Speed control of switched reluctance motor with torque ripple reduction using non-dominated sorting genetic algorithm (NSGA-II)

In this paper, a control mechanism for speed control of switched reluctance motor (SRM) with torque ripple reduction using non-dominated sorting genetic algorithm (NSGA-II) is presented. The control mechanism consists of proportional-integral (PI) speed controller in the outer loop and PI current controller in the inner loop along with control of turn on and turn off angles for the 3 phase, 6/4 switched reluctance motor. The problem of obtaining the optimum values of proportional and integral gains for both speed and current controller along with the turn on and turn off angles are considered as a multi-objective optimization problem with the objectives of minimizing the Integral Squared Error (ISE) of speed and torque ripple. Simulations of NSGA-II based control of SRM are carried out using SIMULINK/MATLAB software. In order to evaluate the robust performance of NSGA-II, the statistical performances such as best, worst, mean, standard deviation of the Integral Squared Error (ISE) of speed and torque ripple for 20 independent trials are considered. The results obtained by NSGA-II are compared and validated with Real coded Genetic Algorithm (RGA) with Simulated Binary Crossover (SBX). The results reveal that NSGA-II based controllers give better performance in terms of lesser torque ripple and quick settling time due to its systematic random search capabilities thereby improving the dynamic performance of SRM drives.