Torque ripples reduction and speed control of a switched reluctance motor based on artificial intelligence techniques

Abstract

This paper proposes a technique for reducing torque ripples and speed control of switched reluctance motor (SRM) using artificial intelligence. The controller of SRM is developed based on a fuzzy logic controller using MATLAB/Simulink software. Fuzzy logic controller overcomes the nonlinearity and uncertainty of the SRM. The proposed controller is used for predicting torque ripples and speed control profiles. The machine performance using the proposed controller is compared with using a traditional PI controller. In addition, comparison of motor performance with and without the use of proposed controllers is highlighted. The motor performance is evaluated using the suggested different controllers. The simulation results show that the proposed method indicates a 65% to 75% reduction in torque ripples compared to the traditional PI method.