Optimization of speed control algorithm to achieve minimum torque ripple for a switched reluctance motor drive via GA

This study presents a speed controller design for a switched reluctance (SR) motor in order to achieve minimum torque ripple and high control performance. First of all, SR motor convertor designed for soft chopping is chosen. This converter as well as producing less torque ripple, provides more degrees of freedom for SR motor drive controller. A PID controller and a switching algorithm for turn-on and turn-off degree of each phase of motor form speed control loop of SR motor drive. The primary parameters of controller are achieved by try and error. But eventually an optimization algorithm to reach the goals and constraints in different set points is defined and its parameters are optimized with a Genetic Algorithm (GA). This algorithm optimized the turn-on and turn-off degrees of each phase, the parameters of PID controller in transient state, and parameters of PID controller that considered for reducing the torque ripple in steady state. Also, GA simultaneously obtains the optimum parameters of three nonlinear gains considered for fuzzy switching between the two PID controllers. The proposed control algorithm was simulated using MATLAB / Simulink software package and an application example of 8/6 SRM to validate the performance of designed algorithm.