Tracking Control for Nonaffine Systems: A Self-Organizing Approximation Approach

被引：30

作者：

Dong, Wenjie ^{[1
]}

Zhao, Yuanyuan ^{[2
]}

Chen, Yiming ^{[3
]}

Farrell, Jay A. ^{[3
]}

机构：

[1] Univ Texas Pan Amer, Edinburg, TX 78539 USA

[2] Western Digital Corp, Lake Forest, CA 92630 USA

[3] Univ Calif Riverside, Dept Elect Engn, Riverside, CA 92521 USA

来源：

IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS | 2012年 / 23卷 / 02期

基金：

美国国家科学基金会;

关键词：

Adaptive nonlinear control; locally weighted learning; nonaffine systems; self-organizing approximation; NET ROBOT CONTROLLER; ADAPTIVE-CONTROL; NONLINEAR-SYSTEMS; NEURAL-NETWORKS; UNCERTAIN SYSTEMS; OUTPUT-FEEDBACK; PERFORMANCE;

D O I：

10.1109/TNNLS.2011.2178509

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 considers tracking control for single-input, single-output nonaffine dynamic systems. A performance-dependent self-organizing approximation-based approach is proposed. The designer specifies a positive tracking error criterion. The self-organizing approximation-based controller then monitors the tracking performance and adds basis elements only as needed to achieve the tracking specification. Even though the system is not affine, the approach is defined such that the approximated function is independent of the control variable u. Stability is proved and the self-organization is derived in a Lyapunov-based methodology. To illustrate certain novel aspects of the proposed controller, a numerical example is included.

引用

页码：223 / 235

页数：13

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