Almost Sure 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.Differently from the case with non-state-dependent measurement noises,we show that a negative control gain,though can not ensure mean square consensus,may ensure almost sure consensus.This tells us that the relative-state-dependent measurement noises will sometimes be helpful for the almost sure consensus of the network.For symmetric measurement models,the almost sure convergence rate is estimated by the Iterated Logarithm Law of Brownian motions.

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

作者: LI Tao WU Fuke

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.

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: 1242-1246

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）