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New results on anti-synchronization of switched neural networks with time-varying delays and lag signals

Neural networks : the official journal of the International Neural Network Society 2016年 81卷 52-8页

作者： Yuting Cao Shiping Wen Michael Z Q Chen Tingwen Huang Zhigang Zeng School of Automation Huazhong University of Science and Technology Wuhan 430074 China Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan 430074 China. Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan 430074 China. Electronic address: wenshiping226@***. The Department of Mechanical Engineering The University of Hong Kong Hong Kong. Texas A & M University at Qatar Doha 5825 Qatar.

This paper investigates the problem of global exponential anti-synchronization of a class of switched neural networks with time-varying delays and lag signals. Considering the packed circuits, the controller is dependent on the output of the system as the inner states are very hard to measure. Therefore, it is necessary to investigate the controller based on the output of the neuron cell. Through theoretical analysis, it is obvious that the obtained ones improve and generalize the results derived in the previous literature. To illustrate the effectiveness, a simulation example with applications in image encryptions is also presented in the paper.

关键词： Anti-synchronization Exponential stability Switched neural networks

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Observer-Based Robust Coordinated Tracking of Multi-Agent Systems with Input Saturation

Observer-Based Robust Coordinated Tracking of Multi-Agent Sy...

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IEEE Annual Conference on Decision and control

作者： Xiaoling Wang Housheng Su Xiaofan Wang Department of Automation Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai 200240 China Department of Control Science and Engineering Image Processing and Intelligent Control Key Laboratory of Education Ministry of China Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9781479978878

This paper addresses the robust semi-global coordinated tracking problem of multiple-input multiple-output (MIMO) multi-agent systems with input saturation and communication noise. A distributed observer-based coordinated tracking protocol is constructed by combining a novel parameterized low-and-high feedback technique with the high-gain observers design approach. It is shown that, under the assumptions that each agent is asymptotically null-controllab.e with bounded controls and the network is connected, semi-global consensus tracking or semi-global swarm tracking can be attained for left-invertible and minimal-phase systems.

关键词： noise(communication) bounded control tracking high gain Agents

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A heuristically accelerated multi-agent reinforcement learning algorithm applied to flow line maintenance scheduling

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Journal of Computational Information Systems 2015年第6期11卷 2245-2255页

作者： Wang, Xiao Wang, Hongwei Qi, Chao Wang, Xu School of Safety Engineering Shenyang Aerospace University Shenyang China Institute of Systems Engineering/State Key Laboratory of Education Ministry for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan China

This paper investigates the maintenance scheduling problem in a flow line system consisting of two series machines with a finite buffer in between. The machines deteriorate with age and have multiple deteriorating quality states represented by multiple decreasing yield levels. The maintenance problem of both machines is modeled as semi-Markov decision processes. A heuristically accelerated multi-agent reinforcement learning algorithm with a feature of incorporating heuristic function for action selection is developed to produce a reasonable maintenance scheduling. A comparison with a Ε-greedy search based exploration algorithm, a simulated annealing search based exploration algorithm, a tabu search based exploration algorithm and a neighborhood search based exploration algorithm in reinforcement learning is presented. The results indicate that the proposed heuristically accelerated multi-agent reinforcement learning algorithm is competitive and has a certain advantage for larger problems. Copyright © 2015 Binary Information Press.

关键词： Tabu search

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A new crossbar architecture based on two serial memristors with threshold

A new crossbar architecture based on two serial memristors w...

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International Joint Conference on Neural Networks (IJCNN)

作者： Xiaoping Wang Min Chen Yi Shen Xiaoya Hu Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan China School of Automation Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9781479919611

This paper presents a memory crossbar based on two serial memristors with threshold characteristic to eliminate the effect of sneak paths, which is a key issue in crossbar memory system leading to great degradation in their performance and power efficiency. At first, we analyze the threshold characteristic of memristor and propose a memristor model with threshold. Based on this model, the paper presents the design and simulation of a non-volatile memory system utilizing two serial memristors with different polarities as a memory cell. This scheme solves the sneak-path problem by taking advantage of the threshold characteristic and the performance with having always high resistance state in all the memory cells, which is validated by simulation results. The scheme also possesses the superior properties of remarkable compatibility and high density.

关键词： Memristors Nonvolatile memory

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Semi-global containment control of multi-agent systems with intermittent input saturation

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Journal of the Franklin Institute 2015年第9期352卷 3504-3525页

作者： Housheng Su Gui Jia Michael Z.Q. Chen School of Automation Image Processing and Intelligent Control Key Laboratory of Education Ministry of China Huazhong University of Science and Technology Luoyu Road 1037 Wuhan 430074 China Department of Mechanical Engineering The University of Hong Kong Hong Kong

This paper investigates containment control of multi-agent systems with intermittent communications and input saturation on fixed undirected networks . Under the assumption that each agent is asymptotically null controllab.e with bounded controls and there exists at least one leader that has directed path to each followers, both state feedback and output feedback control protocols are designed by utilizing the algebraic Riccati equation . For any a priori given bounded set , semi-global state feedback and output feedback containment control of multi-agent systems with intermittent communication can be attained. Numerical simulations are provided to ensure the effectiveness of results.

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Impulsive positive observers and dynamic output feedback stabilization of positive linear continuous systems

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International Journal of Robust and Nonlinear control 2016年第13期27卷

作者： Jiang-Wen Xiao Meng-Jie Hu Yan-Wu Wang Wu-Hua Chen School of Automation Huazhong University of Science and Technology Wuhan 430074 China Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan China College of Mathematics and Information Science Guangxi University Nanning 530004 China

This paper is concerned with the design and the synthesis of the impulsive positive observer (IPO) for positive linear continuous systems. The IPO can estimate the states for positive systems even when the measured output is only availab.e at discrete-time instants. In this paper, a time-varying weighted copositive Lyapunov function is constructed, and the upper and lower bounds of impulsive intervals method combined with the convex combination technique are used to establish sufficient conditions for the existence of the IPO. Furthermore, the design of the dynamic output feedback controller based on the IPO is addressed to positively stabilize positive linear systems. Algorithms are given to design the IPO and the controller, respectively. Finally, two numerical examples are provided to show the effectiveness of the theoretical results. Copyright © 2016 John Wiley & Sons, Ltd.

关键词： impulsive positive observer dynamic output feedback controller time-varying weighted copositive Lyapunov function positive system upper and lower bounds of impulsive intervals method convex combination technique

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A novel ANN-based harmonic extraction method tested with ESN, RNN and MLP in shunt active power filters

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International Journal of Wireless and Mobile Computing 2014年第2期7卷 123-131页

作者： Xu, Jinbang Yang, Jun Shen, Anwen Chen, Junfeng Image Processing and Intelligent Control Key Laboratory of Education Ministry of China Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan 430074 China

With the wide use of power conversion devices - 'nonlinear loads' - many harmonic currents are being injected into the power grid. Shunt Active Power Filters (SAPF) are the power electronic equipment to compensate the harmonic currents caused by nonlinear loads. As the foundation of the harmonics recognition and compensation, harmonic extraction is the key technology in SAPF. Artificial Neural Networks (ANN) method has the features of parallel computation and satisfactory results for distorted source voltages over traditional extraction methods. This paper proposes a new harmonic extraction method based on ANN. To test the feasibility of different types of neural networks in this application, this paper compares the performances of three types of ANN: Echo State Networks (ESN), Recurrent Neural Networks (RNN) and Multilayer Perceptron Networks (MLP). © 2014 Inderscience Enterprises Ltd.

关键词： Extraction

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control reconfiguration on deadlocked gimballed thrust of launch vehicle

Lecture Notes in Control and Information Sciences

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Lecture Notes in control and Information Sciences 2014年 452卷 27-59页

作者： Liu, Lei Wang, Yongji Key Laboratory of Ministry of Education for Image Processing and Intelligent Control School of Automation Huazhong University of Science and Technology Wuhan 430074 Hubei China

ISBN: (纸本)9783642363849

An unprecedented challenge of the new generation launch vehicle control is its four parallel strap-on engines are oscillateable by the servomechanism. It increases the manoeuvrability of the vehicle and the control complexity simultaneously. The chapter investigates actuator failure compensation for new generation launch vehicle control. A control reconfiguration scheme of fault-tolerant control is developed to enhance the reliability of launch vehicle attitude control systems and prevent the control invalidation caused by the deadlock of the oscillating actuator, based on the congruity of the composite moment before and after the failure happens. This reconfiguration scheme is capable of utilizing the remaining control authority to achieve the desired performance in the presence of deadlock at certain detectable angle occurring in one or several actuators at unknown time instants. © Springer-Verlag Berlin Heidelberg 2014.

关键词： Launch vehicles

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Multistability analysis of a general class of recurrent neural networks with non-monotonic activation functions and time-varying delays

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Neural networks : the official journal of the International Neural Network Society 2016年 79卷 117-27页

作者： Peng Liu Zhigang Zeng Jun Wang School of Automation Huazhong University of Science and Technology Wuhan 430074 China Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan 430074 China. Electronic address: liupengjz@***. Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan 430074 China. Electronic address: hustzgzeng@***. Department of Computer Science College of Science and Engineering City University of Hong Kong Kowloon Tong Hong Kong. Electronic address: jwang.cs@cityu.edu.hk.

This paper addresses the multistability for a general class of recurrent neural networks with time-varying delays. Without assuming the linearity or monotonicity of the activation functions, several new sufficient conditions are obtained to ensure the existence of (2K+1)(n) equilibrium points and the exponential stability of (K+1)(n) equilibrium points among them for n-neuron neural networks, where K is a positive integer and determined by the type of activation functions and the parameters of neural network jointly. The obtained results generalize and improve the earlier publications. Furthermore, the attraction basins of these exponentially stable equilibrium points are estimated. It is revealed that the attraction basins of these exponentially stable equilibrium points can be larger than their originally partitioned subsets. Finally, three illustrative numerical examples show the effectiveness of theoretical results.

关键词： Cohen–Grossberg neural networks Multistability Non-monotonic activation functions Time-varying delays

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A research on human cognitive modeling in rumor spreading based on HTM

Communications in Computer and Information Science

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Communications in Computer and Information Science 2014年 461卷 268-277页

作者： Li, Xiangchen Chen, X. Wang, Wei School of Automation Huazhong University of Science and Technology Wuhan China Image Processing and Intelligent Control Key Laboratory of Education Ministry of China Wuhan China

ISBN: (纸本)9783662452820

As a sociological phenomenon, rumor spreading has been widely researched by sociologists and other fields’ scholars. How do people generate those strange thinking about the rumor? This paper, from artificial intelligence view, focuses on an algorithm based on Hierarchical Temporal Memory (HTM) to simulate human cognitive process of generating rumors from individual heterogeneous living experience. Comparison with classical Bayesian Networks, our algorithm could effectively and really simulate human cognitive process of rumors, and in accordance with some typical psychology effects proved by sociologists and psychologists. © Springer-Verlag Berlin Heidelberg 2014.

关键词： Bayesian networks

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