A genetic algorithm optimization of hybrid fuzzy-fuzzy rules in induction motor control

Abstract

This paper discusses speed control performance of a proposed hybrid fuzzy-fuzzy controller (HFFC) in a variable speed induction motor (IM) drive system. With respect to finding the rule base of the fuzzy controller, a simple genetic algorithm (GA) is employed to resolve the problem of optimization to diminish an objective function, i.e., the Integrated Absolute Error (IAE) criterion. The principle of HFFC is established with the aim of overcoming the shortcoming of the field oriented control (FOC) technique. Simulation results show that HFFC with GA-optimized is the better strategy as compared to HFFC without GA, and conventional hybrid fuzzy-PI controller (HFPIC) for the speed control of IM.