Iterative learning consensus tracking control for distributed parameter models multi-agent with disturbance

被引：0
作者：
Huang, Qingnan [1 ]
Wang, Cun [1 ]
Dai, Xisheng [1 ,2 ]
机构：
[1] Guangxi Univ Sci & Technol, Sch Elect & Informat Engn, Liuzhou 545006, Peoples R China
[2] Guangxi Higher Educ Inst, Key Lab Ind Proc Intelligent Control Technol, Liuzhou 545006, Peoples R China
来源：
PROCEEDINGS OF THE 2019 31ST CHINESE CONTROL AND DECISION CONFERENCE (CCDC 2019) | 2019年
基金：
中国国家自然科学基金;
关键词：
Iterative learning control; distributed parameter model; multi-agent systems; disturbance; consensus tracking; SYSTEMS; NETWORKS;
D O I：
10.1109/ccdc.2019.8832989
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this paper, we study the consensus tracking for a class of distributed parameter models multi-agent systems. Taking into account the presence of disturbance in the system, using knowledge between neighboring agents, the virtual leader technology is introduced. A distributed P-type iterative learning control protocol is proposed. When the ILC law is applied to the system, the consensus tracking error between any two agents under the sense of L-2 norm can converge to zero after a sufficient number of iterations in a finite time interval. Finally, simulation examples demonstrate the effectiveness of the method.
引用
收藏
页码：3092 / 3097
页数：6
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