional terminal sliding mode is resolved. Simulation results are given for two benchmark examples of extended chained-form nonholonomic systems: a wheeled mobile robot and an underactuated surface vessel. The results show the effectiveness of the proposed strategy. © 2011 AACC American Automatic control Council.

关键词： Mobile robots

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Evolution and maintenance of cooperation via inheritance of neighborhood relationship

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Chinese Science Bulletin 2013年第28期58卷 3491-3498页

作者： TAN ShaoLin Lü JinHu YU XingHuo HILL David John The Key Laboratory of System and Control Institute of Systems ScienceAcademy of Mathematics and Systems ScienceChinese Academy of Sciences School of Electrical and Computer Engineering RMIT University Department of Electrical and Electronic Engineering The University of Hong Kong School of Electrical and Information Engineering University of Sydney

Cooperative behaviors are ubiquitous in nature and human *** is very important to understand the internal mechanism of emergence and maintenance of *** we know now,the offsprings inherit not only the phenotype but also the neighborhood relationship of their *** recent research results show that the interactions among individuals facilitate survival of cooperation through network reciprocity of clustering *** paper aims at introducing an inheritance mechanism of neighborhood relationship to explore the evolution of *** detail,a mathematical model is proposed to characterize the evolutionary process with the above inheritance *** analysis and numerical simulations indicate that high-level cooperation can emerge and be maintained for a wide variety of cost-to-benefit ratios,even if mutation happens during the evolving process.

关键词：合作机制邻里关系维护演变进化过程人类社会遗传机制数学模型

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COMPLEXITY ANALYSIS OF NETWORK-BASED DYNAMICAL systems

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Journal of systems Science & Complexity 2011年第3期24卷 413-432页

作者： Guofeng ZHANG Long WANG Tongwen CHEN School of Electronic Engineering University of Electronic Science and Technology of China Chengdu 610054 China. Intelligent Control Laboratory Center for Systems and Control College of Engineering Peking University Beijing 100871 China Department of Electrical and Computer Engineering University of Alberta Edmonton Alberta T6G 2V4 Canada

This paper investigates the nonlinear dynamics of network-based dynamical systems where network communication channels of finite data rates are inserted into the closed loops of the control systems. The authors analyze the bifurcation and chaotic behavior of the non-smooth dynamical systems. The authors first prove that for almost all system parameters there are no periodic orbits. This result distinguishes this type of non-smooth dynamical systems from many others exhibiting border-collision bifurcations. Next, the authors show analytically that the chaotic sets are separated from the region containing the line segment of all fixed points with a finite distance. Finally, the authors employ a simple model to highlight that both the number of clients sharing a common network channel and fluctuations in the available network bandwidth have significant influence on the performance of such dynamical systems.

关键词： Bifurcation feedback network-based dynamical system non-convexity periodicity.

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Asymptotic properties of distributed social sampling algorithm

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Science China(Information Sciences) 2020年第1期63卷 152-166页

作者： Qian LIU Xingkang HE Haitao FANG The Key Laboratory of Systems and Control Academy of Mathematics and Systems ScienceChinese Academy of Sciences School of Mathematical Sciences University of Chinese Academy of Sciences ACCESS Linnaeus Centre School of Electrical Engineering and Computer ScienceKTH Royal Institute of Technology

Social sampling is a novel randomized message passing protocol inspired by social communication for opinion formation in social networks. In a typical social sampling algorithm, each agent holds a sample from the empirical distribution of social opinions at initial time, and it collaborates with other agents in a distributed manner to estimate the initial empirical distribution by randomly sampling a message from current distribution estimate. In this paper, we focus on analyzing the theoretical properties of the distributed social sampling algorithm over random networks. First, we provide a framework based on stochastic approximation to study the asymptotic properties of the algorithm. Then, under mild conditions, we prove that the estimates of all agents converge to a common random distribution, which is composed of the initial empirical distribution and the accumulation of quantized error. Besides, by tuning algorithm parameters, we prove the strong consistency, namely, the distribution estimates of agents almost surely converge to the initial empirical distribution. Furthermore, the asymptotic normality of estimation error generated by distributed social sample algorithm is addressed. Finally, we provide a numerical simulation to validate the theoretical results of this paper.

关键词： social networks opinion formation social sampling stochastic approximation random networks asymptotic normality

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Hierarchical rank density genetic algorithm for radial-basis function neural network design

Hierarchical rank density genetic algorithm for radial-basis...

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2002 Congress on Evolutionary Computation, CEC 2002

作者： Yen, Gary G. Lu, Haiming Intelligent Systems and Control Laboratory School of Electrical and Computer Engineering Oklahoma State University Stillwater OK 74078-5032 United States

ISBN: (纸本)0780372824

In this paper, we propose a genetic algorithm based design procedure for a radial-basis function neural network. A hierarchical rank density genetic algorithm (HRDGA) is used to evolve both the neural network's topology and parameters. In addition, the rank-density based fitness assignment technique is used to optimize the performance and topology of the evolved neural network to deal with the confliction between the training performance and network complexity. Instead of producing a single optimal network, HRDGA provides a set of near-optimal neural networks to the designers or the decision makers so that they can have more flexibility for the final decision-making based on their preferences. In terms of searching for a near-complete set of candidate networks with high performances, the networks designed by the proposed algorithm prove to be competitive, or even superior, to three selected traditional radial-basis function networks for predicting Mackey-Glass chaotic time series. © 2002 IEEE.

关键词： Genetic algorithms

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Fault tolerant control: An intelligent sliding mode control strategy

Fault tolerant control: An intelligent sliding mode control ...

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作者： Yen, Gary G. Ho, Liang-Wei Intelligent Systems and Control Laboratory School of Electrical and Computer Engineering Oklahoma State University Stillwater OK 74078-5032 United States

We investigate the fault tolerant control problem and propose an intelligent online sliding mode control strategy using artificial neural networks to handle the desired trajectories tracking problem for systems suffering from catastrophic faults or incipient failures. The approach is to continuously monitor the system performance and identify the system's current state by using a fault detection method based upon our best knowledge of the nominal system and nominal controller. Once a fault is detected, the proposed intelligent controller will adjust its control signal by adding a corrective sliding mode control signal to confine the system performance within a boundary layer. Meanwhile, an artificial neural network is initialized and compensates for the unknown fault dynamics online. When the online learning process converges, the control input is tuned again by using the output of the identification model and a new least upper bound for the remaining uncertainty is estimated to further reduce the tracking error. © 2000 American Automatic control Council.

关键词： Sliding mode control

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Addressing to online adaptive controller malfunction in fault tolerant control

Addressing to online adaptive controller malfunction in faul...

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Proceedings of the 2004 IEEE International Symposium on intelligent control - 2004 ISIC

作者： Delima, Pedro G. Yen, Gary G. Intelligent Systems and Control Laboratory School of Electrical and Computer Engineering Oklahoma State University Stillwater OK 74078-5032 United States

A complete Fault Tolerant control solution calls for a nonlinear adaptive controller with universal approximation capability and guaranteed stability. To fulfill this requirement we propose the use of Neural Networks trained online under a Globalized Dual Heuristic Programming architecture supervised by a decision logic capable of identifying controller malfunctions in early stages and providing new avenues with greater probability of convergence using information from a Dynamic Model Bank. The classification and distinction of controller malfunctions and of the faults in the system is achieved through three independent quality indexes. Proof-of-the-concept simulations of nonlinear plants demonstrate the approach legitimacy. © 2004 IEEE.

关键词： Fault tolerant computer systems

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Facial feature extraction using genetic algorithm

Facial feature extraction using genetic algorithm

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2002 Congress on Evolutionary Computation, CEC 2002

作者： Yen, Gary G. Nithianandan, Nethrie Intelligent Systems and Control Laboratory School of Electrical and Computer Engineering Oklahoma State University Stillwater OK 74074-5032 United States

ISBN: (纸本)0780372824

An automatic facial feature extraction method is presented in this paper. The method is based on the edge density distribution of the image. In the preprocessing stage a face is approximated to an ellipse, and a genetic algorithm is applied to search for the best ellipse region match. In the feature extraction stage, the genetic algorithm is applied to extract the facial features, such as the eyes, nose and mouth, in the predefined sub regions. The simulation results validates that the proposed method is capable of automatically extracting features from various video images effectively under natural lighting environments and in the presence of certain amount of artificial noise and of multi-face oriented with angles. © 2002 IEEE.

关键词： Genetic algorithms

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Convergence Rate Analysis of Gaussian Belief Propagation for Markov Networks

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IEEE/CAA Journal of Automatica Sinica 2020年第3期7卷 668-673页

作者： Zhaorong Zhang Minyue Fu School of Electrical Engineering and Computer Science The University of Newcastle.University DriveNSW 2308Australia IEEE School of Automation Guangdong University of Technologyand Guangdong Key Laboratory of Intelligent Decision and Cooperative ControlGuangzhou 510006China

Gaussian belief propagation algorithm(GaBP) is one of the most important distributed algorithms in signal processing and statistical learning involving Markov networks. It is well known that the algorithm correctly computes marginal density functions from a high dimensional joint density function over a Markov network in a finite number of iterations when the underlying Gaussian graph is acyclic. It is also known more recently that the algorithm produces correct marginal means asymptotically for cyclic Gaussian graphs under the condition of walk summability(or generalised diagonal dominance). This paper extends this convergence result further by showing that the convergence is exponential under the generalised diagonal dominance condition,and provides a simple bound for the convergence rate. Our results are derived by combining the known walk summability approach for asymptotic convergence analysis with the control systems approach for stability analysis.

关键词： Belief propagation distributed algorithm distributed estimation Gaussian belief propagation Markov networks

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From Parallel Plants to Smart Plants:intelligent control and Management for Plant Growth

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IEEE/CAA Journal of Automatica Sinica 2017年第2期4卷 161-166页

作者： Mengzhen Kang Fei-Yue Wang State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences (SKL-MCCSCASIA) Qingdao Academy of Intelligent Industries Beijing Engineering Research Center of Intelligent Systems and Technology IEEE State Key Laboratory of Management and Control for Complex Systems (SKL-MCCS) Institute of AutomationChinese Academy of Sciences (CASIA) School of Computer and Control Engineering University of Chinese Academy of Sciences Research Center for Military Computational Experiments and Parallel Systems Technology National University of Defense Technology

Precision management of agricultural systems, aiming at optimizing profitability, productivity and sustainability, comprises a set of technologies including sensors, information systems, and informed management, etc. Expert systems are expected to aid farmers in plant management or environment control, but they are mostly based on the offline and static information, deviated from the actual situation. Parallel management, achieved by virtual/artificial agricultural system, computational experiment and parallel execution, provides a generic framework of solution for online decision support. In this paper, we present the three steps toward the parallel management of plant: growth description U+0028 the crop model U+0029, prediction, and prescription. This approach can update the expert system by adding learning ability and the adaption of knowledge database according to the descriptive and predictive model. The possibilities of passing the knowledge of experienced farmers to younger generation, as well as the application to the parallel breeding of plant through such system, are discussed. © 2017 Chinese Association of Automation.

关键词： Agriculture Artificial intelligence Decision support systems Expert systems Sustainable development

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