Enhancing BLDC Motor Speed Control by Mitigating Bias with a Variation Model Filter

Brushless DC motors (BLDC) are integral to a wide array of applications, from electric vehicles to industrial machinery, due to their superior efficiency, reliability, and performance. Effective control of BLDC motors is essential to leverage their full potential and ensure optimal operation. Traditional PID controllers often fall short in handling the nonlinear and dynamic characteristics of BLDC systems, while advanced methods like Active Disturbance Rejection Control (ADRC) introduce additional complexity and cost. This research proposes a Variation Model Filter (VMF) based control system that estimates and compensates for the total bias arising from parameter variations and internal uncertainties. This method simplifies the control process, enhances robustness, and boosts performance without requiring extensive parameter tuning or high costs. Additionally, the paper provides a comprehensive mathematical model for the speed dynamics of BLDC motors. Simulation results based on MATLAB/Simulink indicate that the VMF-based PID control system surpasses both linear ADRC and traditional PID controllers in managing speed dynamics and responding to load disturbances. This approach offers an efficient and cost-effective solution for BLDC motor speed control, with significant potential for broader application and further optimization in motor control systems.

@article{Majid2024,
  title     = {Enhancing BLDC Motor Speed Control by Mitigating Bias with a Variation Model Filter},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {15},
  number    = {9},
  year      = {2024},
  publisher = {The Science and Information Organization},
  author    = {Abdul Rahman Abdul Majid},
  doi       = {10.14569/IJACSA.2024.0150925},
  url       = {https://doi.org/10.14569/IJACSA.2024.0150925}
}