Periodic Event-Triggered Consensus of Stochastic Multi-Agent Systems Under Switching Topology

The event-triggered mechanism serves as an effective discontinuous control strategy for addressing the consensus tracking problem in multi-agent systems (MASs). This approach optimizes energy consumption by updating the controller only when some observed errors exceed a predefined threshold. Considering the influence of noise on agent dynamics in complex control environments, this study investigates an event-triggered control scheme for stochastic MASs, where noise is modeled as Brownian motion. Furthermore, the communication topology of the stochastic MASs is assumed to exhibit a Markovian switching mechanism. Analytical criteria are derived to guarantee consensus tracking in the mean square sense, and a numerical example is provided to validate the effectiveness of the proposed control methods.