Title: Multipartite tracking consensus of linear MASs with arbitrarily projective parameters

Authors: Liuxiao Guo; Jing Chen; Manfeng Hu; Zhengxian Jiang

Addresses: School of Science, Jiangnan University, Wuxi, 214122, China ' School of Science, Jiangnan University, Wuxi, 214122, China ' School of Science, Jiangnan University, Wuxi, 214122, China ' School of Science, Jiangnan University, Wuxi, 214122, China

Abstract: This paper proposes distributed bipartite and multipartite tracking consensus for linear multiagent systems (MASs) with arbitrarily nonzero projective parameters in networks, which includes traditional consensus, bipartite consensus and group consensus as its special items. Based on the projective similarity transformation and Riccati inequality, novel types of protocols are designed to achieve bipartite and multipartite consensus exponentially without analysing signed graph as in most current literature on bipartite problem. For obtaining multipartite consensus involving less global information, the distributed protocols with adaptive tuning of the coupling strength are further designed. The theoretical results are illustrated through two numerical simulation examples when linear systems are equilibrium point and periodic states.

Keywords: multipartite consensus; multi-agent system; linear systems; projective parameters; adaptive control.

DOI: 10.1504/IJMIC.2020.114196

International Journal of Modelling, Identification and Control, 2020 Vol.35 No.3, pp.203 - 210

Received: 28 Jan 2020
Accepted: 13 Jun 2020
Published online: 13 Apr 2021 *

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