Nonlinear adaptive control using networks of piecewise linear approximators

被引:53
作者
Choi, JY [1 ]
Farrell, JA
机构
[1] Seoul Natl Univ, ASRI, ERC ACI, Sch Elect Engn, Seoul 151, South Korea
[2] Univ Calif Riverside, Dept Elect Engn, Riverside, CA 92506 USA
来源
IEEE TRANSACTIONS ON NEURAL NETWORKS | 2000年 / 11卷 / 02期
关键词
adaptive control; fuzzy control; iterative learning control; neural control; nonlinear control; repetitive control;
D O I
10.1109/72.839009
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 presents a stable nonparametric adaptive control approach using a piecewise local linear approximator. The continuous piecewise linear approximator is developed and its universal approximation capability is proved. The controller architecture is based on adaptive feedback linearization plus sliding mode control. A time varying activation region is introduced for efficient self-organization of the approximator during operation. We modify the adaptive control approach for piecewise linens approximation and self-organizing structures. In addition, we provide analyses of asymptotic stability of the tracking error and parameter convergence for the proposed adaptive control scheme with the on-line self-organizing structure, The method with a deadzone is also discussed to prevent a high-frequency input which might excite the unmodeled dynamics in practical applications. The application of the piecewise linear adaptive control method is demonstrated by a computational simulation.
引用
收藏
页码:390 / 401
页数:12
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