Design a Fuzzy Logic Based Speed Controller for DC Motor with Genetic Algorithm Optimization

Abstract:

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In this paper, an intelligent speed controller for DC motor is designed by combination of the fuzzy logic and genetic algorithms. First, the speed controller is designed according to fuzzy rules such that the DC drive is fundamentally robust. Then, to improve the DC drive performance, parameters of the fuzzy speed controller are optimized by using the genetic algorithm. Simulation works in MATLAB environment demonstrate that the genetic optimized fuzzy speed controller became very strong, gives very good results and possesses good robustness.

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Periodical:

Edited by:

Wu Fan

Pages:

2324-2330

DOI:

10.4028/www.scientific.net/AMM.110-116.2324

Citation:

N. Changizi et al., "Design a Fuzzy Logic Based Speed Controller for DC Motor with Genetic Algorithm Optimization", Applied Mechanics and Materials, Vols. 110-116, pp. 2324-2330, 2012

Online since:

October 2011

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$35.00

[1] Raghavan S., Digital control for speed and position of a DC motor, MS Thesis, Texas A&M University, Kingsville, August (2005).

[2] Yen J., Langari R., Fuzzy logic: Intelligence, Control, and Information, Prentice-Hall, (1999).

[3] Swarup K.S., Yamashiro S., Unit commitment solution methodology using genetic algorithm, IEEE Trans: Power System, vol. 17, p.87–91, (2002).

DOI: 10.1109/59.982197

[4] Gen M., Cheng R., Genetic Algorithms and Engineering Design, John Wiley and Sons, INC, (1997).

[5] Belarbi K., Titel F., Genetic Algorithm for the Design of a Class of Fuzzy Controllers An Alternative, IEEE Trans: On Fuzzy Systems, Vol. 8, No. 3 pp.398-405, (2000).

DOI: 10.1109/91.868946

[6] Zhou Y. S., Lai L. Y., Optimal Design for Fuzzy Controllers by Genetic Algorithms, IEEE Trans: On Industry Application, Vol. 36, No. 1 pp.93-97, (2000).

[7] Hazzab A., Bousserhane I.K., Kamli M., Design of fuzzy sliding mode controller by genetic algorithms for induction machine speed control, International Journal of Emerging Electric Power System, Vol. 01, No. 02, (2004).

DOI: 10.2202/1553-779x.1016

[8] Lee M., Takagi H., Integrating design stages of fuzzy systems using genetic algorithms, Proc. 2nd IEEE Internat. Conf. on Fuzzy Systems, San Francisco, CA, pp.612-617, (1993).

[9] Foran J., Optimisation of a Fuzzy Logic Controller Using Genetic Algorithms, Doctorat, Texas University of America, USA, (2002).

[10] Halila A., Étude des machines à courant continu, MS Thesis, University of LAVAL, (Text in French), May (2001).

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