Probabilistic Algorithms for Multi-Agent Consensus Problems under Information Constraints

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In this research, we have studied cooperative control of multi-agent systems, which have recently gained much attention in the networked control area, and have focused on the consensus problem. We have dealt with cases where the constraints on the information exchange among agents are severe and have developed distributed algorithms to achieve consensus with as little communication as possible. Specifically, average consensus algorithms have been considered under directed connectivity structures with time-varying dynamics. Moreover, generalization to the so-called Kuramoto models of nonlinear oscillators has been obtained. For related studies on control systems under communication constraints, we have also derived limitations in data rates for stabilization of uncertain linear systems.