Speed and Current Control of Switched Reluctance Motor Using Sparrow Search Algorithm Based Fuzzy <scp>PID</scp> Controller

Abstract This paper proposes a cascaded fuzzy PID control system based on sparrow search algorithm (SSA), which effectively reduces the torque ripple of switched reluctance motors and improves the motor control performance. The introduced sparrow algorithm solves the problem of difficult adjustment of complex parameters in control systems. The control system in this paper uses an inner and outer loop control structure, where the outer loop is the speed control loop and the inner loop is the current control loop. Simultaneously adjust the speed and current of SRM to improve motor speed regulation performance, reduce current ripple and better suppress motor torque ripple. To prove the effectiveness of the control system, a control model is established in MATLAB Simulink. It is compared with fuzzy PID control system and two cascaded PID control systems based on bacterial foraging optimization algorithm (BFOA) and spotted hyena optimization algorithm (SHO). Gray Wolf Algorithm (GWO) and Particle Swarm Optimization (PSO) were also introduced to optimize the controller and compared. The final results show that the cascaded fuzzy PID control system optimized by the Sparrow algorithm proposed in this paper has better speed control performance and lower torque ripple. © 2025 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.