Leader-following consensus of data-sampled multi-agent systems with stochastic switching topologies

This paper investigates the leader-following consensus problem for multi-agent systems with Markovian switching topologies in a sampled-data setting. We study two algorithms corresponding to the case where the leader׳s state is time varying or time invariant. With a time-varying leader׳s state, we present necessary and sufficient conditions for boundedness of the tracking error systems. With a time-invariant leader׳s state, we present necessary and sufficient conditions for mean-square stability of the tracking error systems. An optimization algorithm is given to derive the allowable control gains or the feasible sampling period. Simulation examples are presented to show the usefulness of the results.