Genetic-based fuzzy clustering for DC-motor friction identification and compensation

IEEE Transactions on Control Systems Technology

Volumn 6, Issue 4, 1998, Pages 462-472

  Tzes, Anthony ^a,b   Peng, Pei Yuan ^a,c   Guthy, John ^b  

^a IEEE   (United States)

^b POLYTECHNIC UNIVERSITY   (United States)

^c UNITED TECHNOLOGIES RESEARCH CENTER   (United States)

Author keywords

Fuzzy logic; Genetic algorithms; Mechanical factors; Motor drives; Variable structure systems

Indexed keywords

FEEDBACK CONTROL; FRICTION; FUZZY SETS; GENETIC ALGORITHMS; IDENTIFICATION (CONTROL SYSTEMS); MATHEMATICAL MODELS; PARAMETER ESTIMATION;

GENETIC BASED FUZZY CLUSTERING; VARIABLE STRUCTURE SYSTEMS;

DC MOTORS;

EID: 0032122985     PISSN: 10636536     EISSN: None     Source Type: Journal    
DOI: 10.1109/87.701338     Document Type: Article

References (29)

1. A. Tzes, P.-Y. Peng, and C.-C. Houng, "Neural-network control for dc-motor micromaneuvering," IEEE Trans. Ind. Electron., vol. 42, pp. 516-523, Oct. 1995.
2. B. Armstrong, "Friction: Experimental determination modeling and compensation," in Proc. IEEE Int. Conf. Robot. Automat., Philadelphia, PA, May 1988, pp. 1422-1427.
3. C. Canudas, K. Astrom, and K. Braun, "Adaptive friction compensation in dc-motor drives," IEEE Trans. Robot. Automat., vol. 3, pp. 681-685, Dec. 1987.
4. C. Canudas, P. Noel, A. Aubin, B. Brogliato, and P. Drevet, "Adaptive friction compensation in robot manipulators: Low velocities," in Proc. IEEE Int. Conf. Robot. Automat., Scottsdale, AZ, May 1989, pp. 1352-1357.
5. B. Friedland and Y.-J. Park, "On adaptive friction compensation," IEEE Trans. Automat. Contr., vol. AC-37, pp. 1609-1612, Oct. 1992.
6. C. J. Radcliffe and S. C. Southward, "A property of stick-slip friction models which promotes limit cycle generation," in Proc. Amer. Contr. Conf., San Diego, CA, May 1990, pp. 1198-1203.
7. S. C. Southward, C. J. Radcliffe, and C. R. MacCluer, "Robust nonlinear stick-slip friction compensation," Trans. ASME, vol. 113, no. 4, pp. 639-645, 1991.
8. B. Armstrong-Helouvry, Control of Machines with Friction. Norwell, MA: Kluwer, 1991.
9. W. Pedrycz, "An identification algorithm in in fuzzy relational systems," Fuzzy Sets Syst., vol. 13, pp. 153-167, 1984.
10. T. Takagi and M. Sugeno, "Fuzzy identification of systens and its applications to modeling and control," IEEE Trans. Syst., Man, Cybern., vol. 15, pp. 116-132, 1985.
11. C. W. Xu, "Fuzzy system identification," Proc. Inst. Electr. Eng., vol. 136, pt. D, July 1989, pp. 146-150.
12. S. Baglio, L. Fortuna, S. Graziani, and G. Muscato, "Membership function shape and the dynamic behavior of fuzzy systems," Int. J. Adaptive Contr. Signal Processing, vol. 8, pp. 369-377, 1994.
13. J. Holland, Adaptation in Natural and Artificial Systems. Cambridge, MA: MIT Press, 1992.
14. D. Goldberg, Genetic Algorithms in Search, Optimization and Machine Learning. Reading, MA: Addison-Wesley, 1989.
15. J. J. Grefenstette, "Optimization of control parameters for genetic algorithms," IEEE Trans. Syst., Man, Cybern., vol. SMC-16, pp. 122-128, Jan. 1986.
16. J. Buckley and Y. Hayashi, "Fuzzy genetic algorithm and applications," Fuzzy Sets Syst., vol. 61, no. 2, pp. 129-136, 1994.
17. C. C. Wong and S. M. Feng, "Switching-type fuzzy controller design by genetic algorithms," Fuzzy Sets Syst., vol. 74, no. 2, pp. 175-185, 1995.
18. D. Park, A. Kandel, and G. Langholz, "Genetic-based new fuzzy reasoning models with application to fuzzy control," IEEE Trans. Syst., Man, Cybern., vol. 24, pp. 39-47, 1994.
19. D. A. Linkens and H. O. Nyongesa, "Genetic algorithms for fuzzy control: Parts 1 & 2," in Proc. Inst. Electr. Eng., vol. 142, pt. D, no. 3, 1995, pp. 161-185.
20. B. Armstrong-Hélouvry, P. Dupont, and C. de Wit, "A survey of models, analysis tools and compensation methods for the control of machines with friction," Automatica, vol. 30, pp. 1083-1138, July 1994.
21. H. Czichos, Tribology. New York: Elsevier, 1978.
22. B. Armstrong-Helouvry, "Stick-slip arising from Stribeck friction," in Proc. IEEE Int. Conf. Robot. Automat., Cincinatti, OH, May 1990, pp. 1377-1382.
23. Y. Yoshinari, W. Pedrycz, and K. Hirota, "Construction of fuzzy models through clustering techniques," Fuzzy Sets Syst., vol. 54, no. 2, pp. 157-165, 1993.
24. D. E. Gustafson and W. C. Kessel, "Fuzzy clustering with a fuzzy covariance matrix," in Proc. IEEE Conf. Decision Contr., New Orleans, LA, Dec. 1979, pp. 761-766.
25. J. Zhao, V. Wertz, and R. Gorez, "A fuzzy clustering method for the identification of fuzzy models for dynamic systems," in Proc. 9th IEEE Int. Symp. Intell Contr., Columbus, OH, Aug. 1994, pp. 172-177.
26. S. Chiu, "Fuzzy model identification based on clustering estimation," J. Intell Fuzzy Syst., vol. 2, no. 3, 1994.
27. R. Krishnapuram and C. Freg, "Fitting an unknown number of lines and planes to image data through compatible cluster merging," Pattern Recognition, vol. 25, no. 4, pp. 385-400, 1992.
28. R. R. Yager and D. P. Filev, "Unified structure and parameter identification of fuzzy models," IEEE Trans. Syst., Man, Cybern., vol. 23, pp. 1198-1205, 1993.
29. P. Wellstead and M. Zarrop, Self-Tuning Systems: Control and Signal Processing. New York: Wiley, 1991.