BACKSTEPPING STATION-KEEPING CONTROL USING RECURRENT WAVELET FUZZY CMAC FOR BALL-DRI VEN CHAIRS

被引：0

作者：

Tsai, Ching-Chih ^{[1
]}

Ciou, Yi-Ping ^{[1
]}

Tai, Feng-Chun ^{[1
]}

Su, Shun-Feng ^{[2
]}

Lin, Chih-Min ^{[3
]}

机构：

[1] Natl Chung Hsing Univ, Dept Elect Engn, Taichung, Taiwan

[2] Natl Taiwan Univ Sci & Technol, Grad Inst Automat & Control, Taipei, Taiwan

[3] Yuan Ze Univ, Dept Elect Engn, Chungli 32003, Taiwan

来源：

PROCEEDINGS OF 2014 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS (ICMLC), VOL 2 | 2014年

关键词：

Backstepping; Ball-driven chair; Modeling; Recurrent Wavelet Fuzzy CMAC (RWFCMAC); Sliding-mode control; Station-keeping;

D O I：

暂无

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 an adaptive backstepping station-keeping control using recurrent wavelet fuzzy cerebella model articulation controller (RWFCMAq for omnidirectional ball-driven chairs used in indoor environments. Lagrangian mechanics is adopted to establish a coupled mathematical model of the vehicle; when the nutation angle is sufficiently small, this model is shown to be consistent with the well-known decoupled model under two special cases. Based on the derived model with uncertainties caused by different riders, an intelligent adaptive controller is developed by using RWFCMAC, aggregated hierarchical siding-mode control and backstepping control, in order to maintain the nutation angle at zero. The effectiveness and merit of the proposed controller are exemplified by conducting several simulations on the laboratory-built omnidirectional ball-riding vehicle.

引用

页码：721 / 727

页数：7

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