Performance Development of Space Vector Pulse Width Modulation for Induction Motor Drive Using Artificial Intelligence

Abstract

Space vector pulse width modulation (SVPWM) technique is an advanced computation-intensive PWM method. It is the best among all PWM techniques for three-phase induction motor (TIM) drive applications because of its superior performance characteristics. In this paper, the use of artificial neural network (ANN) based SVPWM technique avoids the computational complex used in conventional SVM implementation. An ANN scheme structure is suggested to identify and approximate the conventional SVPWM for decrease the computational problem. Moreover, proportional-integral (PI) controller tuning is achieved using a particle swarm optimization (PSO) algorithm to improve the TIM speed controller’s response performance. By designing an appropriate PSO algorithm, kp and ki of the PI speed controller parameters are tuned for TIM to attain the best parameter values.