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Exponential synchronization of coupled memristive neural networks via pinning control

Chinese Physics B 2013年第5期22卷 203-212页

作者：王冠沈轶尹泉 Department of Control Science and Engineering Huazhong University of Science and Technology Key Laboratory of Ministry of Education for Image Processing and Intelligent Control

This paper is concerned with the exponential synchronization problem of coupled memristive neural networks. In contrast to general neural networks, memristive neural networks exhibit state-dependent switching behaviors due to the physical properties of memristors. Under a mild topology condition, it is proved that a small fraction of controlled sub- systems can efficiently synchronize the coupled systems. The pinned subsystems are identified via a search algorithm. Moreover, the information exchange network needs not to be undirected or strongly connected. Finally, two numerical simulations are performed to verify the usefulness and effectiveness of our results.

关键词： synchronization memristor coupled neural networks pinning control

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Consensus and rendezvous predictive control for multi-agent systems with input constraints

Consensus and rendezvous predictive control for multi-agent ...

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第三十三届中国控制会议

作者： Zhaomeng Cheng Hai-Tao Zhang Ming-Can Fan Key Laboratory of Image Processing and Intelligent Control School of AutomationState Key Lab of Digital Manufacturing Equipment and TechnologyHuazhong University of Science and Technology

ISBN: (纸本)9781479947249

The discrete-time double-integrator consensus and rendezvous problems are both addressed for distributed multiagent systems with directed switching topologies and input *** develop model predictive control algorithms to achieve stable consensus or rendezvous provided that the proximity nets always have a directed spanning tree and the sampling period is sufficiently ***,the control horizon is extended to larger than one as well,which endows sufficient degrees of freedom to facilitate controller *** simulations are finally conducted to show the effectiveness of the control algorithms.

关键词： Model predictive control(MPC),Multi-agent system(MAS),consensus,switching topology,input constraints

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Reversible spiking neural P systems

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Frontiers of Computer Science 2013年第3期7卷 350-358页

作者： Tao SONG Xiaolong SHI Jinbang XU Key Laboratory of Image Processing and Intelligent Control Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan 430074 China

Spiking neural （SN） P systems are a class of distributed parallel computing devices inspired by the way neurons communicate by means of spikes. In this work, we investigate reversibility in SN P systems, as well as the computing power of reversible SN P systems. Reversible SN P systems are proved to have Turing creativity, that is, they can compute any recursively enumerable set of non-negative integers by simulating universal reversible register machine.

关键词： membrane computing spiking neural P system reversible computing model universality reversible register machine

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Coordinated obstacle avoidance with reduced interaction

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Neurocomputing 2014年 139卷 233-245页

作者： Jiaojie Li Wei Zhang Housheng Su Yupu Yang Hongtao Zhou 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 Measurement and Control Technology Shanghai Dian Ji University Shanghai 200240 China School of Automation Key Laboratory of Education Ministry for Image Processing and Intelligent Control Huazhong University of Science and Technology Luoyu Road 1037 Wuhan 430074 China

In this paper, we study the coordinated obstacle avoidance algorithm of multi-agent systems when only a subset of agents has obstacle dynamic information, or every agent has local interaction. Each agent can get partial measuring states information from its neighboring agent and obstacle. Coordinated obstacle avoidance here represents not only the agents moving without collision with an obstacle, but also the agents bypassing and assembling at the opposite side of the obstacle collectively, where the opposite side is defined according to the initial relative position of the agents to the obstacle. We focus on the collective obstacle avoidance algorithms for both agents with first-order kinematics and agents with second-order dynamics. In the situation where only a fixed fraction of agents can sense obstacle information for agents with first-order kinematics, we propose a collective obstacle avoidance algorithm without velocity measurements. And then we extend the algorithm to the case in switched topology. We show that all agents can bypass an obstacle and converge together, and then assemble at the opposite side of the obstacle in finite time, if the agents׳ topology graph is connected and at least one agent can sense the obstacle. In the case where obstacle information is available to only a fixed fraction of agents with second-order kinematics, we propose two collective obstacle avoidance algorithms without measuring acceleration when the obstacle has varying velocity and constant velocity. The switched topology is considered and extended next. We show that agents can bypass the obstacle with their positions and velocities approaching consensus in finite time if the connectivity of switched topology is continuously maintained. Several simulation examples demonstrate the proposed algorithms.

关键词： Obstacle avoidance Consensus Reduced interaction Circular motion Multi-agents

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Observer-based synchronization of memristive systems with multiple networked input and output delays

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Nonlinear Dynamics 2014年第1期78卷 541-554页

作者： Shiping Wen Zhigang Zeng Tingwen Huang School of Automation Huazhong University of Science and Technology Wuhan China Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan China Texas A & M University at Qatar Doha Qatar

This paper investigates the synchronization problem of memristive systems with multiple networked input and output delays via observer-based control. A memristive system is set up, and the fuzzy method has been employed to linearize the dynamical system of the memristive system; the networked input and output delays are considered in the synchronization problem of this system. A truncated predictor feedback approach is employed to design the observers. Under certain restrictions, a class of finite-dimensional observer-based output feedback controllers is designed. A numerical example is carried out to demonstrate the effectiveness of the proposed methods.

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Path planning for multiple mobile robots under double-warehouse

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Information Sciences 2014年 278卷 357-379页

作者： Yong Ma Hongwei Wang Yong Xie Min Guo School of Navigation Wuhan University of Technology Wuhan 430063 China Hubei Key Laboratory of Inland Shipping Technology Wuhan 430063 China Key Laboratory of Image Processing and Intelligent Control Institute of Systems Engineering Huazhong University of Science and Technology Wuhan 430074 China

This work investigates the conflict-free path planning problems for efficient guidance of multiple mobile robots under the dynamic double-warehouse environment, a challenging problem that appears recurrently in a wide range of applications such as the service robots moving in a multistory building. United with two symmetrical transfer elevators, double-warehouse consists of two parallel warehouses. Within each warehouse, the polynomial based paths are subject to constraints such as motion boundaries, kinematics constraints, obstacle-avoidance, limited resource of elevators and smoothness. We formulate the shortest path planning problems as one time-varying nonlinear programming problem (TNLPP) while restricted to the above constraints, and apply the multi-phase strategy to reduce their difficulty. We present the new variant algorithms of PSO named constriction factor and random perturb PSO (Con-Per-PSO) and the simulating annealing PSO (SA-PSO) to achieve the solution. Numerical simulations verify that, our approach can fulfill multiple mobile robots path planning problems under double-warehouse successfully.

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Evolutionary membrane computing: A comprehensive survey and new results

Evolutionary membrane computing: A comprehensive survey and ...

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作者： Zhang, Gexiang Gheorghe, Marian Pan, Linqiang Pérez-Jiménez, Mario J. School of Electrical Engineering Southwest Jiaotong University Chengdu 610031 China Department of Computer Science University of Sheffield Regent Court Portobello Street Sheffield S1 4DP United Kingdom Key Laboratory of Image Processing and Intelligent Control Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan 430074 China Department of Computer Science and Artificial Intelligence University of Sevilla Avda. Reina Mercedes s/n Sevilla 41012 Spain

Evolutionary membrane computing is an important research direction of membrane computing that aims to explore the complex interactions between membrane computing and evolutionary computation. These disciplines are receiving increasing attention. In this paper, an overview of the evolutionary membrane computing state-of-the-art and new results on two established topics in well defined scopes (membrane-inspired evolutionary algorithms and automated design of membrane computing models) are presented. We survey their theoretical developments and applications, sketch the differences between them, and compare the advantages and limitations. © 2014 Elsevier Inc. All rights reserved.

关键词： Surveys

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Genetic Algorithm based Neural Network for the Displacement of Landslide Forecasting

Genetic Algorithm based Neural Network for the Displacement ...

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第三十三届中国控制会议

作者： Jiejie Chen Zhigang Zeng Ping Jiang Huiming Tang The School of Automation Huazhong University of Science and Technology Key Laboratory of Image Information Processing and Intelligent Control Ministry Education Faculty of Engineering China University of Geosciences

This paper proposes two hybrid prediction models using for predicting the displacement of landslide, Genetic Algorithm-Radial Basis Function Neural Network (GA-RBFN) and Genetic Algorithm- Back Propagation Neural Network (GA-BPNN). A case study of Yuhuangge landslide in the Three Gorges reservoir in China is used to illustrate the capability and merit of our schemes. In addition, the result shows that GP-BPNN get better accuracy than GA-RBFN in the same measurements.

关键词： Terrain factors Genetic algorithms Neural networks Forecasting Training Transfer functions Educational institutions

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Homotopy-based image reconstruction in breast ultrasound tomography

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Journal of Information and Computational Science 2013年第3期10卷 687-699页

作者： Gaddoura, Omer M. Wang, Longhui Ding, Mingyue School of Life Science and Engineering Image Processing and Intelligence Control Key Laboratory of Education Ministry of China Huazhong University of Science and Engineering Wuhan 430074 China

To diagnose breast cancer, an alternative approach to X-ray mammography and B-mode ultrasound is the Breast Ultrasound Computed Tomography (UCT). Concerning breast cancer detection, mammographic techniques have been considered as gold standard modality but these methods suffer through high rate of false-positive results and radiations. In addition, the use of low resolution images in the conventional ultrasound techniques is another problem that makes it difficult to differentiate between breast tissues and tumor existence. In this particular study, we have used a full wave-based tomographic technique to diagnose the breast cancer. While taking into account the physical characteristics, full wave-based approach constructs non-linear operator that transforms it as a nonlinear inverse problem or a minimization problem. To solve the non-linear inverse problem, we have used Homotopoy Continuation Methods (HCM), which is globally convergent method and provides multiple solutions. In the subsequent steps, to reduce the computational complexity and the high usage of memory for finding out the Jacobian of the cost function, we have applied discrete adjoint method. In the last, the effect of the noise to the reconstructed image has been tested. In this preliminary analysis with the use of adjoint methods, obtained results have shown the robustness and visibility of our proposed approach. © 2013 by Binary Information Press.

关键词： image reconstruction

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Swarm aggregations of heterogeneous multi-agent systems

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International Journal of control 2014年第12期87卷 2594页

作者： Liang, Haili Su, Housheng Wang, Xiaofan Chen, Michael Z.Q. [a] Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai 200240 China[b] School of Automation Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Huazhong University of Science and Technology Luoyu Road 1037 Wuhan 430074 China[c] Department of Mechanical Engineering The University of Hong Kong Hong Kong

This paper investigates the problem of swarm aggregations of heterogeneous multi-agent systems. Comparing with the existing studies on swarm aggregations of homogeneous multi-agent systems, this paper is much more resembling the practical situations, where the agents have different dynamics. We show that the heterogeneous agents will gather with a certain error under some assumptions and conditions. The stability properties have been proven by theoretical analysis and verified via numerical simulation. The stability of the heterogeneous multi-agent systems has been achieved based on matrix theory and the Lyapunov stability theorem. Numerical simulation is given to demonstrate the effectiveness of the theoretical result. [PUBLICATION ABSTRACT]

关键词： swarm multi-agent systems heterogeneous systems stability

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