| Issue |
E3S Web Conf.
Volume 680, 2025
The 4th International Conference on Energy and Green Computing (ICEGC’2025)
|
|
|---|---|---|
| Article Number | 00042 | |
| Number of page(s) | 11 | |
| DOI | https://doi.org/10.1051/e3sconf/202568000042 | |
| Published online | 19 December 2025 | |
Cruise Control of BLDC Motors Using GA-Optimized Super Twisted Sliding Mode Control
1 ISA Laboratory, National School of Applied Sciences (ENSA), Ibn Tofail University, Kénitra 14000, Morocco
2 Laboratoire Universitaire des Sciences Appliquées de Cherbourg (LUSAC), Normandie Univ, UNICAEN, LUSAC, EA 4253, France
* Corresponding author: hasni.anwar20@gmail.com
The rapid development and growing popularity of brushless motors (BLDC) in industrial, automotive and aerospace applications poses a series of inherent challenges, such as precise speed and torque control and, above all, reduced energy efficiency. This work alleviates the above problems by proposing a speed control scheme for brushless motors that takes into account all external disturbances, in particular the variability of load torque with the operating environment. The proposed scheme relies on the use of a controller based on the super-twist sliding mode control strategy (STSMC), whose parameters are optimized using a genetic algorithm (GA). To study the controller’s performance and robustness, two test cases were simulated on Matlab/Simulink. The first consisted in verifying tracking performance against a user-specified speed reference value, and the second in checking robustness in the face of an external disturbance, a time-varying load torque. The recorded performances show a motor response time of between 0.02 s and 0.05 s for constant torque, and between 0.02 s and 0.06 s in the presence of disturbances. This performance verifies the robustness and effectiveness of the proposed control strategy, establishing its viability in dynamic operation.
© The Authors, published by EDP Sciences, 2025
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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