Dynamic Maximum Consensus of Multi-Agent Systems with Unknown but Bounded Measurement Errors

In this paper, the dynamic maximum consensus problem of multi-agent systems with unknown but bounded measurement errors is studied. A local interaction protocol is proposed. In this problem, each agent is input an external reference signal, and its goal is to track the maximum value of all reference signals through local interaction between agents. Different from the existing works, the upper bounds of the measurement errors of each agent are allowed to be different from each other, and the external reference signal is dynamic. Due to the existence of unknown but bounded measurement errors, agents usually cannot achieve the control goal of tracking the maximum value of all dynamic reference signals indiscriminately. Consequently, the upper bounds of convergence time and tracking error are given. In addition, the upper bound of tracking error is given when the reference signal is constant. Finally, the simulation results verify the effectiveness of the proposed protocol.