Data-sampled mean-square consensus of hybrid multi-agent systems with time-varying delay and multiplicative noises

Abstract

This paper addresses the issue of dynamic mean-square consensus for second-order hybrid multi-agent systems. Time-varying delays and multiplicative noises are considered. New distributed control protocols are designed based on data-sampled information of neighbor agents. Equivalently using the error system based on Laplacian matrix, the method could make a dynamic consensus both under the fixed and switching topologies. By adopting stochastic system theory, Lyapunov stability method and linear matrix inequality theory, several sufficient conditions for the dynamic mean-square consensus are obtained. The upper bound of time delay and the discrete-time sampling period of hybrid multi-agent systems under a stochastic noises environment are inferred. Several simulations are presented to demonstrate the effectiveness of the proposed methods.