A Comparative Analysis of Intelligent Algorithm-Based Tuning of PID Controller for Speed Control of BLDC Motor

Brushless DC (BLDC) motors have gained prominence for their superior efficiency, reliability, and extended lifespan due to the absence of brushes. PID controllers effectively regulate the speed or position of BLDC motors by adjusting the motor’s input voltage based on an error signal derived from the difference between the desired and actual speed or position, ensuring precise and stable operation. In this paper, a PID controller is tuned for the speed control of the BLDC motor using Particle Swarm Optimization (PSO) and Genetic algorithm (GA). The system is developed on the MATLAB/Simulink platform, and a comparative analysis is performed between the PSO and GA-based tuning of the PID controller. The preliminary result demonstrates that the GA-PID controller outperforms the PSO-PID controller regarding faster rise time and percentage of overshoot. On the contrary, PSO-PID performs better in the case of stability and robustness with a larger negative magnitude of the real part of dominating eigenvalues.