Genetic learning of fuzzy controllers

New methods for designing and analyzing fuzzy controllers are required. Some architectures for integrating genetic algorithms with fuzzy logic controllers, the so called hybrid gene-fuzzy controllers, are introduced and discussed. A new hybrid gene-fuzzy controller based on the algebraic model of the 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 truck backer-upper system. The genetic algorithm is further used to tune the coefficients of the deduced algebraic model. The simulated results indicate that the hybrid gene-fuzzy controller is superior to a conventional fuzzy controller. (C) 1999 IMACS/Elsevier Science B.V. All rights reserved.