Distributed Robust Dynamic Average Consensus with Dynamic Event-Triggered Communication

Abstract

This paper presents the formulation and analysis of a fully distributed dynamic event-triggered communication based robust dynamic average consensus algorithm. Dynamic average consensus problem involves a networked set of agents estimating the time-varying average of a dynamic reference signal locally available to individual agents. We propose an asymptotically stable solution to the dynamic average consensus problem what is also robust to network disruptions. Since this robust algorithm requires continuous communication among agents, we introduce a novel dynamic event-triggered communication scheme to reduce the overall inter-agent interactions. It is shown that the event-triggered algorithm is asymptotically stable and free of Zeno behavior. Numerical simulations are provided to illustrate the effectiveness of the proposed algorithm.