H∞ estimation for fuzzy membership function optimization

International Journal of Approximate Reasoning

Volumn 40, Issue 3, 2005, Pages 224-242

  Simon, Dan ^a  

^a Cleveland State University   (United States)

Author keywords

Constraints; Estimation; Gradient descent; H filtering; Kalman filtering; Learning; Minimax filtering; Optimization; Training

Indexed keywords

AUTOMOTIVE ENGINEERING; CONTROL EQUIPMENT; FUNCTIONS; FUZZY CONTROL; FUZZY SETS; KALMAN FILTERING; LEARNING SYSTEMS; NONLINEAR FILTERING; OPTIMIZATION; PARAMETER ESTIMATION;

CONSTRAINTS; GRADIENT DESCENT; LEARNING; MINIMAX FILTERING; PARAMETER OPTIMIZATION;

CONTROL SYSTEMS;

EID: 27744549009     PISSN: 0888613X     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ijar.2005.04.002     Document Type: Article

References (36)

1. L. Magdalena, and F. Monasterio-Huelin Fuzzy logic controller with learning through the evolution of its knowledge base International Journal of Approximate Reasoning 16 1997 335 358
2. D. Simon, and H. El-Sherief Fuzzy logic for digital phase-locked loop filter design IEEE Transactions on Fuzzy Systems 3 1995 211 218
3. H. Surmann Genetic optimization of a fuzzy system for charging batteries IEEE Transactions on Industrial Electronics 43 1996 541 548
4. W. Barada, and H. Singh Generating optimal adaptive fuzzy-neural models of dynamical systems with applications to control IEEE Transactions on Systems, Man, and Cybernetics-Part C 28 1998 371 391
5. M. Figueiredo, and F. Gomide Design of fuzzy systems using neurofuzzy networks IEEE Transactions on Neural Networks 10 1999 815 827
6. J. Goddard, R. Parrazales, I. Lopez, A. de Luca, Rule learning in fuzzy systems using evolutionary programs, in: IEEE Midwest Symposium on Circuits and Systems, Ames, IA 1996, pp. 703-709
7. S. Smith, and D. Comer Automated calibration of a fuzzy logic controller using a cell state space algorithm IEEE Control Systems Magazine 11 1991 18 28
8. R. Wu, and S. Chen A new method for constructing membership functions and fuzzy rules from training examples IEEE Transactions on Systems, Man, and Cybernetics-Part B 29 1999 25 40
9. C. Tao, and J. Taur Design of fuzzy controllers with adaptive rule insertion IEEE Transactions on Systems, Man, and Cybernetics-Part B: Cybernetics 29 1999 389 397
10. B. Demaya, R. Palm, S. Boverie, A. Titli, Multilevel qualitative and numerical optimization of fuzzy controller, in: IEEE International Conference on Fuzzy Systems, Yokohama, Japan, 1995, pp. 1149-1154
11. D. Simon Training fuzzy systems with the extended Kalman filter Fuzzy Sets and Systems 132 December 2002 189 199
12. J. Deskur, R. Muszynski, D. Sarnowski, Tuning and investigation of combined fuzzy controller, in: International Conference on Power Electronics and Variable Speed Drives, London, 1998, pp. 353-357
13. M. Jacomet, A. Stahel, and R. Walti On-line optimization of fuzzy systems Information Sciences 98 1997 301 313
14. M. Sugeno, and K. Tanaka Successive identification of a fuzzy model and its applications to prediction of a complex system Fuzzy Sets and Systems 42 1991 315 334
15. L. Wang Adaptive fuzzy systems and control: design and stability analysis 1994 Prentice-Hall Englewood Cliffs, NJ
16. L. Wang, J. Mendel, Back-propagation of fuzzy systems as nonlinear dynamic system identifiers, in: IEEE International Conference on Fuzzy Systems, San Diego, CA, 1992, pp. 1409-1418
17. E. Nakamura, N. Kehtarnavez, Optimization of fuzzy membership function parameters, in: IEEE International Conference on Systems, Man and Cybernetics, Vancouver, Canada, 1995, pp. 1-6
18. D. Simon Design, rule base reduction of a fuzzy filter for the estimation of motor currents International Journal of Approximate Reasoning 25 October 2000 145 167
19. D. Simon, and H. El-Sherief Hybrid Kalman/minimax filtering in phase-locked loops Control Engineering Practice 4 5 1996 615 623
20. T. Terano, K. Asai, and M. Sugeno Fuzzy Systems Theory and Its Applications 1992 Academic Press New York
21. J. Yen, and R. Langari Fuzzy logic: intelligence, control, and information 1999 Prentice-Hall Englewood Cliffs, NJ
22. Y. Yam, P. Baranyi, and C. Yang Reduction of fuzzy rule base via singular value decomposition IEEE Transactions on Fuzzy Systems 7 1999 120 132
23. B. Kosko Neural Networks and Fuzzy Systems 1992 Prentice Hall
24. F. Guély, P. Siarry, Gradient descent method for optimizing various fuzzy rule bases, in: IEEE International Conference on Fuzzy Systems, San Francisco, 1993, pp. 1241-1246
25. D. Simon Sum normal optimization of fuzzy membership functions International Journal of Uncertainty, Fuzziness, and Knowledge-Based Systems 10 August 2002 363 384
26. B. Hassibi, A. Sayed, and T. Kailath Indefinite-quadratic estimation and control SIAM 1999
27. ∞filter design IEEE Transactions on Signal Processing 1997 1092 1095
28. ∞-optimal estimation International Journal of Control 55 1992 1443 1452
29. B. Anderson, and J. Moore Optimal filtering 1979 Prentice Hall Englewood Cliffs, NJ
30. G. Puskorius, and L. Feldkamp Neurocontrol of nonlinear dynamical systems with kalman filter trained recurrent networks IEEE Transactions on Neural Networks 5 1994 279 297
31. G. Leu, and R. Baratti An extended kalman filtering approach with a criterion to set its tuning parameters; application to a catalytic reactor Computers and Chemical Engineering 23 2000 1839 1849
32. D. Simon, A game theory approach to constrained minimax state estimation IEEE Transactions on Signal Processing, in press
33. M. Guven, and K. Passino Avoiding exponential growth in fuzzy systems IEEE Transactions on Fuzzy Systems 9 2001 194 199
34. A. Gelb Applied optimal estimation 1974 MIT Press Cambridge, MA
35. K. Reif, S. Gunther, E. Yaz, and R. Unbehauen Stochastic stability of the discrete-time extended Kalman filter IEEE Transactions on Automatic Control 44 1999 714 728
36. E. Wan, and R. van der Merwe The unscented Kalman filter S. Haykin Kalman filtering and neural networks 2001 John Wiley and Sons New York 221 280