Adaptive control using the fuzzy basis function with robust design

Nien Tsu Hu; Ter Feng Wu; Pu Sheng Tsai; Jen Yang Chen

doi:10.1109/IIH-MSP.2014.242

Adaptive control using the fuzzy basis function with robust design

Nien Tsu Hu
, Ter Feng Wu
, Pu Sheng Tsai
, Jen Yang Chen

Graduate Institute of Automation Technology

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

Abstract

This paper presents the structure of model reference adaptive control based on fuzzy basis function. Initially, the techniques of fuzzy basis function are introduced to approach uncertain (or unknown) nonlinear systems. In addition, a heuristic adaptive algorithm, which is robust feature under the Lyapunov stability criterion is developed so that the output of the plant tracks a reference model output or follows another signal. As a result, the linear combination of the fuzzy basis function can approximate any nonlinear continuous function to any arbitrary accuracy that is substantiated by the Stone Weierstrass theorem. Two examples are given to illustrate the performance of the proposed method. Computer simulation results confirm that the proposed method not only satisfied tracking performance, but it also is vigorously robust.

Original language	English
Title of host publication	Proceedings - 2014 10th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIH-MSP 2014
Editors	Junzo Watada, Akinori Ito, Jeng-Shyang Pan, Han-Chieh Chao, Chien-Ming Chen
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	966-969
Number of pages	4
ISBN (Electronic)	9781479953905
DOIs	https://doi.org/10.1109/IIH-MSP.2014.242
State	Published - 24 Dec 2014
Event	10th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIH-MSP 2014 - Kitakyushu, Japan Duration: 27 Aug 2014 → 29 Aug 2014

Publication series

Name	Proceedings - 2014 10th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIH-MSP 2014

Conference

Conference	10th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIH-MSP 2014
Country/Territory	Japan
City	Kitakyushu
Period	27/08/14 → 29/08/14

Bibliographical note

Publisher Copyright:
© 2014 IEEE.

Keywords

fuzzy basis function
lyapunov stability criterion
model reference adaptive control
robust control

Access to Document

10.1109/IIH-MSP.2014.242

Cite this

Hu, N. T., Wu, T. F., Tsai, P. S., & Chen, J. Y. (2014). Adaptive control using the fuzzy basis function with robust design. In J. Watada, A. Ito, J.-S. Pan, H.-C. Chao, & C.-M. Chen (Eds.), Proceedings - 2014 10th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIH-MSP 2014 (pp. 966-969). Article 6998488 (Proceedings - 2014 10th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIH-MSP 2014). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IIH-MSP.2014.242

Hu, Nien Tsu ; Wu, Ter Feng ; Tsai, Pu Sheng et al. / Adaptive control using the fuzzy basis function with robust design. Proceedings - 2014 10th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIH-MSP 2014. editor / Junzo Watada ; Akinori Ito ; Jeng-Shyang Pan ; Han-Chieh Chao ; Chien-Ming Chen. Institute of Electrical and Electronics Engineers Inc., 2014. pp. 966-969 (Proceedings - 2014 10th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIH-MSP 2014).

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abstract = "This paper presents the structure of model reference adaptive control based on fuzzy basis function. Initially, the techniques of fuzzy basis function are introduced to approach uncertain (or unknown) nonlinear systems. In addition, a heuristic adaptive algorithm, which is robust feature under the Lyapunov stability criterion is developed so that the output of the plant tracks a reference model output or follows another signal. As a result, the linear combination of the fuzzy basis function can approximate any nonlinear continuous function to any arbitrary accuracy that is substantiated by the Stone Weierstrass theorem. Two examples are given to illustrate the performance of the proposed method. Computer simulation results confirm that the proposed method not only satisfied tracking performance, but it also is vigorously robust.",

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Hu, NT, Wu, TF, Tsai, PS & Chen, JY 2014, Adaptive control using the fuzzy basis function with robust design. in J Watada, A Ito, J-S Pan, H-C Chao & C-M Chen (eds), Proceedings - 2014 10th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIH-MSP 2014., 6998488, Proceedings - 2014 10th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIH-MSP 2014, Institute of Electrical and Electronics Engineers Inc., pp. 966-969, 10th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIH-MSP 2014, Kitakyushu, Japan, 27/08/14. https://doi.org/10.1109/IIH-MSP.2014.242

Adaptive control using the fuzzy basis function with robust design. / Hu, Nien Tsu; Wu, Ter Feng; Tsai, Pu Sheng et al.
Proceedings - 2014 10th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIH-MSP 2014. ed. / Junzo Watada; Akinori Ito; Jeng-Shyang Pan; Han-Chieh Chao; Chien-Ming Chen. Institute of Electrical and Electronics Engineers Inc., 2014. p. 966-969 6998488 (Proceedings - 2014 10th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIH-MSP 2014).

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

TY - GEN

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AU - Wu, Ter Feng

AU - Tsai, Pu Sheng

AU - Chen, Jen Yang

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N2 - This paper presents the structure of model reference adaptive control based on fuzzy basis function. Initially, the techniques of fuzzy basis function are introduced to approach uncertain (or unknown) nonlinear systems. In addition, a heuristic adaptive algorithm, which is robust feature under the Lyapunov stability criterion is developed so that the output of the plant tracks a reference model output or follows another signal. As a result, the linear combination of the fuzzy basis function can approximate any nonlinear continuous function to any arbitrary accuracy that is substantiated by the Stone Weierstrass theorem. Two examples are given to illustrate the performance of the proposed method. Computer simulation results confirm that the proposed method not only satisfied tracking performance, but it also is vigorously robust.

AB - This paper presents the structure of model reference adaptive control based on fuzzy basis function. Initially, the techniques of fuzzy basis function are introduced to approach uncertain (or unknown) nonlinear systems. In addition, a heuristic adaptive algorithm, which is robust feature under the Lyapunov stability criterion is developed so that the output of the plant tracks a reference model output or follows another signal. As a result, the linear combination of the fuzzy basis function can approximate any nonlinear continuous function to any arbitrary accuracy that is substantiated by the Stone Weierstrass theorem. Two examples are given to illustrate the performance of the proposed method. Computer simulation results confirm that the proposed method not only satisfied tracking performance, but it also is vigorously robust.

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Hu NT, Wu TF, Tsai PS, Chen JY. Adaptive control using the fuzzy basis function with robust design. In Watada J, Ito A, Pan JS, Chao HC, Chen CM, editors, Proceedings - 2014 10th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIH-MSP 2014. Institute of Electrical and Electronics Engineers Inc. 2014. p. 966-969. 6998488. (Proceedings - 2014 10th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIH-MSP 2014). doi: 10.1109/IIH-MSP.2014.242

Adaptive control using the fuzzy basis function with robust design

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Keywords

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