Optimum Performance Achieving of BLDC Motor Based on Optimized SMC Strategy

Electric vehicles, healthcare devices, and manufacturing machinery all use brushless DC motors (BLDCM) because of the need for precise speed regulation to accommodate load and reference variation. In this research, the Particle Swarm Optimization (PSO) method is used to find the best values for the Proportional-Integral (PI) and Sliding Mode Controller (SMC) parameters used to regulate the speed of BLDC motors. The Integral Time Absolute Error (ITAE) is employed as the fitness function when utilizing the PSO technique for fine-tuning the PI and SMC parameters. Statistical and visual representations of the optimization techniques' effectiveness are provided. The simulation results demonstrate the PSO-based SMC's superiority over the optimization PI controller and the SMC without optimization regarding fast-tracking to the intended value and reduced torque ripple under non-uniform situations.