Adaptive cooperative formation-containment control for networked Euler–Lagrange systems without using relative velocity information

• Published in: IET control theory & applications Vol. 11; no. 9; pp. 1450 - 1458
• Main Authors: Chen, Liang-Ming, Li, Chuan-Jiang, Mei, Jie, Ma, Guang-Fu
• Format: Journal Article
• Language: English
• Published: The Institution of Engineering and Technology 02.06.2017
• Subjects: adaptive control; adaptive cooperative formation‐containment control; CFCC problem; control gains; control system synthesis; controller design; convex hull; directed graph; directed graphs; distributed containment control problem; multiagent systems; multi‐agent systems; networked control systems; networked Euler–Lagrange systems; position control; Research Article; multi-agent systems; controller design; adaptive control; control system synthesis; networked Euler–Lagrange systems; convex hull; adaptive cooperative formation-containment control; directed graphs; directed graph; networked control systems; CFCC problem; position control; distributed containment control problem; control gains; multiagent systems
• ISSN: 1751-8644; 1751-8652; 1751-8652
• DOI: 10.1049/iet-cta.2016.1185

This study is concerned with the problem of cooperative formation-containment control (CFCC) for networked Euler–Lagrange systems under a directed graph. Compared with the distributed containment control problem, CFCC problem is a new problem in the community of multi-agent systems as the control for leaders' formation is further considered. By introducing the desired relative distance between agents into the auxiliary variables, the formation control algorithms are designed firstly for multiple leaders to reach a constant configuration. Then, the distributed containment control algorithms are designed for the followers such that all followers asymptotically converge to the convex hull spanned by the leaders. In the proposed algorithms, the relative velocity information is not required for the agents' controller design. Moreover, to reduce the dependence on system global information, the control gains in the algorithms are changing adaptively using only local information. Finally, simulation results are provided to illustrate the effectiveness of the obtained theoretical results.