Several extensions in methods for adaptive output feedback control

被引：21

作者：

Kim, Nakwan ^{[1
]}

Calise, Anthony J.

机构：

[1] Chungnam Natl Univ, Taejon 305764, South Korea

[2] Georgia Inst Technol, Atlanta, GA 30332 USA

来源：

IEEE TRANSACTIONS ON NEURAL NETWORKS | 2007年 / 18卷 / 02期

关键词：

e-modification; neural networks (NNs); nonlinear adaptive control; output feedback; parametric uncertainty;

D O I：

10.1109/TNN.2006.885120

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Several extensions to neural network (NN)-based adaptive output feedback control of nonlinear systems are developed. An extension from linearly to nonlinearly parameterized NNs is given for a direct adaptive output feedback approach. An extension that permits the introduction of e-modificaition in both the direct adaptive approach and an error-observer-based approach is also given. Finally, for the case of nonaffine systems, we eliminate a fixed-point assumption that has appeared in earlier work.

引用

页码：482 / 494

页数：13

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