Abstract
As a typical nonlinear control method, backstepping control can decouple the mathematical model of permanent magnet synchronous motors. In addition, permanent magnet synchronous motor control systems based on the backstepping method can enhance the control performance of the control system to a certain extent. Furthermore, the design step is easy and simple to implement in engineering practice. However, the long-term wear and tear, aging, high temperature caused by changes in the basic parameters of motor and external load sudden changes as well as other factors will bring interference to the control system, leading to reduced-control accuracy and control performance degradation. To solve this problem, this paper suggests a control strategy combining backstepping control and fuzzy control based on backstepping control. It sets the load adaptive law and utilizes fuzzy control to make online real-time adjustments to the control parameters in the backstepping control. This is done to improve the immunity of interference and stability of the control system in response to the changes in the parameters of the body of the motor and sudden changes of the load. The effectiveness and feasibility of this system is verified by MATLAB simulation and experimental results, which provides a feasible solution for permanent magnet synchronous motor immunity and high-precision control occasions.
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Acknowledgements
This work was supported in part by the National Natural Science Foundation of China under Grant 52177056. This work was supported by Key Research and Development Program of Shaanxi Province, No. 2023-YBGY-368. This work was supported by Xi’an Key Laboratory of Electrical Equipment Condition Monitoring and Power Supply Security, Xi’an 710054, China.
Funding
National Natural Science Foundation of China, 52177056, GuangHui Du, Key Research and Development Projects of Shaanxi Province, 2023-YBGY-368, QiXun Zhou.
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Zhang, Y., Yan, Q., Ai, C. et al. Backstepping control of permanent magnet synchronous motors based on load adaptive fuzzy parameter online tuning. J. Power Electron. (2024). https://doi.org/10.1007/s43236-024-00790-9
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DOI: https://doi.org/10.1007/s43236-024-00790-9