Performance Improvement of Direct Torque Control Induction Motor Drive using Genetic Algorithm Optimized PI Controller

Abstract

Direct Torque Control (DTC) is an advanced control technique because of its fast torque response, ingenuousness, less sensitivity against motor parameter variations. The prosperity of the induction motor is dominated by the application torque which is dictated by the proportional integral (PI) controller output. In consequence of parameter variations, non-linear dynamics, external disturbances, the fixed gain PI controller becomes unstable to provide the desired performance of the IM. This produces an improper estimation of control variables and results in a speed error, flux ripple, torque ripple, stator current distortion and degrade the low speed performance. So the sorting of PI controller gain parameters are important. In this paper, the optimization of PI controller gain parameters is done using genetic algorithm (GA) in consonance with the speed fluctuation within the predicted and reference speed which in turn improve the determination of reference torque. The simulation of the presented DTC IM drive using GA optimized PI controller has been performed in MATLAB/SIMULINK environment. The presented DTC improves 100% high speed response, 50% low speed response and 17.38% stator current distortion from the conventional DTC.