Mean-Square Consensus for Heterogeneous Multi-Agent Systems With Packet Losses

This brief studies the mean-square consensus problem for discrete-time heterogeneous multi-agent systems, where the state information is received with varying dropout uncertainty, which leads to heterogeneous observations. The main challenge addressed in this brief is the design of the state estimator and the controller for each agent with different dynamics subject to multiplicative noise. The optimal estimator is designed based on the measurement value to estimate each agent's state, and a novel distributed dynamic output feedback control protocol is first developed based on the given estimator. A sufficient solvability condition for achieving mean-square consensus in heterogeneous multi-agent systems is derived. Finally, simulation results show the effectiveness of the proposed control strategy.