Analysis of BLDC Motor Speed Error with Fuzzy Logic Control in Static and Dynamic Tests of Trimaran Boats
DOI:
https://doi.org/10.29303/goescienceed.v6i4.1392Keywords:
BLDC motor, fuzzy logic control, speed error, static and dynamic test, trimaran propulsionAbstract
This study analyzes the speed error of Brushless DC (BLDC) motors using fuzzy logic control through static and dynamic tests on a trimaran prototype. The research method involved static validation of sensors, including photodiode, ACS758, and voltage divider, followed by dynamic tests in an artificial wave pool at set points ranging from 6000 to 10,000 RPM. The fuzzy logic controller was designed with error and change of error as input variables and PWM correction as output. The results indicate that validated sensors achieved an average error of less than 5%, ensuring reliable data for control input. In dynamic tests, fuzzy control reduced the average speed error compared to the open-loop system, with the most significant improvement observed at higher speeds. These findings demonstrate that fuzzy logic control enhances synchronization and stability of BLDC motors in marine environments, making it a promising approach for electric propulsion in multihull vessels such as trimarans.
References
Abdelghany, M. A., Elnady, A. O., & Ibrahim, S. O. (2023). Optimum PID controller with fuzzy self-tuning for DC servo motor. Journal of Robotics and Control, 4(4), 500–508. https://doi.org/10.18196/jrc.v4i4.18676
Abdullah, Z. B., Shneen, S. W., & Dakheel, H. S. (2024). Design and implementation of voltage source inverter using sinusoidal PWM to drive a single-phase induction motor. International Journal of Robotics and Control Systems, 4(4), 1527–1546. https://doi.org/10.31763/ijrcs.v4i3.1541
Abdullah, Z. B., Shneen, S. W., & Dakheel, H. S. (2025). Performance enhancement of BLDC motor drive systems using fuzzy logic control and PID controller for improved transient response and stability. International Journal of Robotics and Control Systems, 5(2), Article 1882. https://doi.org/10.31763/ijrcs.v5i2.1882
Arulmozhiyal, R., & Kandiban, R. (2012). Design and implementation of fuzzy PID controller for BLDC motor using FPGA. In 2012 IEEE International Conference on Power Electronics, Drives and Energy Systems (PEDES). IEEE. https://doi.org/10.1109/PEDES.2012.6484251
Bano, F., & Salkuti, S. R. (2023). Control of BLDC motor speed using fuzzy logic controller. In Advances in Electrical and Computer Technologies (pp. 169–179). Springer. https://doi.org/10.1007/978-3-031-18389-8_15
Chhlonh, C., Riawan, D. C., & Suryoatmojo, H. (2019). Modeling and simulation of independent speed steering control for front in-wheel in EV using BLDC motor in MATLAB GUI. In 2019 International Seminar on Intelligent Technology and Its Applications (ISITIA) (pp. 270–275). IEEE. https://doi.org/10.1109/ISITIA.2019.8937199
Gharib, H., & Kovács, G. (2024). Implementation and possibilities of fuzzy logic for optimal operation and maintenance of marine diesel engines. Machines, 12(6), 425. https://doi.org/10.3390/machines12060425
Ginola, D., Tupan, J., & Luhulima, D. (2021). Implementation of fuzzy logic controller in marine propulsion system. Journal of Marine Science and Application, 20(2), 189–198. https://doi.org/10.1007/s11804-021-00218-8
González-González, J. A., et al. (2025). A survey and analysis of multiphase electric propulsion motors and controllers. International Journal of Control and Automation, 23(1). https://doi.org/10.1016/j.jnca.2025.02.005
Kroičs, K., & Būmanis, A. (2024). BLDC motor speed control with digital adaptive PID–fuzzy controller and reduced harmonic content. Energies, 17(6), 1311. https://doi.org/10.3390/en17061311
Muralidharan, S., et al. (2023). Performance analysis of controllers in BLDC motor. E3S Web of Conferences, 387, 01001. https://doi.org/10.1051/e3sconf/202338701001
Nutenki, R., & Varma, B. V. (2024). PID controller design for DC motor speed control. In 2024 Fourth International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT). IEEE. https://doi.org/10.1109/ICAECT60202.2024.10469124
Potdar, T., & Jape, M. V. (2024). Comparison of PI and fuzzy logic control for speed control of induction motor for marine application. In Recent Evolutions in Energy, Drives and e-Vehicles (pp. 445–455). Springer. https://doi.org/10.1007/978-981-97-0763-8_36
Reddy, M. S. P., et al. (2025). Speed control of BLDC motor using PWM and Arduino Uno. E3S Web of Conferences, 619, 02007. https://doi.org/10.1051/e3sconf/202561902007
Shenbagalakshmi, R., Mittal, S. K., Subramaniyan, J., Vengatesan, V., Manikandan, D., & Ramaswamy, K. (2025). Adaptive speed control of BLDC motors for enhanced electric vehicle performance using fuzzy logic. Scientific Reports, 15, Article 12579. https://doi.org/10.1038/s41598-025-90957-6
Shuraiji, A. L., & Shneen, S. W. (2022). Fuzzy logic control and PID controller for brushless permanent magnetic direct current motor: A comparative study. Journal of Robotics and Control, 3(6). https://doi.org/10.18196/jrc.v3i6.15974
Varsha, V., Prabhakaran, S., & Nirmala, T. (2024). Optimizing BLDC motor performance with advanced fuzzy logic PID controller under dynamic load condition. International Research Journal on Advanced Engineering and Management, 2(8), 2573–2578. https://doi.org/10.47392/IRJAEM.2024.2573
Wu, C., & Huang, H. (2016). The research on PMSM fuzzy control in the marine electric propulsion system. International Journal of Control and Automation, 9(2), 353–360. https://doi.org/10.14257/ijca.2016.9.2.33
Zakeer, S. H., & Kamble, S. S. (2019). A new methodology to control the speed of e-vehicles by using brushless DC motor. In 2019 5th International Conference on Advanced Computing & Communication Systems (ICACCS) (pp. 476–481). IEEE. https://doi.org/10.1109/ICACCS.2019.8728371
Zhang, D., & Wang, J. (2019). Fuzzy PID speed control of BLDC motor based on model design. Journal of
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