Optimal Speed Control of Dual-star Linear Induction Motor based on Particle Swarm Algorithm

The current study investigates the use of Particle Swarm Optimization (PSO) for determining optimal parameters of the PID in the Field-Oriented Control (FOC) of a Dual-Star Linear Induction Motor (DSLIM). The objective is to enhance the motor’s performance by fine-tuning the PID controller settings. A mathematical model of the DSLIM and its FOC system is developed considering end-effect phenomenon, and an objective function is defined to evaluate the controller’s performance. The PSO algorithm is then employed to iteratively adjust the PID parameters based on the objective function. The effectiveness of the optimized PID parameters is validated through Matlab/ Simulink under various operating conditions. Results demonstrate improved motor performance in terms of speed regulation, torque control, and efficiency, highlighting the efficacy of PSO-based optimization in FOC of DSLIMs.