The Exponential Consensus of Linear Multi-Agent Systems with Binary-Valued Measurements and Markovian Switching Topologies

This paper studies consensus of linear multi-agent systems with binary-valued measurements and switching topologies. Unlike the existing consensus of multi-agent systems with binary-valued measurements, Markovian switching topology is introduced in this paper. A new algorithm is proposed to improve the consensus speed of multi-agent systems, with constant gains in both estimation and control, instead of time-varying gains. By analyzing the estimation error and the consensus error simultaneously, we prove that the proposed algorithm can make agents achieve consensus in a bouned range, and the consensus speed is negative exponential under certain conditions, which is faster than that in existing literature. Finally, simulation results are given to demonstrate the theoretical results.