Abstract
New methods for designing and analyzing intelligent control systems are required. Methods for using genetic algorithms for evolving neurocontrollers are reviewed. Some architectures for integrating genetic algorithms with fuzzy logic controllers are presented and discussed. A new application of a genetic algorithm for evolving the algebraic model of a fuzzy controller is proposed. Genetic algorithms are shown to be able to deduce the algebraic model of a simple fuzzy controller used for controlling a servo-system. The genetic algorithm is further used to tune the coefficients of the deduced algebraic model.
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