Adaptive bipartite consensus control of general linear multi-agent systems using noisy measurements

摘要

This paper considers bipartite consensus problem for general linear systems with communication noises and antagonistic interactions. The interaction network associated with the cooperative-competitive multi agent system is modeled by a signed graph (called coopetition network in sequel) and the agent dynamics is described by a general linear system. Instead of using the stochastic-approximation method available for previous works, adaptive laws are firstly designed for heterogenous time-varying control gains for agents. Furthermore, a fully distributed controller is proposed for multi-agent systems with measurement noises. At the same time, the bipartite consensus errors are proved to be exponentially bounded in mean square and the convergence is analyzed with a stochastic Lyapunov function method. Finally, some simulation results are presented to demonstrate the effectiveness of the proposed adaptive control strategy.(c) 2021 European Control Association. Published by Elsevier Ltd. All rights reserved.