Optimal design of type_l TSK fuzzy controller using GRLA for AVR system

LESCOPE'07 - 2007 Large Engineering Systems Conference on Power Engineering

Volumn , Issue , 2007, Pages 106-111

  Naderi, F ^a   Gharaveisi, A A ^a   Rashidinejad, M ^a  

^a SHAHID BAHONAR UNIVERSITY OF KERMAN   (Iran)

Author keywords

[No Author keywords available]

Indexed keywords

CHROMOSOMES; CONTROL THEORY; ELECTRIC POTENTIAL; GENETIC ALGORITHMS; LEARNING ALGORITHMS; LEARNING SYSTEMS; MEMBERSHIP FUNCTIONS; PROPORTIONAL CONTROL SYSTEMS; REINFORCEMENT; THREE TERM CONTROL SYSTEMS; VOLTAGE REGULATORS;

AUTOMATIC VOLTAGE REGULATORS; COMPETITION AND COOPERATIONS; DESIGN METHODS; FUZZY CONTROLLERS; INPUT REFERENCES; MAMDANI; OPTIMAL DESIGNS; OUTPUT VARIABLES; PID CONTROLLERS;

FUZZY CONTROL;

EID: 48349139070     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/LESCPE.2007.4437362     Document Type: Conference Paper

References (18)

1. H. Lee-Kwang , O. R. Oh, Fuzzy theory and applications 1,11, Hongreung publishing co. (in Korean), 1990.
2. PROCYK, T.J., and MAMDANI, E.H.:'A linguistic self-organizing process controller', Automatica, 1979, 15, pp. 15-30
3. nd Int. Conf. on Fuzzy Logic and Neural Networks (IIZUKA'92), 1992, pp.345-348
4. th Fuzzy System Symposium,June,1989,pp.253-258(in Japanese).
5. Z. Michalewicz, Genetic Algorithms + Data Structures = Evolution Program, .Berlin, Germany: Springer-Verlag, 1996.
6. th IFSA Congress, Vol. Engineering, July, 1991, pp. 155-158
7. F. Hoffmann, "Evolutionary algorithms for fuzzy control system design," Proc. IEEE, vol. 89,no. 9, pp. 1318-1333, Sep. 2001.
8. S. J. Kang, C. H. Woo, H. S. Hwang, and K. B. Woo, " Evolutionry design of fuzzy rule base for nonlinear system modeling and control,"IEEE Trans. Fuzzy Seyst. , vol. 8, no. 1, pp.37-44,Feb.2000.
9. th Int. Conf. Genetic Algorithms, 1991, pp. 450-457.
10. H. R. Berenji, "A reinforcement learning-based architecture for fuzzy logic control," Int. Approx. Reasoning, vol .6, pp. 267-292, 1992.
11. H. R. Berenji, and P. Khedkar, "Learning and tuning fuzzy logic controllers through reinforcement ," IEEE Trans. Neura Networks, vol. 3, pp. 724-740, May 1992.
12. Chin-Hsun Chou "Genetic Algorithm-Based Optimal Fuzzy Controller Design in the Linguistic Space," IEEE Trans. Fuzzy Systems, vol. 14, No. 3, pp. 372-385, June 2006.
13. th IEEE Int.Conf. Fuzzy Syst., vol. 1, 2000,pp.30-35.
14. X. W. Yan, Z. D. Deng,and Z. Q. Sun, "Genetic Takagi-Sugeno fuzzy reinforcement learning," in Proc.2001 IEEE Int. Symp. Intelligent Control, pp. 67-72.
15. nd IEEE Int. Conf. Fuzzy systems, san Francisco, CA, Mar. 1993,pp. 613-617.
16. D. Whitley, S. Dominic, R. Das, and C. W. Anderson, "Genetic reinforcement learning for neurecontrol problems," Machine Learning, Vol. 13, 1993, pp. 259-284.
17. H. Saadat, Power System Analysis, New York: McGraw-Hill, 1999.
18. Ziegler, J. G., & Nichols, N. B. "Optimum Setting For Automatic Controllers", Transactions of ASME, Page(s): 759-768, 1942.