Switched Reluctance Motor Speed and Torque Control using ACO and PSO Algorithms

Abstract

A Switched Reluctance Machine (SRM) is an electric motor that operates based on the principle of magnetic reluctance. In addition, SRMs have several advantages over other types of electric motors. However, SRMs also have some disadvantages. They can produce high noise and vibration levels, especially at high speeds. This paper describes the torque and speed controller for SRM using two techniques, Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO) combined with a PI corrector. The conventional PI controller is nowadays used in most engineering, being acknowledged for their ability to give up superior control in power electronic systems. Moreover, finding appropriate values for the PI controller is not easy. A solution based on ACO and PSO is used to overcome this problem and simplify tuning the PI controller parameters. Simulation in MATLAB-Simulink was used to demonstrate the effectiveness of the suggested controllers.