Iterative learning consensus tracking control for a class of multi-agent systems with output saturation

被引：7

作者：

Liang J.-Q. ^{[1
]}

Bu X.-H. ^{[1
]}

Liu J. ^{[1
]}

Qian W. ^{[1
]}

机构：

[1] School of Electrical Engineering and Automation, Henan Polytechnic University, Jiaozuo, 454000, Henan

来源：

Kongzhi Lilun Yu Yingyong/Control Theory and Applications | 2018年 / 35卷 / 06期

基金：

中国国家自然科学基金;

关键词：

Consensus; Distributed algorithms; Iterative learning control(ILC); Multi-agent systems(MAS); Output saturation; Randomly switching topologies;

D O I：

10.7641/CTA.2017.70659

中图分类号：

学科分类号：

摘要：

In this paper, a distributed iterative learning control algorithm is proposed to the consensus tracking control problem of multi-agent systems with output saturation. First, it is assumed that the considered multi-agent system has a fixed communication topology and only a part of agents can obtain the desired trajectory information. The P-type iterative learning control law is developed from the consensus tracking error that constructed by the constraint output. Then, a sufficient condition of the algorithm is given by using the approach of contraction mapping, and the theoretical convergence analysis of the tracking error is also provided. Finally, the theoretical results are extended into multi-agent systems with randomly switching topology. Simulation results further validate the effectiveness of the proposed algorithm. © 2018, Editorial Department of Control Theory & Applications South China University of Technology. All right reserved.

引用

页码：786 / 794

页数：8

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