Optimization of Membership Functions of Fuzzy Logic Controller for Controlling Liquid Level Using Genetic Algorithms.

Abstract

Selection of membership functions (MF) for a fuzzy logic controller (FLC) is an iterative and a time consuming task. This paper describes the use of genetic algorithm (GA) search strategy for optimizing MFs of antecedent and consequent variables of an FLC that has been used for controlling the level of water on realtime basis in a laboratory scale pilot plant. For the simulation of GA integral line square error (JTSE) has been used as the fitness function.