Abstract
In this paper, the problems of target tracking and obstacle avoidance for multi-agent networks with input constraints are investigated. When there is a moving obstacle, the control objectives are to make the agents track a moving target and to avoid collisions among agents. First, without considering the input constraints, a novel distributed controller can be obtained based on the potential function. Second, at each sampling time, the control algorithm is optimized. Furthermore, to solve the problem that agents cannot effectively avoid the obstacles in dynamic environment where the obstacles are moving, a new velocity repulsive potential is designed. One advantage of the designed control algorithm is that each agent only requires local knowledge of its neighboring agents. Finally, simulation results are provided to verify the effectiveness of the proposed approach.
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This work was supported by National Basic Research Program of China (973 Program) (No. 2010CB731800), Key Project of National Science Foundation of China (No. 60934003), National Nature Science Foundation of China (No. 61074065), Key Project for Natural Science Research of Hebei Education Department, PRC (No. ZD200908), and Key Project for Shanghai Committee of Science and Technology (No. 08511501600).
Jing Yan received the B. Eng. degree in automation from Henan University, PRC in 2008. He is currently a Ph.D. candidate in control theory and control engineering at Yanshan University, PRC.
His research interests include cooperative control of multi-agent systems and wireless networks.
Xin-Ping Guan received the M. Sc. degree in applied mathematics from Harbin Institute of Technology, PRC in 1991, and the Ph.D. degree in electrical engineering from Harbin Institute of Technology in 1999. From 1986 to 2007, he was a professor of control theory and control engineering at Yanshan University, PRC. Since 2007, he has joined Shanghai Jiao Tong University, PRC.
His research interests include robust congestion control in communication networks, cooperative control of multi-agent systems, and networked control systems.
Xiao-Yuan Luo received the M. Sc. and Ph.D. degrees from the Department of Electrical Engineering, Yanshan University, PRC in 2001 and 2004, respectively. He is currently an associate professor in Yanshan University.
His research interests include fault detection and fault tolerant control, multi-agent, and networked control systems.
Fu-Xiao Tan received the B.Eng. degree in automation from Hefei University of Technology, PRC in 1997, and the Ph.D. degree in control theory and control engineering from Yanshan University, PRC in 2009. He is currently an associate professor in Fuyang Teachers College, PRC.
His research interests include cooperative control of multi-agent systems and networked control systems.
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Yan, J., Xin-Ping, G., Xiao-Yuan, L. et al. Target tracking and obstacle avoidance for multi-agent networks with input constraints. Int. J. Autom. Comput. 8, 46–53 (2011). https://doi.org/10.1007/s11633-010-0553-1
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DOI: https://doi.org/10.1007/s11633-010-0553-1