Fitting fuzzy membership functions using genetic algorithms

The use of Fuzzy Logic to solve control problems have been increasing considerably in the past years. This makes the teaching of Fuzzy Control in engineering courses an urgent need. So, a self-training computer package in fuzzy control theory for students was developed before. The package has all necessary instructions for understanding of all principles of fuzzy control by the users. The training instructions are given through an application drill. Though this approach proved to be an effective one, in giving to the students a way to understand an actual situation, it has a limitation: the learning method itself. The students always use the `try-and-error' method to arrive to an adequate control action. The problem with this method is that students may be driven to the wrong conclusion that fuzzy control system corrections are but a matter of supposition. The purpose of this paper is to present a strategy for the membership functions automatic adjustment using genetics algorithms.