Design of Sophisticated Fuzzy Logic Controllers Using Genetic Algorithms

Design of fuzzy logic controllers encounters difficulties in the selection of optimized membership functions and fuzzy rule base, which is traditionally achieved by a tedious trial-and-error process. This paper develops genetic algorithms for automatic design of high performance fuzzy logic controllers using sophisticated membership functions that intrinsically reflect the nonlinearities encountered in many engineering control applications. The controller design space is coded in base-7 strings (chromosomes), where each bit (gene) matches the 7 discrete fuzzy value. The developed approach is subsequently applied to the design of a proportional plus integral type fuzzy controller for a nonlinear water level control system. The performance of this control system is demonstrated higher than that of a conventional PID controller. For further comparison, a fuzzy proportional plus derivative controller is also developed using this approach, the response of which is shown to present no steady-state error.