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Distributed Robust Dynamic Weighted Average-tracking with Dynamic Event-triggered Communication

In this paper, a novel robust dynamic weighted average-tracking algorithm is proposed to achieve accurate tracking of weighted average value of all time-varying reference signals in the network, which is robust to network disruptions. The stability of the algorithm is analyzed, and the finite-time convergence of the algorithm is proved by constructing a Lyapunov function. Since this robust algorithm requires continuous communication between agents, a new dynamic event-triggered communication scheme to reduce the communication between agents is introduced, and its stability is analyzed . It is shown that the event-triggered algorithm is asymptotically stable and free of Zeno behavior. Numerical simulation results verify the effectiveness of the robust dynamic weighted average-tracking algorithm and the event-triggered algorithm.