Consensus via event-triggered strategy of nonlinear multi-agent systems with Markovian switching topologies

Jinfeng Gao; Jiahao Li; Haipeng Pan; Zhengguang Wu; Xiuxing Yin; Huijiao Wang

doi:10.1016/j.isatra.2019.11.013

Consensus via event-triggered strategy of nonlinear multi-agent systems with Markovian switching topologies

ISA Trans. 2020 Sep:104:122-129. doi: 10.1016/j.isatra.2019.11.013. Epub 2019 Nov 15.

Authors

Jinfeng Gao¹, Jiahao Li², Haipeng Pan², Zhengguang Wu³, Xiuxing Yin⁴, Huijiao Wang⁵

Affiliations

¹ Faculty of Mechanical Engineering and Automation, Zhejiang Sci-Tech University, Hangzhou, 310018, PR China. Electronic address: gaojf163@163.com.
² Faculty of Mechanical Engineering and Automation, Zhejiang Sci-Tech University, Hangzhou, 310018, PR China.
³ National Laboratory of Industrial Control Technology, Institute of Cyber-Systems and Control, Zhejiang University, Hangzhou, 310027, PR China.
⁴ Faculty of Mechanical Engineering and Automation, Zhejiang Sci-Tech University, Hangzhou, 310018, PR China; School of Engineering, University of Warwick, United Kingdom.
⁵ Institute of Information and Control, Hangzhou Dianzi University, Hangzhou, 310018, PR China.

PMID: 31759683
DOI: 10.1016/j.isatra.2019.11.013

Abstract

The consensus problem via event-triggered strategy of nonlinear multi-agent systems (MASs) with Markovian switching topologies is addressed in this paper. To simplify information transmission, a distributed event-triggered mechanism (ETM) is designed. By combining the Markovian switching topologies and ETM, an appropriate consensus control protocol is presented. Considering the impact of delay on systems stability, the system model is transformed by the delay system approach. By choosing a Lyapunov-Krasovskii function and applying linear matrix inequalities technique, sufficient conditions are obtained to ensure the consensus stability with H_∞ norm bound of the MASs. A numerical simulation is given to confirm the effectiveness of the designed method.

Keywords: Consensus; Event-triggered strategy; Linear matrix inequalities; Markovian switching topologies; Multi-agent systems.