A Fully Distributed Event-Triggered Average Tracking Protocol with Discrete Communication and Control Updating

This paper investigates a communicationlcontrol-efficient protocol for the distributed average tracking (DAT) problem of multi-agent systems, where each agent has only access to its own reference signal and aims to track the average of all signals. For this objective, we design a novel adaptive event-triggered mechanism (AETM) with discrete communication and control updating, which significantly reduces the cost of communication and control and Zeno behavior is excluded. Then, a fully distributed protocol under the AETM is well-established, which exhibits high scalability by removing the requirement of global such as eigenvalues of the Laplacian matrix. Moreover, several sufficient conditions are derived to ensure all agents asymptotically track the average of all reference signals. Finally, a simulation example is given to verify the effectiveness of the designed protocol.