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

Authors

Rakhmat Agung Ramadhani, Ika Noer Syamsiana, Arwin Datumaya Wahyudi Sumari, Moechammad Sarosa

Published in

MethodsX. Volume 17. Pages 104114. Epub Aug 22, 2026.

Abstract

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.

PMID:
42732364
Bibliographic data and abstract were imported from PubMed on 13 Sep 2026.

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