Multi-Stages for Tuning Fuzzy Logic Controller (FLC) Using Genetic Algorithm (GA)

Abstract

In this paper, a study on tuning of fuzzy logic controller (FLC) using genetic algorithm (GA) for controlling an armature controlled DC motor as an example of linear plant and for controlling nonlinear plant as another example is performed. There are different ways in which a FLC can be tuned, like: tuning the scaling gains, Rule Base (RB), and Data Base (DB) represented by type of membership functions or parameters of membership functions used. The tuning process in this paper includes a multi-stage tuning represented by searching the good scaling gains, RB, and DB then a combination of multi-stage (CMS) tuning methods using Genetic Algorithm (GA) based on a fitness function that is defined in terms of performance criterion (Integral of Squared Error ISE). The performances of these tuning stages are evaluated and a comparison between them has been introduced using linear and nonlinear plants.

Keywords

• fuzzy logic controller
• rule base
• data base
• genetic algorithm