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Reaching a stochastic consensus in the noisy networks of linear MIMO agents:Dynamic output-feedback and convergence rate
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作者 WANG YunPeng CHENG Long +2 位作者 YANG ChenGuang HOU ZengGuang TAN Min 《Science China(Technological Sciences)》 SCIE EI CAS CSCD 2016年第1期45-54,共10页
This paper addresses the leader-following consensus problem of linear multi-agent systems(MASs) with communication noise. Each agent's dynamical behavior is described by a linear multi-input and multi-output(MIMO)... This paper addresses the leader-following consensus problem of linear multi-agent systems(MASs) with communication noise. Each agent's dynamical behavior is described by a linear multi-input and multi-output(MIMO) system, and the agent's full state is assumed to be unavailable. To deal with this challenge, a state observer is constructed to estimate the agent's full state. A dynamic output-feedback based protocol that is based on the estimated state is proposed. To mitigate the effect of communication noise, noise-attenuation gains are also introduced into the proposed protocol. In this study, each agent is allowed to have its own noise-attenuation gain. It is shown that the proposed protocol can solve the mean square leader-following consensus problem of a linear MIMO MAS. Moreover, if all noise-attenuation gains are of Q(t-β), where b∈(0,1), the convergence rate of the MAS can be quantitatively analyzed. It turns out that all followers' states converge to the leader's state in the mean square sense at a rate of O(t-β). 展开更多
关键词 multi-agent system mean square consensus communication noise noise-attenuation gain convergence rate
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