Optimal Synchronization for Multiagent Systems Under Directed Graphs by Scalable Distributed Event-Triggered Control

This brief focuses on the convex optimization synchronization problem of linear multi-agent systems (MASs) based on adaptive distributed event-triggered control scheme under directed graphs, where the leader-follower consensus problem is solved by minimizing the sum of the cost functions of all agents. Firstly, a auxiliary system to generate the implicit trajectory, and a controller based on the implicit trajectory are respectively constructed for each follower, where the implicit trajectory plays an important role in minimizing the team cost function. Secondly, the novel event-triggered mechanisms are designed to realize the event-triggered communication between neighbor agents and the discrete update of controller simultaneously. Then, it has been shown that the optimal synchronization is reached and no Zeno behavior is exhibited by using the proposed methods.