Bipartite Consensus of Multi-Agent Systems via Adaptive Dynamic Event-Triggered Control

This paper investigates the bipartite consensus problem for leader-following multi-agent systems over the signed undirected graph. An adaptive dynamic event-triggered strategy is developed for achieving bipartite consensus with relative information among agents. Specifically, by including adaptive techniques, the design of control protocols frees from the dependence on global network information. Then, due to the relative information we introduced, also no global coordinate frame is needed. Furthermore, the triggering condition in this study can be dynamically evolved by adding an internal variable, hence prolonging the duration between consecutive events. The proposed protocol is proved to asymptotically reach the bipartite consensus while excluding Zeno behavior. The effectiveness of our method is demonstrated through a numerical example.