APPLICATION OF NEURAL NETWORKS TO FUZZY CONTROL

This paper gives a possible application of neural networks to fuzzy control. In fuzzy control a set of linguistic rules are given and by specifying a method of fuzzy reasoning and defuzzification an input-output relation is obtained. Fuzzy controllers thus obtained are usually irregular, and are not necessarily what experts expect. It is sometimes difficult to implement such controllers when processing time is limited. Here we attempt to dissolve such drawbacks using neural networks that can learn these input-output maps. We show that good neuro-controller can be obtained for an inverted pendulum system. The structure of the neuro-controller is simple, and hence analysis and implementation are easy. We discuss the stability of the system and confirm our results by experiments.