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On the Optimization of Fuzzy-Controllers by Neural Networks
Wolfram-M. Lippe, Steffen Niendieck, Andreas Tenhagen
Westfalische Wilhelms-Universitat Munster Institut fur Informatik EinsteinstraBe 62, 48149 Munster, Germany
Received:January 10, 1999Accepted:April 15, 1999Published:June 20, 1999
Abstract
Methods are known for combining fuzzy-controllers with neural networks. One of the reasons of these combinations is to work around the fuzzy controllers’ disadvantage of not being adaptive. It is helpful to represent a given fuzzy controller by a neural network and to have rules adapted by a special learning algorithm. Some of these methods are applied in the NEFCONmode or the model of Lin and Lee. Unfortunately, none adapts all fuzzy-controller components. We suggest a new model enabling the user to represent a given fuzzy controller by a neural network and adapt its components as desired.
Cite this article as:W. Lippe, S. Niendieck, and A. Tenhagen, “On the Optimization of Fuzzy-Controllers by Neural Networks,” J. Adv. Comput. Intell. Intell. Inform., Vol.3 No.3, pp. 158-163, 1999.Data files:
