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

Department of Electrical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Citation (Scopus)

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.

Original language	English
Title of host publication	Multiple Approaches to Intelligent Systems - 12th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems IEA/AIE 1999, Proceedings
Editors	Ibrahim Imam, Yves Kodratoff, Ayman El-Dessouki, Moonis Ali
Publisher	Springer Verlag
Pages	64-73
Number of pages	10
ISBN (Print)	3540660763, 9783540660767
DOIs	https://doi.org/10.1007/978-3-540-48765-4_9
Publication status	Published - 1999
Event	12th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, IEA/AIE 1999 - Cairo, Egypt Duration: 1999 May 31 → 1999 Jun 3

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	1611
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	12th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, IEA/AIE 1999
Country/Territory	Egypt
City	Cairo
Period	1999/05/31 → 1999/06/03

Keywords

Cerebellar model articulation controller
Fuzzy control
Inverted pendulum
Sliding mode
Variable structure system

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Access to Document

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

Cite this

Fan, H. K., Chen, C. M., & Hong, C. M. (1999). Design of fuzzy sliding controller based on cerebellar learning model. In I. Imam, Y. Kodratoff, A. El-Dessouki, & M. Ali (Eds.), Multiple Approaches to Intelligent Systems - 12th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems IEA/AIE 1999, Proceedings (pp. 64-73). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 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. ed. / 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); Vol. 1611).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Fan, HK, Chen, CM & Hong, CM 1999, Design of fuzzy sliding controller based on cerebellar learning model. in I Imam, Y Kodratoff, A El-Dessouki & M Ali (eds), 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), vol. 1611, Springer Verlag, pp. 64-73, 12th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, IEA/AIE 1999, Cairo, Egypt, 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. In Imam I, Kodratoff Y, El-Dessouki A, Ali M, editors, 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. editor / Ibrahim Imam ; Yves Kodratoff ; Ayman El-Dessouki ; Moonis Ali. Springer Verlag, 1999. pp. 64-73 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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AB - 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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