CONSENSUS CONTROL FOR LEADER-FOLLOWING MULTI-AGENT SYSTEMS WITH MEASUREMENT NOISES

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This work is conced with consensus control for a class of leader-following multi-agent systems (MASs). The information that each agent received is corrupted by measurement noises. To reduce the impact of noises on consensus, time-varying consensus gains are adopted, based on which consensus protocols are designed. By using the tools of stochastic analysis and algebraic graph theory, a sufficient condition is obtained for the protocol to ensure strong mean square consensus under the fixed topologies. This condition is shown to be necessary and sufficient in the noise-free case. Furthermore, by using a common Lyapunov function, the result is extended to the switching topology case.
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