A computational framework for stability-constrained offline PI tuning of BLDC FOC systems using gray wolf...

Proportional-Integral (PI) controllers are widely used in Field-Oriented Control (FOC) systems for Brushless DC (BLDC) motors because they are simple. However, their performance relies heavily on proper parameter tuning. Traditional methods like Ziegler-Nichols or trial-and-error can give unpredictable results when operating conditions or loads change. This study introduces a computer-based approach for stable offline PI tuning in BLDC FOC systems using the Gray Wolf Optimization (GWO) algorithm. • The proposed framework integrates mathematical modeling of the BLDC motor, stability rules, multi-objective evaluation, and automated optimization steps into a single software process. • The proposed framework also offers repeatable tuning steps, methods for setting initial parameters, progress tracking, and performance checks, making it easier to reuse in engineering projects. • The results show that this method significantly improves system response. With no load, speed overshoot dropped from about 20% (0.96 pu) in standard FOC to around 3% (0.82 pu) with FOC-GWO, and the initial torque surge decreased from 0.118 pu to 0.072 pu. When a load disturbance occurs, the FOC-GWO system has a smaller speed drop, recovers faster, and shows less fluctuation in speed and torque than the traditional method.