Stochastic bounded consensus tracking of leader-follower multi-agent systems with measurement noises and sampled-data

被引：0

作者：

吴治海 ^{[1
]}

彭力 ^{[1
,2
]}

谢林柏 ^{[1
]}

闻继伟 ^{[1
]}

机构：

[1] The Key Laboratory for Advanced Process Control of Light Industry of the Ministry of Education,School of Internet of Things Engineering,Jiangnan University

[2] The State Key Laboratory for Digital Manufacturing Equipment and Technology,School of Mechanical Science and Engineering,Huazhong University of Science and Technology

来源：

Chinese Physics B | 2012年 / 12期

基金：

中国国家自然科学基金; 中央高校基本科研业务费专项资金资助;

关键词：

leader-follower multi-agent systems; stochastic bounded consensus tracking; measurement noises; sampled-data;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper is concerned with the stochastic bounded consensus tracking problems of leader-follower multi-agent systems,where the control input of an agent can only use the information measured at the sampling instants from its neighbours or the virtual leader with a time-varying reference state,and the measurements are corrupted by random noises.The probability limit theory and the algebra graph theory are employed to derive the necessary and sufficient conditions guaranteeing the mean square bounded consensus tracking.It is shown that the maximum allowable upper boundary of the sampling period simultaneously depends on the constant feedback gains and the network topology. Furthermore,the effects of the sampling period on the tracking performance are analysed.It turns out that from the view point of the sampling period,there is a trade-off between the tracking speed and the static tracking error. Simulations are provided to demonstrate the effectiveness of the theoretical results.

引用

页码：568 / 575

页数：8