Abstract
In this paper, a method for the automatic design of Fuzzy Control Systems is introduced. The method is based on the identification of the inverse model of the process to be controlled by using a Neural Network. The Neural Network which models the inverse process, is used again to obtain a set of tuples representing the fuzzy variables of the fuzzy controller. In order to obtain the fuzzy linguistic variables involved in the fuzzy controller, a Neural Network is used with the DCL algorithm. Finally, the fuzzy controller is implemented by a decision table. The method has been applied to the automatic development of a fuzzy controller for a highly non linear process.
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References
Faßmer, J. “Adaptive Generierung der Produktionsregeln eines Fuzzy-Regler mit Hilfe eines Neuronalen Netzwerkes”. Diplomarbeit IFW Hannover, December 1992.
Isermann, R. “Prozeidentification”. Band 1, 2. Springer Verlag 1988.
Kosko. B. “Neural networks and fuzzy systems”. Prentice-Hall International 1992.
Lee, C.C. “Fuzzy logic in control systems: Fuzzy logic controler part I-II”. IEEE Transactions on Systems, Man and Cybernetics, Mar/April 1990, vol. 20, n. 2, pp. 1320–1336.
Narendra, K.S.; Parthasarathy, K. “Identification and control of dynamical system using neural networks”. IEEE Transactions on Neural Networks, March 1990, vol. 1, n. 1, pp. 4–27.
Procyk, T.J.; Mamdami,E.H. “Alinguistic self-organizing process controller”. Automatica 1979,vol. 15, pp. 15–30.
Quin, S.-Z.; Su, H.T.; Mc Avoy, T.J. “Comparation of four neural net learning methods for dynamic system identification”. IEEE Transactions on Neural Networks, Jan 92, vol. 3, n. 1, pp. 122–130.
Reynold Chu, S.; Shoureshi, R.; Tenorio, M. “Neural networks for system identification”. IEEE Control System Magazine, April 1990, pp. 31–34.
Takagi, H. “Fusion technology of fuzzy theory and neural networks suvey and future directions”. Proceedings of the International Conference on Fuzzy Logic and Neural Networks., July 1990, pp. 13–26.
Takagi, H.; Hayashi, I. “Fuzzy reasoning”. International Journal of Approximate Reasoning, Mai 1991, vol. 5, n. 5, pp. 191–212.
Wang, L-X.; Mendel, J.M. “Generating fuzzy rules by learning from examples”. Proceedings of the 1991 IEEE International Symposium on Intelligent Control. Arlinton, California 1991.
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© 1995 Springer-Verlag Berlin Heidelberg
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Villadangos, J., de Mendívil, J.R.G., Alastruey, C.F., Garitagoitia, J.R. (1995). Neural networks for automatic fuzzy control system design. In: Mira, J., Sandoval, F. (eds) From Natural to Artificial Neural Computation. IWANN 1995. Lecture Notes in Computer Science, vol 930. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-59497-3_289
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DOI: https://doi.org/10.1007/3-540-59497-3_289
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