Decentralized Stabilization for Nonlinear Systems with Unknown Mismatched Interconnections

被引：0

作者：

Zhao, Bo ^{[1
]}

Wang, Ding ^{[1
]}

Shi, Guang ^{[1
]}

Liu, Derong ^{[2
]}

Li, Yuanchun ^{[3
]}

机构：

[1] Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China

[2] Univ Sci & Technol Beijing, Sch Automat & Elect Engn, Beijing 100083, Peoples R China

[3] Changchun Univ Technol, Dept Control Sci & Engn, Changchun 130012, Peoples R China

来源：

NEURAL INFORMATION PROCESSING, ICONIP 2016, PT III | 2016年 / 9949卷

关键词：

Adaptive Dynamic Programming; Decentralized control; Unknown mismatched interconnections; Policy iteration;

D O I：

10.1007/978-3-319-46675-0_21

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 establishes a neural network and policy iteration based decentralized control scheme to stabilize large-scale nonlinear systems with unknown mismatched interconnections. For relaxing the common assumption of upper boundedness on interconnections when designing the decentralized optimal control, interconnections are approximated by neural networks with local signals of isolated subsystem and replaced reference signals of coupled subsystems. By using the adaptive estimation term, the performance index function is constructed to reflect the replacement error. Hereafter, it is proven that the developed decentralized optimal control policies can guarantee the closed-loop large-scale nonlinear system to be uniformly ultimately bounded. The effectiveness of the developed scheme is verified by a simulation example.

引用

页码：185 / 192

页数：8

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