Torque ripple reduction of switched reluctance motor drive with adaptive sliding mode control and Particle Swarm Optimization

Abstract

In this paper, for speed control with torque ripple minimization of switched reluctance motor drives an optimal speed controller based on Elitist-Mutated Multi-Objective Particle Swarm Optimization (EM-MOPSO) with good accuracies, and performances is presented. The control mechanism is composed of an adaptive sliding mode speed controller to determine the appropriate current command and a hysteresis current controller. In the adaptive sliding mode controller, the heuristic parameters are usually determined by a tedious and repetitive trial-and-error process. By using EM-MOPSO, the trial-and error process is eliminated. The optimal parameters of adaptive sliding mode conrtoller and turn-on and turn-off angles are chosen by applying a multi-objective function, including both Integrals Squared Error (ISE) of speed and torque ripple. The performance of this EM-MOPSO based controller has been demonstrated by simulation in MATLAB/SIMULINK software for a four phases, 4-kw SRM.