Containment control for second-order nonlinear multi-agent systems with intermittent communications

ABSTRACT

This article investigates the containment control problem for a class of second-order multi-agent systems with inherent nonlinear dynamics, under the common assumption that each agent can only obtain the relative information of its neighbours intermittently. A kind of distributed protocol based only on the relative local intermittent measurements of neighbouring agents is designed for containment control under fixed directed topology. In the absence of delays, based on the Lyapunov function technology and the intermittent control method, some sufficient conditions are presented to guarantee the intermittent containment control of second-order nonlinear multi-agent systems. In the presence of delays, some containment conditions are also obtained for a second-order multi-agent systems with inherent delayed nonlinear dynamics and intermittent communications. Moreover, the similar results are obtained for second-order nonlinear multi-agent systems under switching directed topology. Finally, simulation examples are given to illustrate the correctness and effectiveness of the theoretical analysis.

KEYWORDS:

• Containment control
• second-order multi-agent systems
• delayed nonlinear dynamics
• intermittent communications

Disclosure statement

No potential conflict of interest was reported by the authors.

ORCID

Zengqiang Chen http://orcid.org/0000-0002-1415-4073

Additional information

Funding

This work was supported by the National Natural Science Foundation of China under Grant Nos. 61573200, 61573199.

Notes on contributors

Fuyong Wang

Fuyong Wang received the B.S. degree in electrical engineering and automation and M.S. degree in computer application technology from the Ludong University, Yantai, China, in 2013 and 2016, respectively. He is now pursuing the Ph.D. degree in the College of Computer and Control Engineering, Nankai University, Tianjin, China. His current research interests are complex networks and multi-agents system.

Zhongxin Liu

Zhongxin Liu received the B.S. degree in automation and Ph.D. degree in control theory and control engineering from the Nankai University, Tianjin, China, in 1997 and 2002, respectively. He has been at Nankai University, where he is currently a Professor in the Department of Automation. His main areas of research are in predictive control, complex networks and multi-agents system.

Zengqiang Chen

Zengqiang Chen received the B.S. degree in mathematics, M.S. and Ph.D. degrees in control theory and control engineering from the Nankai University, Tianjin, China, in 1987, 1990 and 1997, respectively. He has been at Nankai University, where he is currently a Professor in the Department of Automation. His main areas of research are in neural network control, complex networks and multi-agents system.

Sensen Wang

Sensen Wang received the B.S. degree in electrical engineering and automation from the Shandong Jianzhu University, Jinan, China, in 2017. He is now pursuing the M.S. degree in the College of Artificial Intelligence, Nankai University, Tianjin, China. His research interest covers coordination of multi-agent systems.