Tracking consensus for nonlinear heterogeneous multi-agent systems subject to unknown disturbances via sliding mode control

We investigate the tracking control for a class of nonlinear heterogeneous leader-follower multi-agent systems（MAS）with unknown external disturbances. Firstly, the neighbor-based distributed finite-time observers are proposed for the followers to estimate the position and velocity of the leader. The...

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Published inChinese physics B Vol. 26; no. 7; pp. 39 - 48
Main Author 张翔 王金环 杨德东 徐勇
Format Journal Article
LanguageEnglish
Published 01.06.2017
Subjects
一致性
外部扰动
多智能体系统
有限时间
终端滑模控制
自适应控制律
跟踪误差
非线性
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Summary:We investigate the tracking control for a class of nonlinear heterogeneous leader-follower multi-agent systems（MAS）with unknown external disturbances. Firstly, the neighbor-based distributed finite-time observers are proposed for the followers to estimate the position and velocity of the leader. Then, two novel distributed adaptive control laws are designed by means of linear sliding mode（LSM） as well as nonsingular terminal sliding mode（NTSM）, respectively. One can prove that the tracking consensus can be achieved asymptotically under LSM and the tracking error can converge to a quite small neighborhood of the origin in finite time by NTSM in spite of uncertainties and disturbances. Finally, a simulation example is given to verify the effectiveness of the obtained theoretical results.
Bibliography:multi-agent systems; tracking consensus; distributed adaptive control; sliding mode
We investigate the tracking control for a class of nonlinear heterogeneous leader-follower multi-agent systems（MAS）with unknown external disturbances. Firstly, the neighbor-based distributed finite-time observers are proposed for the followers to estimate the position and velocity of the leader. Then, two novel distributed adaptive control laws are designed by means of linear sliding mode（LSM） as well as nonsingular terminal sliding mode（NTSM）, respectively. One can prove that the tracking consensus can be achieved asymptotically under LSM and the tracking error can converge to a quite small neighborhood of the origin in finite time by NTSM in spite of uncertainties and disturbances. Finally, a simulation example is given to verify the effectiveness of the obtained theoretical results.
Xiang Zhang1,Jin-Huan Wang1,De-Dong Yang2,Yong Xu1（ 1 School of Sciences. Hebei Province Key Laboratory of Big Data Calculation, Hebei University of Technology, Tianjin 300401, China ; 2 School of Control Science and Engineering, Hebei University of Technology, Tianjin 300130, China）
11-5639/O4
ISSN:1674-1056
2058-3834
DOI:10.1088/1674-1056/26/7/070501