Comprehensive Analysis of Control Techniques for BLDC Motor: Genetic Algorithm vs Fuzzy-PID

Effective control of BLDC motors is necessary due to their widespread applications in areas that require high precision in speed regulation, high efficiency, and high reliability. This paper reviews and compares speed control techniques for the BLDC motor. The BLDC motor system with Genetic Algorithm-tuned PID and Fuzzy PID controllers has been simulated using MATLAB/Simulink in this paper. Among them, Genetic Algorithm-tuned PID showed the best performance, with a rise time reduced by about 75.49% and a settling time reduced by about 58.60% compared to Fuzzy PID, proving it suitable for applications that require fast response. However, it showed a higher overshoot of 310.42%, which may affect stability. On the other hand, the Fuzzy PID controller gave better stability with minimum overshoot but was slow, with a longer rise time and settling time. These results highlight a clear trade-off: one method is faster but less stable, while the other is more stable but slower. Choosing the right controller depends on whether speed or stability is more important for the specific application.