Leader–follower consensus for nonlinear multi-agent systems with unknown measurement sensitivities

Abstract

In this paper, the leader–follower consensus problem is investigated for a class of lower-triangular nonlinear multi-agent systems with unknown measurement sensitivities. By developing a dual-domination gain method, a distributed compensator is proposed for each follower by utilising the output information of the follower and its neighbour agents. Based on the compensator, an output feedback control law is designed to achieve consensus. These two gains are used to deal with the unknown measurement noises and nonlinear terms, respectively. Then the consensus problem is transformed into a stability problem by introducing an appropriate state transformation. Based on the Lyapunov stability theory, it is proved that the states of the leader and followers can achieve consensus asymptotically. In the end, numerical simulations are provided to verify the correctness of the proposed consensus algorithm.

Keywords:

• Consensus
• lower-triangular
• nonlinear multi-agent systems
• unknown measurement sensitivities

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data Availability Statement

The authors confirm that the data supporting the findings of this study are available within the article.

Additional information

Funding

This work was supported by National Natural Science Foundation of China (62273200), Hubei Key Laboratory of Hydroelectric Machinery Design and Maintenance (2021KJX04).

Notes on contributors

Dawei Wang

Dawei Wang received the B.S. in automation from Hubei Normal University, Huangshi, China, in 2019. He is currently pursuing the M.S. degree in electrical engineering with China Three Gorges University, Yichang, China. His current research interests include nonlinear multi-agent systems and consensus control.

Yanjun Shen

Yanjun Shen received the bachelor’s degree from the Department of Mathematics at the Normal University of Huazhong of China in 1992, the master’s degree from the Department of Mathematics at Wuhan University in 2001 and the Ph.D. degree in the Department of Control and Engineering at Huazhong University of Science and Technology in 2004. Now, he is currently a professor in the College of Electrical Engineering and New Energy, China Three Gorges University. His research interests include robust control, nonlinear systems, and neural networks.

Zifan Fang

Zifan Fang has been a Professor of Mechanical Engineering at The Mechanical & Power Engineering College of China Three Gorges University, since 1986. He received the Ph.D. in Vehicle Engineering from Chongqing University. Pro. Fang has broad research interests, which include finite element analysis, design, and dynamics. He has published widely in these areas and serves as engineering consultation.