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
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.
This article is published under a Creative Commons Attribution-NoDerivatives 4.0 International License.