Observer-based output feedback containment control of a class of nonlinear multi-agent systems via adaptive neural control method

被引：0
|
作者：
Xu, Tingru [1 ]
Lyu, Jianting [1 ,2 ]
Yang, Xinrong [1 ,2 ]
Wang, Xin [1 ,2 ]
机构：
[1] Heilongjiang Univ, Sch Math Sci, Harbin 150080, Peoples R China
[2] Heilongjiang Univ, Heilongjiang Prov Key Lab Theory & Computat Compl, Harbin 150080, Peoples R China
来源：
PROCEEDINGS OF THE 32ND 2020 CHINESE CONTROL AND DECISION CONFERENCE (CCDC 2020) | 2020年
基金：
中国国家自然科学基金;
关键词：
Containment control; nonlinear multi-agent system; neural networks; TRACKING CONTROL; CONSENSUS; DYNAMICS;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper investigates containment control problem for a class of nonlinear multi-agent systems with multiple dynamic leaders, where the condition of zero control input for leader is not assumed. The dynamics of the each subsystem are assumed to be unknown and are estimated using neural networks. A local observer is used to estimate the states and an observer-based neural network controller is designed to guarantee that followers converge to the convex hull spanned by the leaders. Numerical simulations are finally given to show the effectiveness of the obtained results.
引用
收藏
页码：1738 / 1743
页数：6
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