Gravitational search optimization approach to improve fuzzy logic speed controller for induction motor drive

Abstract

Fuzzy logic controller (FLC) is very useful for controlling speed and torque variables in the three-phase induction motor (TIM) operation. However, the conventional FLC has the exhaustive traditional trial and error procedure in obtaining membership functions (MFs). This paper presents an adaptive FLC design technique for TIM using a gravitational search algorithm (GSA) optimization technique. This technique provides the numerical values to limit the error and change in error of the MFs based on the evaluation results of the objective function formulated by the GSA. The root mean square error (RMSE) of the speed response is used as a fitness function. An optimal GSA-based FLC (GSAF) fitness function is also employed to tune and minimize the RMSE for improving the performance of the TIM in terms of changes speed and torque. Space vector pulse width modulation (SVPWM) technique is utilized to generate signals via voltage/frequency control strategy for variable frequency inverter. Results obtained from the GSAF are compared with those obtained through particle swarm optimization (PSO) to validate the developed controller. The robustness of the GSAF is better than that of the PSO controller in all tested cases in terms of damping capability and transient response under different load and speed. Streszczenie. W artykule zaprezentowano adaptacyjny sterownik typu fuzzy logic przeznaczony do trójfazowego silnika indukcyjnego wykorzystujący algorytm optymalizacyjny badania grawitacyjnego. Jako funkcję fitness użyto błąd rms odpowiedzi prędkości. Do zasilania silnika wykorzystano metodę modulacji szerokości impulsu. Optymalizacja typu grawitacyjne badanie jako metoda poprawy jakości sterownika fuzzy logic zastosowanego do silnika indukcyjnego