article

Decoupled fuzzy controller design with single-input fuzzy logic

Authors:

Shi-Yuan Chen,

Fang-Ming Yu,

Hung-Yuan ChungAuthors Info & Claims

Fuzzy Sets and Systems, Volume 129, Issue 3

Pages 335 - 342

https://doi.org/10.1016/S0165-0114(01)00130-0

Published: 01 August 2002 Publication History

Abstract

A decoupled fuzzy controller design with single-input fuzzy logic is proposed. We will utilize the approach of the single-input fuzzy logic to explore the fourth-order nonlinear systems. In addition, five fuzzy rules are given to control a class of fourth-order nonlinear systems. Using this approach, the system can achieve asymptotic stability and the response of system will converge faster than that of previous reports. Two simulation studies of a cart-pole system and a ball-beam system are presented to demonstrate the effectiveness of the method.

References

[1]

{1} G. Bartolini, A. Ferrara, Multivariable fuzzy sliding mode control by using a simplex of control vectors, in: S.G. Tzafestas, A.N. Venetsanopoulos (Eds.), Fuzzy Reasoning in Information, Decision, and Control Systems, Kluwer, Amsterdam, The Netherlands, 1994, pp. 307-328.

Google Scholar

[2]

{2} C.L. Chen, P.C. Chen, C.K. Chen, Analysis and design of fuzzy control system, Fuzzy Sets Systems 57 (2) (1993) 125-140.

Digital Library

Google Scholar

[3]

{3} Byung-Jae Choi, Seong-Woo Kwak, Byung Kook Kim, Design of a single-input fuzzy logic controller and its properties, Fuzzy Sets and Systems 106 (1999) 299-308.

Digital Library

Google Scholar

[4]

{4} S. Galicher, L. Foulloy, Fuzzy controllers: synthesis equivalence, IEEE Trans. Fuzzy Systems 3 (1995) 140-148.

Digital Library

Google Scholar

[5]

{5} J.S. Glower, J. Munighan, Design fuzzy controllers from a variable structures standpoint, IEEE Trans. Fuzzy Systems 5 (1) (1997) 138-144.

Digital Library

Google Scholar

[6]

{6} Guang-Chyan Hwang, Shih-Chang Lin, A stability approach to fuzzy control design for nonlinear systems, Fuzzy Sets and Systems 48 (1992) 279-287.

Digital Library

Google Scholar

[7]

{7} Y.R. Hwang, M. Tomizuka, Fuzzy smoothing algorithms for variable structure systems, IEEE Trans. Fuzzy Systems 2 (1994) 277-284.

Digital Library

Google Scholar

[8]

{8} Sung-Woo Kim, Ju-Jang Lee, Design of a fuzzy controller with fuzzy sliding surface, Fuzzy Sets and Systems 71 (1995) 359-367.

Digital Library

Google Scholar

[9]

{9} C.C. Kung, S.C. Lin, Fuzzy controller design: a sliding mode approach, in: S.G. Tzafestas, A.N. Venetsanopoulos (Eds.), Fuzzy Reasoning in Information, Decision, and Control Systems, Kluwer, Amsterdam, The Netherlands, 1994, pp. 277-306.

Google Scholar

[10]

{10} K. Liu, F.L. Lewis, Some issues about fuzzy control, in: proc. IEEE Conf. Decision Control, San Antonio, TX, Vol. 2, December 1993, pp. 1743-1748.

Crossref

Google Scholar

[11]

{11} Ji-Chang Lo, Ya-Hui Kuo, Decoupled fuzzy sliding-mode control, IEEE Trans. Fuzzy Systems 6 (3) (1998) 426-435.

Digital Library

Google Scholar

[12]

{12} E.H. Mamdani, Applications of fuzzy algorithms for simple dynamic plants, Proc. IEE, Vol. 121, 1974, pp. 1585-1588.

Crossref

Google Scholar

Cited By

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Gegov ASanders DVatchova B(2017)Aggregation of inconsistent rules for fuzzy rule base simplificationInternational Journal of Knowledge-based and Intelligent Engineering Systems10.3233/KES-17035821:3(135-145)Online publication date: 1-Jan-2017
https://dl.acm.org/doi/10.3233/KES-170358
Gegov AArabikhan FSanders D(2015)Rule base simplification in fuzzy systems by aggregation of inconsistent rulesJournal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology10.5555/2740244.274027728:3(1331-1343)Online publication date: 1-May-2015
https://dl.acm.org/doi/10.5555/2740244.2740277
Gegov AGobalakrishnan NSanders D(2014)Rule base compression in fuzzy systems by filtration of non-monotonic rulesJournal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology10.5555/2684890.268493027:4(2029-2043)Online publication date: 1-Jul-2014
https://dl.acm.org/doi/10.5555/2684890.2684930
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Index Terms

Decoupled fuzzy controller design with single-input fuzzy logic
1. Computing methodologies
  1. Artificial intelligence
    1. Control methods
      1. Computational control theory
    2. Knowledge representation and reasoning
      1. Probabilistic reasoning
      2. Vagueness and fuzzy logic

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Information

Published In

Fuzzy Sets and Systems Volume 129, Issue 3

Control and applications

August 2002

136 pages

ISSN:0165-0114

Issue’s Table of Contents

Publisher

Elsevier North-Holland, Inc.

United States

Publication History

Published: 01 August 2002

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Gegov ASanders DVatchova B(2017)Aggregation of inconsistent rules for fuzzy rule base simplificationInternational Journal of Knowledge-based and Intelligent Engineering Systems10.3233/KES-17035821:3(135-145)Online publication date: 1-Jan-2017
https://dl.acm.org/doi/10.3233/KES-170358
Gegov AArabikhan FSanders D(2015)Rule base simplification in fuzzy systems by aggregation of inconsistent rulesJournal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology10.5555/2740244.274027728:3(1331-1343)Online publication date: 1-May-2015
https://dl.acm.org/doi/10.5555/2740244.2740277
Gegov AGobalakrishnan NSanders D(2014)Rule base compression in fuzzy systems by filtration of non-monotonic rulesJournal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology10.5555/2684890.268493027:4(2029-2043)Online publication date: 1-Jul-2014
https://dl.acm.org/doi/10.5555/2684890.2684930
Gegov ASanders DVatchova B(2014)Complexity management methodology for fuzzy systems with feedback rule basesJournal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology10.5555/2596321.259636426:1(451-464)Online publication date: 1-Jan-2014
https://dl.acm.org/doi/10.5555/2596321.2596364
Mahmoodabadi MMomennejad SBagheri A(2014)Online optimal decoupled sliding mode control based on moving least squares and particle swarm optimizationInformation Sciences: an International Journal10.1016/j.ins.2014.01.027268(342-356)Online publication date: 1-Jun-2014
https://dl.acm.org/doi/10.1016/j.ins.2014.01.027
Yorgancioglu FKomurcugil H(2010)Decoupled sliding-mode controller based on time-varying sliding surfaces for fourth-order systemsExpert Systems with Applications: An International Journal10.1016/j.eswa.2010.03.04937:10(6764-6774)Online publication date: 1-Oct-2010
https://dl.acm.org/doi/10.1016/j.eswa.2010.03.049
Bagheri AMoghaddam J(2009)Simulation and tracking control based on neural-network strategy and sliding-mode control for underwater remotely operated vehicleNeurocomputing10.1016/j.neucom.2008.06.00872:7-9(1934-1950)Online publication date: 1-Mar-2009
https://dl.acm.org/doi/10.1016/j.neucom.2008.06.008
Oh SJung SPedrycz W(2009)Design of optimized fuzzy cascade controllers by means of Hierarchical Fair Competition-based Genetic AlgorithmsExpert Systems with Applications: An International Journal10.1016/j.eswa.2009.03.02736:9(11641-11651)Online publication date: 1-Nov-2009
https://dl.acm.org/doi/10.1016/j.eswa.2009.03.027
Hung LLin HChung H(2007)New adaptive fuzzy sliding-mode control for uncertain non-linear systemsInternational Journal of Computer Applications in Technology10.5555/1357559.135756028:4(229-239)Online publication date: 1-Jul-2007
https://dl.acm.org/doi/10.5555/1357559.1357560
Hung LChung H(2007)Decoupled control using neural network-based sliding-mode controller for nonlinear systemsExpert Systems with Applications: An International Journal10.1016/j.eswa.2006.02.02432:4(1168-1182)Online publication date: 1-May-2007
https://dl.acm.org/doi/10.1016/j.eswa.2006.02.024
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Abstract

References

Cited By

Index Terms

Recommendations

The robust stability of seesaw system with fuzzy logic control

Adaptive fuzzy control for multi-input multi-output nonlinear systems with unknown dead-zone inputs

Fuzzy sliding mode control for an under-actuated system with mismatched uncertainties

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