Dynamic Event-Triggered Distributed Optimization for Multi-Agent Systems with External Disturbances

This paper is devoted to the distributed optimization issue for multi-agent systems (MASs) with external interferences. Firstly, a distributed protocol with dynamic event-triggered (DET) communication is proposed to avert continuous communication among intelligent agents, here an auxiliary variable is introduced for each individual to adjust dynamically its threshold. Then, it is proved that under the DET mechanism, the lower bound of the inter-event time between consecutive triggering moments is positive and the Zeno phenomenon is naturally eliminated. Moreover, the exponential convergence of the MASs is ensured and the external disturbance is rejected via utilizing the internal model (IM) principle. The proposed protocol is illustrated lastly by providing a specific example.