A robust hybrid control strategy for enhancing torque stability and performance in PMSM drives
DOI:
https://doi.org/10.20998/2074-272X.2025.6.09Keywords:
permanent magnet synchronous motor, sliding mode control, proportional resonant control, integral absolute error, integral time absolute error, integral square error, Luenberger observer, Kalman filterAbstract
Introduction. Recently, permanent magnet synchronous motors (PMSMs) have become essential in various high-performance applications, including electric vehicles and renewable energy systems. However, traditional control methods, such as PI controllers, often struggle to handle dynamic operating conditions and external disturbances, resulting in torque ripple and stability issues. Problem. The main issue with existing control strategies is their inability to maintain accurate torque control and system stability under fluctuating loads and varying motor parameters, which negatively impacts performance in real-world applications. Goal. This paper proposes a robust hybrid control strategy that integrates sliding mode control (SMC) with proportional resonant control (PRC), enhanced by Luenberger and Kalman observers. The goal is to improve torque stability, reduce errors, and optimize performance in PMSM drive systems. Methodology. The proposed method combines SMC and PRC to form an SMC-PRC controller, with Luenberger and Kalman observers integrated for effective load torque estimation. Results. The simulation experiments were carried out to compare the effectiveness of the proposed control strategy with that of traditional PI controllers. The results revealed that the SMC-PRC approach offers a notable improvement in overall control performance, including reduced tracking error, enhanced dynamic response, and better stability. Furthermore, the proposed method achieved faster settling times and maintained robust operation under varying system conditions. Scientific novelty. This work introduces a hybrid control approach that combines SMC and PRC with advanced state estimation techniques, providing a robust and efficient solution to PMSM control. Practical value. The proposed method is highly beneficial for applications under dynamic operating conditions, such as electric vehicles and renewable energy systems, improving system efficiency and stability. References 40, tables 7, figures 10.
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