Target Tracking and Obstacle Avoidance for Multi-agent Networks with Input Constraints  

作　　者：Jing Yan Xin-Ping Guan Xiao-Yuan Luo Fu-Xiao Tan 

机构地区：[1]Department of Electrical Engineering, Yanshan University, Qinhuangdao 066004, PRC [2]School of Electronic and Electric Engineering, Shanghai Jiao Tong University, Shanghai 200240, PRC [3]School of Computer and Information, Fuyang Teachers College, Fuyang 236041, PRC

出　　处：《International Journal of Automation and computing》2011年第1期46-53,共8页国际自动化与计算杂志（英文版）

基　　金：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);Key Project for Shanghai Committee of Science and Technology (No. 08511501600)

摘　　要：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.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.

关 键 词：Target tracking obstacle avoidance multi-agent networks potential function optimal control. 

分 类 号：TP13[自动化与计算机技术—控制理论与控制工程] TN953[自动化与计算机技术—控制科学与工程]