Sampled-Data Consensus of Multiagent Systems Under Distributed Event-Triggered Impulsive Control With an Innovative Optimization Strategy: Reasonable Sampling and Control Instants Are Selected

This article investigates the sampled-data consensus of multiagent systems (MASs) under distributed event-triggered impulsive control (DETIC). To further conserve control resources, we propose a novel control strategy along with an innovative optimization strategy to, respectively, improve the sampling/triggering mechanisms and optimize the impulsive control signals. Specifically, a three-level Lyapunov-based triggering mechanism is designed to select more desirable sampling moments and impulsive control instants from a presampled sequence. Furthermore, impulsive controller optimization algorithms (ICOAs) are developed for MASs with three distinct topological structures, thereby accelerating the consensus speed. The results demonstrate that the proposed strategies achieve comparable or even superior control performance to traditional sampled-data and event-triggered control (ETC) methods, while requiring far fewer sampling and control operations. Notably, Zeno behavior is inherently avoided. Based on Lyapunov analysis and inequality techniques, several sufficient consensus criteria are established, and the effectiveness of these results is verified through three simulation examples.