Mean Square Averaging With Relative-State-Dependent Measurement Noises and Linear Noise Intensity Functions

摘要：

　　In this paper,we consider the distributed averaging of high-dimensional first-order agents with relative-state-dependent measurement noises.Each agent can measure or receive its neighbors state information with random noises,whose intensity is a linear vector-valued function of agents relative states.By the tools of stochastic differential equations and algebraic graph theory,we give some necessary and sufcient conditions in terms of the control gain matrix,the noise intensity function and the network topology graph to ensure mean square average-consensus.Especially,for the case with independent and homogeneous channels,if the noise intensity grows with the rate σ,then 0 < k < N/(N-1)σ2 is a necessary and sufficient condition on the control gain k to ensure mean square average-consensus.

关键词： Multi-Agent System Distributed Averaging Consensus Measurement Noise

作者: LI Tao WU Fuke ZHANG Ji-Feng

作者单位: Shanghai Key Laboratory of Power Station Automation Technology,School of Mechatronic Engineering and School of Mathematics and Statistics,Huazhong University of Science and Technology,Wuhan 430074,P.R. Key Laboratory of Systems and Control,Academy of Mathematics and Systems Science,Chinese Academy of

会议类型: 国际会议

会议名称: The 33th Chinese Control Conference第33届中国控制会议

会议地点: 南京

会议语种:英文

页码: 1179-1183

在线出版日期: 2014-07-28（万方平台首次上网日期，不代表论文的发表时间）