Dynamic Event-Triggered Consensus of Matrix-Weighted Linear Multiagent Systems

Abstract

This article investigates the dynamic event-triggered consensus of linear leader-following multiagent systems under matrix-weighted networks. In such networks, matrix weights characterize the dependencies among multidimensional states of agents. First, we propose a distributed dynamic event-triggered control protocol in which each agent employs an auxiliary system to dynamically adjust the triggering threshold. Moreover, it is ensured that the sequence of triggering times does not exhibit Zeno behavior under given conditions. Remarkably, clustering naturally occurs in matrix-weighted networks, which reflects the important role of matrix coupling in the convergence process. Furthermore, Lyapunov stability theory is applied to achieve leader-following consensus in matrix-weighted multiagent networks. Finally, a simulation is presented to verify the reliability of the obtained results.