Distributed Containment Control for Discrete-Time Nonlinear Multiagent Systems Over Dynamic Topology With System Uncertainties

Changkun Du, Nannan Li, Zhen Li, Samson Shenglong Yu, Chee Peng Lim

Abstract: This article explores the distributed containment control problem under dynamic directed topologies in discrete-time nonlinear multiagent systems (MASs) subject to parameter uncertainties that are nonlinearly coupled with the agents' states. Specifically, a parameter estimation algorithm is first adopted to deal with the parametric uncertainty. Then, based on the estimated parameters, a distributed adaptive containment control protocol is proposed in a distributed fashion for nonlinear and uncertain MASs over dynamic digraphs. To tackle the challenges caused by the dynamic topology, the evolution of the dynamic topology of MASs is transformed into time-varying Markov chains. By analyzing the characteristics of time-varying Markov chains, the properties of some key matrices related to the dynamic topology are derived, which benefits the convergence analysis of containment control. By applying the proposed control protocol, the reference signals can be tracked by the leaders, while the followers' states are driven into the convex hull formed by leaders. Finally, simulation results and performance analysis are discussed to demonstrate the effectiveness of developed methods.