A Decentralized Dynamic Self-Triggered Control Approach to Consensus of Multiagent Systems

Abstract

This article studies the self-triggered consensus control problem for linear multiagent systems (MASs) with the aim of improving resources utilization efficiency, e.g., saving communication bandwidth and reducing node energy consumption. First, a distributed control protocol is designed and a novel decentralized dynamic self-triggering mechanism (DDSTM) is proposed, with which, each agent can not only compute its own next triggering instant but also is able to compute the neighbors’ next triggering instant. Then, a hybrid system model is constructed to completely describe the close-loop system with jump dynamics. Based on the hybrid model, Lyapunov conditions are derived for MAS consensus analysis. The proposed DDSTM can overcome some limitations of the existing distributed STMs in the sense of synchronously acquiring consensus error or uniquely determining triggering instants, moreover, it allows transceivers to be turned on only at triggering instants and enter into sleep mode at the rest time, such that node energy is efficiently saved. Preadjustable minimum triggering interval is imposed between any consecutive triggering events; thus, a minimum sleep period for transceivers is always guaranteed. Finally, a numerical example is presented to demonstrate the effectiveness of the proposed approach.