Design of fuzzy sliding controller based on cerebellar learning model

Heng Kang Fan; Chih Ming Chen; Chin Ming Hong

doi:10.1007/978-3-540-48765-4_9

Design of fuzzy sliding controller based on cerebellar learning model

Heng Kang Fan, Chih Ming Chen, Chin Ming Hong

電機工程學系

研究成果: 書貢獻/報告類型 › 會議論文篇章

1 引文斯高帕斯（Scopus）

摘要

As to the control of fuzzy sliding mode, this paper proposes a cerebellar learning model for on-line learning of the controller. Fuzzy sliding mode has excellent robustness to the system uncertainty and immunity to the noise of the external noise. As for the cerebellar learning mode, it possesses the advantages of easy and fast correction. The combination of the two leads to the design of a fuzzy sliding mode controller with self-learning capability to improve the short-comings of difficulties in setting up the regulations of fuzzy control. It also improves the system stability and enhances the effectiveness of the controller.This paper describes the implementation of a fuzzy sliding controller with cerebellar learning mode. After system simulation and capability test, it is applied to the control of slew-up, stand-on and positioning of a 360 ° inverted pendulum.

原文	英語
主出版物標題	Multiple Approaches to Intelligent Systems - 12th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems IEA/AIE 1999, Proceedings
編輯	Ibrahim Imam, Yves Kodratoff, Ayman El-Dessouki, Moonis Ali
發行者	Springer Verlag
頁面	64-73
頁數	10
ISBN（列印）	3540660763, 9783540660767
DOIs	https://doi.org/10.1007/978-3-540-48765-4_9
出版狀態	已發佈 - 1999
事件	12th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, IEA/AIE 1999 - Cairo, 埃及持續時間: 1999 5月 31 → 1999 6月 3

出版系列

名字	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
卷	1611
ISSN（列印）	0302-9743
ISSN（電子）	1611-3349

會議

會議	12th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, IEA/AIE 1999
國家/地區	埃及
城市	Cairo
期間	1999/05/31 → 1999/06/03

ASJC Scopus subject areas

理論電腦科學
電腦科學(全部)

存取文件

10.1007/978-3-540-48765-4_9

其它文件與鏈接

引用此

Fan, H. K., Chen, C. M., & Hong, C. M. (1999). Design of fuzzy sliding controller based on cerebellar learning model. 於 I. Imam, Y. Kodratoff, A. El-Dessouki, & M. Ali (編輯), Multiple Approaches to Intelligent Systems - 12th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems IEA/AIE 1999, Proceedings (頁 64-73). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); 卷 1611). Springer Verlag. https://doi.org/10.1007/978-3-540-48765-4_9

Design of fuzzy sliding controller based on cerebellar learning model. / Fan, Heng Kang; Chen, Chih Ming; Hong, Chin Ming.
Multiple Approaches to Intelligent Systems - 12th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems IEA/AIE 1999, Proceedings. 編輯 / Ibrahim Imam; Yves Kodratoff; Ayman El-Dessouki; Moonis Ali. Springer Verlag, 1999. p. 64-73 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); 卷 1611).

研究成果: 書貢獻/報告類型 › 會議論文篇章

Fan, HK, Chen, CM & Hong, CM 1999, Design of fuzzy sliding controller based on cerebellar learning model. 於 I Imam, Y Kodratoff, A El-Dessouki & M Ali (編輯), Multiple Approaches to Intelligent Systems - 12th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems IEA/AIE 1999, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 卷 1611, Springer Verlag, 頁 64-73, 12th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, IEA/AIE 1999, Cairo, 埃及, 1999/05/31. https://doi.org/10.1007/978-3-540-48765-4_9

Fan HK, Chen CM, Hong CM. Design of fuzzy sliding controller based on cerebellar learning model. 於 Imam I, Kodratoff Y, El-Dessouki A, Ali M, 編輯, Multiple Approaches to Intelligent Systems - 12th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems IEA/AIE 1999, Proceedings. Springer Verlag. 1999. p. 64-73. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-540-48765-4_9

Fan, Heng Kang ; Chen, Chih Ming ; Hong, Chin Ming. / Design of fuzzy sliding controller based on cerebellar learning model. Multiple Approaches to Intelligent Systems - 12th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems IEA/AIE 1999, Proceedings. 編輯 / Ibrahim Imam ; Yves Kodratoff ; Ayman El-Dessouki ; Moonis Ali. Springer Verlag, 1999. 頁 64-73 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "As to the control of fuzzy sliding mode, this paper proposes a cerebellar learning model for on-line learning of the controller. Fuzzy sliding mode has excellent robustness to the system uncertainty and immunity to the noise of the external noise. As for the cerebellar learning mode, it possesses the advantages of easy and fast correction. The combination of the two leads to the design of a fuzzy sliding mode controller with self-learning capability to improve the short-comings of difficulties in setting up the regulations of fuzzy control. It also improves the system stability and enhances the effectiveness of the controller.This paper describes the implementation of a fuzzy sliding controller with cerebellar learning mode. After system simulation and capability test, it is applied to the control of slew-up, stand-on and positioning of a 360 ° inverted pendulum.",

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Design of fuzzy sliding controller based on cerebellar learning model

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