Robust Cooperative Control for Nonlinear Multi-agent Systems with Input-Disturbances via Adaptive Dynamic Programming

被引：0

作者：

Qu, Qiuxia ^{[1
]}

Wang, Juan ^{[1
]}

QiongXia ^{[1
]}

Sun, Liangliang ^{[1
]}

Cui, Yang ^{[2
]}

机构：

[1] Shenyang Jianzhu Univ, Sch Informat & Control Engn, Shenyang 110168, Peoples R China

[2] Univ Sci & Technol Liaoning, Sch Elect & Informat Engn, Anshan 114051, Peoples R China

来源：

PROCEEDINGS OF THE 33RD CHINESE CONTROL AND DECISION CONFERENCE (CCDC 2021) | 2021年

基金：

中国国家自然科学基金;

关键词：

Adaptive dynamic programming; Input-disturbance; Leader-following consensus problem; Multi-agent systems; Nash equilibrium; Neural network; STABILIZATION; CONSENSUS; GAMES;

D O I：

10.1109/CCDC52312.2021.9601887

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Considering the leader-following consensus problem for the nonlinear multi-agent systems with bounded input-disturbances under fixed topology, a novel distributed robust protocol is designed to guarantee all followers synchronize to the leader by investigating the gain of the Nash Equilibrium. The robustness restrictions are given through Lyapunov theory. To get the Nash solution, critic neural networks are trained based on adaptive dynamic programming algorithm in an online and forward-in-time manner to solve the coupled Hamilton-Jacobi equations. An additional term is added to the neural network weight tuning law to avoid the requirement for the initial admissible control law.

引用

页码：3715 / 3720

页数：6

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