Distributed Average Tracking of Heterogeneous Multi-Agent Systems via Event-Triggered Strategies

In this article, the event-triggered distributed average tracking (ETDAT) problem is investigated for heterogeneous multi-agent systems (MASs) with multiple bounded derivatives time-varying reference signals. The objective is to enable the output of every heterogeneous agent ultimately track the mean trajectory of multiple time-varying reference signals via event-triggered communication strategies. By using output regulation techniques, an ETDAT algorithm is established and the stability of the system is analyzed. Meanwhile, the non-zeno analysis is conducted. The main contribution of this article is that agent dynamics are extended to heterogeneous conditions and the communication frequency between agents is reduced, which is more practical and meaningful. Finally, a simulation example illustrates the validity of the main results.