Average Consensus in Discrete-Time Multi-Agent Systems with Distributed Event-Triggered Control

We consider the average consensus problem for the multi-agent system in the discrete-time domain. An event-triggered control protocol dictates the broadcast and control update instants of individual agents to alleviate communication and computational burden. The control protocol is distributed in the sense that to execute the control law, the agents do not require prior knowledge of global parameters of the network. A Lyapunov-based design method prescribes when agents should communicate and update their control so that the network converges to the average of agents' initial states. The distributed dynamic triggering law involves an internal auxiliary variable to regulate the threshold dynamically for each agent. A self-triggering algorithm is used to avoid continuous listening wherein each agent estimates its next triggering time and broadcasts it to its neighbors at the current triggering time. Numerical simulations are shown to validate the efficacy of the proposed algorithms.