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Formation tracking of the second-order multi-agent systems using position-only information via impulsive control with input delays

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Applied Mathematics and Computation 2014年 246卷 572-585页

作者： Yan-Wu Wang Meng Liu Zhi-Wei Liu Jing-Wen Yi School of Automation Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Huazhong University of Science and Technology Wuhan 430074 PR China Department of Automation Wuhan University Wuhan 430072 PR China

In this paper, the formation tracking problem for the second-order multi-agent system with and without input delay are investigated, respectively. The objective is to design the formation tracking algorithm such that a certain follower follows the trajectory of the leader while also maintains a certain desired geometric formation with other agents simultaneously. The impulsive algorithms are designed by using only the relative position information of the neighbors for both the cases with and without the input delay. By using properties of the Laplacian matrix and combining the stability theory of impulsive systems, necessary and sufficient conditions are derived to achieve the formation tracking of the second-order multi-agent system with and without the input delay, respectively. The numerical examples are given to illustrate the effectiveness of our theoretical results.

关键词： Formation tracking Multi-agent system Impulsive control Input delay

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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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Vessel segmentation in retinal images with a multiple kernel learning based method

Vessel segmentation in retinal images with a multiple kernel...

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International Joint Conference on Neural Networks (IJCNN)

作者： Xiaoming Liu Zhigang Zeng Xiaoping Wang College of Computer Science and Technology Wuhan University of Science and Technology Wuhan China Key Laboratory of Image Information Processing and Intelligent Control Ministry of Education Wuhan China

Blood vessel segmentation is an important problem for quantitative structure analysis of retinal images, and many diseases are related to the structure changes. Manual segmentation is time consuming and computer aided segmentation is required to deal with large amount images. This paper presents a new supervised method for segmentation of blood vessels in retinal photographs. Multiple kernel learning (MKL) is introduced to deal with the problem, utilizing features from Hessian matrix based vesselness measure, response of multiscale Gabor filter, and multiple scale line strength features. The method is evaluated on the publicly available DRIVE and STARE databases. The performance of the MKL method is evaluated and experimental results show the high accuracy of the proposed method.

关键词： image segmentation Retina Biomedical imaging Kernel Blood vessels Accuracy Support vector machines

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Adaptive control for power and thermal management of an integrated 5kW solid oxide fuel cell system

Adaptive control for power and thermal management of an inte...

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第十五届全国氢能会议暨第7届两岸三地氢能研讨会

作者： Lin Zhang Jianhua Jiang Xi Li Huan Cheng Jie Yang Jian Li School of Automation Key Laboratory of Education Ministry for Image Processing and Intelligent ControlHuazhong University of Science & TechnologyWuhan430074China School of Materials Science and Engineering State Key Laboratory of Material Processing and Die and Mould TechnologyHuazhong University of Science and TechnologyWuhan 430074China

A 5-kW dynamic solid oxide fuel cell(SOFC)system with a second air bypass has been developed with a model to perform both steady-state and dynamic analysis in this *** identifies and addresses the control challenges a... 详细信息

关键词： Solid oxide fuel cell (SOFC) Optimal set-points Load transitions RBF network based direct adaptive controller

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The influencesof different gas flow types on solid oxide fuel cell stack temperature distribution

The influencesof different gas flow types on solid oxide fue...

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第十五届全国氢能会议暨第7届两岸三地氢能研讨会

作者： Huan Cheng Xi Li Jianhua Jiang Yali Liu Jian Li School of automation Key Laboratory of Education Ministry for Image Processing and Intelligent ControlHuazhong University of Science & TechnologyWuhan430074China School of Materials Science and Engineering State Key Laboratory of Material Processing and Die and Mould TechnologyHuazhong University of Science and TechnologyWuhan 430074China

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A membrane-inspired algorithm with a memory mechanism for knapsack problems

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Journal of Zhejiang University-Science C(Computers and Electronics) 2013年第8期14卷 612-622页

作者： Juan-juan HE Jian-hua XIAO Xiao-long SHI Tao SONG Key Laboratory of Image Processing and Intelligent Control School of AutomationHuazhong University of Science and Technology The Logistics Research Center Nankai University

Membrane algorithms are a class of distributed and parallel algorithms inspired by the structure and behavior of living cells. Many attractive features of living cells have already been abstracted as operators to improve the performance of algorithms. In this work, inspired by the function of biological neuron cells storing information, we consider a memory mechanism by introducing memory modules into a membrane algorithm. The framework of the algorithm consists of two kinds of modules (computation modules and memory modules), both of which are arranged in a ring neighborhood topology. They can store and process information, and exchange information with each other. We test our method on a knapsack problem to demonstrate its feasibility and effectiveness. During the process of approaching the optimum solution, feasible solutions are evolved by rewriting rules in each module, and the information transfers according to directions defined by communication rules. Simulation results showed that the performance of membrane algorithms with memory cells is superior to that of algorithms without memory cells for solving a knapsack problem. Furthermore, the memory mechanism can prevent premature convergence and increase the possibility of finding a global solution.

关键词： Membrane algorithm Memory mechanism Knapsack problem

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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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New criteria for exponential stability of delayed recurrent neural networks

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Neurocomputing 2014年 134卷 182-188页

作者： Jian Xiao Zhigang Zeng Ailong Wu 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 College of Mathematics and Statistics Hubei Normal University Huangshi 435002 China

In this paper, we investigate exponential stability of delayed recurrent neural networks. By using the delay partitioning method, some sufficient conditions are established to guarantee exponential stability of delayed recurrent neural networks under two different conditions with constructing new Lyapunov–Krasvoskii functional. This partitioning approach can reduce the conservatism comparing with some previous results of stability. At last, numerical examples are given out to show the effectiveness and advantage of our results.

关键词： Recurrent neural networks Exponential stability Time delay Delay partitioning approach

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Stability Analysis of Impulsive Positive Systems

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IFAC Proceedings Volumes 2014年第3期47卷 5987-5991页

作者： Ji-Shi Zhang Yan-Wu Wang Jiang-Wen Xiao Zhi-Hong Guan School of Automation Huazhong University of Science and Technology Wuhan 430074 China School of Software Henan University Kaifeng 475004 China Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan 430074 China

This paper is concerned with the problems of stability for a class of impulsive positive systems. An impulsive positive system model is introduced for the first time and a necessary and sufficient condition guaranteeing the positivity of this kind of system is proposed. Several sufficient criteria of global exponential stability and global asymptotical stability for impulsive positive systems are established respectively by using a linear copositive Lyapunov function. Two numerical examples are given to illustrate the effectiveness and applicability of the proposed results.

关键词： Impulsive positive system Positivity Exponentially stable Asymptotically stable Linear copositive Lyapunov function

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Indoor localization system based on wearable posture sensors with incomplete observations

Indoor localization system based on wearable posture sensors...

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International Conference on Modelling, Identification and control (ICMIC)

作者： Yuan Wang Jian Huang Yongji Wang Chunjing Tao Heping Yan Lifang Ma Key Laboratory of Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan China R&D department of National Research Center for Rehabilitation Technical Aids Beijing China

ISBN: (纸本)9781479951055

Radio Frequency Identification (RFID) based indoor localization becomes a hotspot in the robotic research field recently. To overcome the shortcoming that plentiful tags are required in a normal RFID based localization system, this paper presents an indoor localization method by fusing measurements from wearable posture sensors and the absolute position information from scattered RFID tags. From the posture sensors, we can obtain the relative indoor localization data by summing up the vectors composed of step length and heading direction. Since this relative localization is highly affected by the cumulative error, the absolute positions of RFID tags are used as corrections if they are found within a read-range to the user. Because the RFID tags are sparsely placed in the indoor environment, the corrections can be achieved only at incomplete time instants. Therefore, a revised Kalman filter with incomplete observation is applied to the sensor fusion between the posture sensors and RFID tags. Experimental results show that the cumulative error of the system can be significantly reduced and the localization accuracy is enhanced through the sensor fusion.

关键词： Kalman filters Sensor systems Vectors RFID tags Magnetic sensors

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