%0 Journal Article
%T Asynchronous randomized Gossip consensus algorithm with nonuniform-selected probability and optimizing<br>非均匀选择概率下异步随机Gossip共识算法及优化
%A WANG Chang-cheng
%A QI Guo-qing
%A LI Yin-ya
%A SHENG An-dong
%A <br>王长城
%A 戚国庆
%A 李银伢
%A 盛安冬
%J 控制理论与应用
%D 2013
%I 
%X The traditional asynchronous randomized Gossip consensus algorithm is founded on the basis of the uniformselected probability time model which does not consider the impact of topology on local information transfer. We introduce a more reasonable asynchronous randomized Gossip consensus algorithm with nonuniform-select probability, and analyze the convergence of the algorithm in probability sense. The convergence rate depends on the second largest eigenvalue of the probabilistic weighted matrix. An optimization algorithm for selecting probabilities is proposed by projection subgradient method. The numerical example indicates that the algorithm proposed can improve the convergence rate by optimizing the selection of probabilities for agents, and compensates for the traditional algorithm in optimizing communication matrix the disadvantages of dependence on the network topology.
%K multi-agent system
%K nonuniform-select probability
%K randomized Gossip algorithm
%K consensus
%K optimizing<br>多智能体系统
%K 非均匀选择概率
%K 随机Gossip算法
%K 一致性
%K 优化
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=970898A57DFC021F93AB51667BAED7F7&aid=B0A1562CFAEFEFB739E3AB5AE8A85E2F&yid=FF7AA908D58E97FA&vid=340AC2BF8E7AB4FD&iid=38B194292C032A66&sid=BF112261B65CB9C9&eid=31BCE06A2FD82A16&journal_id=1000-8152&journal_name=控制理论与应用&referenced_num=0&reference_num=0