Neural net-based H∞ control for a class of nonlinear systems

被引：1
|
作者：
Lin, CL [1 ]
Lin, TY [1 ]
机构：
[1] Feng Chia Univ, Inst Automat Control Engn, Taichung 40724, Taiwan
来源：
NEURAL PROCESSING LETTERS | 2002年 / 15卷 / 02期
关键词：
multilayer neural network; stability; Lyapunov theory; H-infinity control theory; linear matrix inequality;
D O I：
10.1023/A:1015297019806
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
A novel neural net-based approach for H-infinity control design of a class of nonlinear continuous-time systems is presented. In the proposed frameworks, the nonlinear system models are approximated by multilayer neural networks. The neural networks are piecewisely interpolated to generate a linear differential inclusion models by which a linear state feedback H-infinity control law can be constructed. It is shown that finding the permissible control gain matrices can be transformed to a standard linear matrix inequality problem and solved using the available computer software.
引用
收藏
页码：157 / 177
页数：21
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