Design of flexible structured fuzzy controllers using genetic algorithms

Previously, optimal fuzzy logic controllers have been used successfully in a complex search space using various search approaches. The paper develops a genetic-algorithm based learning approach to implementation of a flexible structured fuzzy controller. The algorithm used facilitates simultaneous determination of control rules, of membership functions and of the structure parameters of the controller, that results in a high-performance controller, that is demonstrated on simulation examples.