Edge-based event-triggered output feedback control for stochastic multi-agent systems

Abstract

This article considers the problem of edge-based event-triggered output feedback control for linear multi-agent systems (MASs) with state-independent process and measurement noise under undirected communication topologies. The main breakthroughs are the design of distributed event-triggered output feedback control strategy and the stochastic stability analysis. Toward this, first, according to Kalman filtering theory, An observer is contrasted to optimally estimate the state of each agent. Next, a novel edge-based event-triggered mechanism (EBETM) is designed to reduce the communication frequency among agents effectively, and a positive interval between events is enforced in EBETM, which can eliminate the Zeno behavior. Then, stability of the estimation error and the consensus error systems is analyzed, the execution error is estimated and the almost sure consensus is achieved. Finally, a numerical example is given to show that MASs achieves almost sure consensus and there is a positive interval between the events of all edges.