The Shape Identification of Membership Functions by Genetic Algorithm and Fuzzy Control of a Fluid Temperature System

Abstract

Fuzzy control has been applied to various fields because it is easy to describe experience and knowledge of human directly. This paper deals with a fuzzy control for a fluid temperature system using optimized shapes of membership functions of fuzzy production rules. The shapes of membership functions are optimized through the learning based on the genetic algorithm. The effectiveness of the fuzzy control with the optimized shapes is confirmed by an experiment of a fluid temperature system.