Optimization of scaling factors of fuzzy logic controllers by genetic algorithms

It is known that besides the membership function and rule sets, scaling factors are also very important to be considered in designing a fuzzy logic controller. If they are not chosen properly, the system may become unstable, oscillate or stable but with a large overshoot and slow response time. However, finding the optimal scaling factors is not a trivial task for complex, partially unknown or nonlinear systems. Furthermore, the traditional trial-and-error methods of finding a proper scaling factors is experience-based, time-consuming and do not always guarantee good response. In this paper, a Genetic Algorithm(GA)-based tuning and optimization method for scaling factors is proposed. In order to show the generality of this method, the proposed GA search for optimal scaling factors is tested on two different types of systems: a third order linear open-loop stable system and an open-loop unstable system (ball and beam system). Simulation results verify that the fuzzy logic controller whose scaling factors are optimized by GA achieve better performance. Copyright (C) 1998 IFAC.