Dynamic non-singleton fuzzy logic systems for nonlinear modeling

IEEE Transactions on Fuzzy Systems

Volumn 5, Issue 2, 1997, Pages 199-208

  Mouzouris, George C ^b   Mendel, Jerry M ^a,b  

^a IEEE

^b University of Southern California ^*  (United States)

Author keywords

Dynamic NSFLS; NARMA; Nonlinear modeling

Indexed keywords

BACKPROPAGATION; IDENTIFICATION (CONTROL SYSTEMS); INFERENCE ENGINES; LEARNING ALGORITHMS; MATHEMATICAL MODELS; NONLINEAR SYSTEMS; PERFORMANCE;

DYNAMIC NON SINGLETON FUZZY LOGIC SYSTEMS; NONLINEAR AUTOREGRESSIVE MOVING AVERAGE; NONLINEAR MODELING;

FUZZY SETS;

EID: 0031142474     PISSN: 10636706     EISSN: None     Source Type: Journal    
DOI: 10.1109/91.580795     Document Type: Article

References (31)

1. M. Balazinski, E. Czogala, and T. Sadowski, "Control of metal-cutting process using neural fuzzy controller," in 2nd IEEE Int. Conf. Fuzzy Syst., San Francisco, CA, Mar. 1993, vol. 1, pp. 161-166.
2. J. T. Connor, R. D. Martin, and L. E. Atlas, "Recurrent neural networks and robust time series prediction," IEEE Trans. Neural Networks, vol. 5, pp. 240-254, Mar. 1994.
3. D. Dubois and H. Prade, Fuzzy Sets and Systems: Theory and Applications. Orlando, FL: Academic, 1980.
4. _, "Fuzzy sets in approximate reasoning - Part 1: Inference with possibility distributions," Fuzzy Sets Syst., vol. 40, no. 1, pp. 143-202, 1991.
5. Y. Hayashi, J. J. Buckley, and E. Czogala, "Fuzzy neural network with fuzzy signals and weights," Int. J. Intell. Syst., vol. 8, pp. 527-537, 1993.
6. S. Haykin, Neural Networks: A Comprehensive Foundation. New York: Macmillan, 1994.
7. H. Hellendoorn and C. Thomas, "Defuzzification in fuzzy controllers," J. Intell. Syst., vol. 1, pp. 109-123, 1993.
8. R. J. Jang and C. Sun, "Neuro-fuzzy modeling and control," Proc. IEEE, vol. 83, pp. 378-406, Mar. 1995.
9. C. C. Lee, "Fuzzy logic in control systems: fuzzy logic controller - Part I," IEEE Trans. Syst., Man, Cybern., vol. 20, pp. 404-418, Feb. 1990.
10. _, "Fuzzy logic in control systems: fuzzy logic controller - Part II," IEEE Trans. Syst., Man, Cybern., vol. 20, pp. 419-435, Feb. 1990.
11. J. M. Mendel, "Fuzzy logic systems for engineering: A tutorial," Proc. IEEE, vol. 83, pp. 345-377, Mar. 1995.
12. _, Lessons in Estimation Theory, for Signal Processing, Communications and Control. Englewood Cliffs, NJ: Prentice-Hall, 1995.
13. G. C. Mouzouris and J.M. Mendel, "Non-Singleton fuzzy logic systems," in 3rd IEEE Proc. Int. Conf. Fuzzy Syst., June 1994, vol. 1, pp. 456-461.
14. _, "Non-Singleton fuzzy logic systems: Theory and application," IEEE Trans. Fuzzy Syst., vol. 5, pp. pp. 56-71, Feb. 1997.
15. _, "Nonlinear time series analysis with Non-Singleton fuzzy logic systems," in IEEE/IAFE Conf. Computati. Intell. Financial Eng., New York, Apr. 1995, pp. 47-56.
16. Y. Muyaram, T. Terano, S. Masui, and N. Akiyama, "Optimizing control of a diesel engine," in Industrial Applications of Fuzzy Control, M. Sugeno, Ed. Amsterdam, The Netherlands: North-Holland, 1992, pp. 63-71.
17. K. S. Narendra and K. Parthasarathy, "Identification and control of dynamical systems using neural networks," IEEE Trans. Neural Networks, vol. 1, pp. 4-27, Mar. 1990.
18. O. Nerrand, P. Roussel-Ragot, L. Personnaz, G. Dreyfus, and S. Marcos, "Neural networks and nonlinear adaptive filtering: Unifying concepts and new algorithms," Neural Computat. vol. 5, no. 2, pp. 165-199, 1993.
19. W. Pedrycz, "Design of fuzzy control algorithms with the aid of fuzzy models," in Industrial Applications of Fuzzy Control, M. Sugeno, Ed. Amsterdam, The Netherlands: North-Holland, 1992, pp. 139-151.
20. Y. Sakai and K. Ohkusa, "A fuzzy controller in turning process automation," Industrial Applications of Fuzzy Control, M. Sugeno, Ed. Amsterdam, The Netherlands: North-Holland, 1992, pp. 139-151.
21. P. S. Sastry, G. Santharam, and K. P. Unnikrishnan, "Memory neuron networks for identification and control of dynamical systems," IEEE Trans. Neural Networks, vol. 5, pp. 306-319, Mar. 1994.
22. H. Tanaka, T. Okuda, and K. Asai, "Fuzzy information and decision in statistical model," in Advances in Fuzzy Set Theory and Applications, M. M. Gupta, R. K. Ragade, and R. R. Yager, Eds. Amsterdam, The Netherlands: North-Holland, 1979, pp. 303-320.
23. L. X. Wang and J. M. Mendel, "Back-propagation fuzzy systems as non-linear dynamic system identifiers," in IEEE Proc. Int. Conf. Fuzzy Syst., San Diego, CA, Mar. 1992, pp. 1409-1418.
24. _, "Generating fuzzy rules from numerical data, with applications," USC-SIPI Rep. 169, 1991; also in IEEE Trans. Syst., Man, Cybern., vol. 22, pp. 1414-1427, Nov. 1992.
25. L. X. Wang, Adaptive Fuzzy Systems and Control. Englewood-Cliffs, NJ: Prentice-Hall, 1994.
26. P. J. Werbos, "Backpropagation through time: What it does and how to do it," Proc. IEEE, vol. 78, pp. 1550-1560, Oct. 1990.
27. R. J. Williams and J. Peng, "An efficient gradient-based algorithm for on-line training of recurrent network trajectories," Neural Computat., vol. 2, pp. 490-501, 1990.
28. R. J. Williams and D. Zipser, "A learning algorithm for continually running fully recurrent neural networks," Neural Computat., vol. 1, no. 2, pp. 270-280, 1989.
29. L. A. Zadeh, "Fuzzy sets," Inform. Contr., vol. 8, no. 3, pp. 338-353, 1965.
30. _, "Outline of a new approach to the analysis of complex systems and decision processes," IEEE Trans. Syst., Man, Cybern., vol. SMC-3, pp. 28-44, Jan. 1973.
31. H. J. Zimmermann, Fuzzy Set Theory And Its Applications, 2nd ed. Boston, MA: Kluwer, 1991.