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Decoupling Control of Permanent Magnet Synchronous Motor Based on Parameter Identification of Fuzzy Least Square Method

By Xin Liu, Yanfei Pan, Yilin Zhu, Hui Han, and Lei Ji
Progress In Electromagnetics Research M, Vol. 103, 49-60, 2021


In order to improve the performance of decoupling control for an interior permanent magnet synchronous motor (IPMSM), a recursive least square algorithm with fuzzy forgetting factor is proposed to identify IPMSM parameters. Firstly, the problems of coupling and parameter identification of IPMSM are analyzed. Secondly, the identification process of resistance and flux linkage is analyzed, and the static parameters are identified as the initial value or constant value. Thirdly, fuzzy control is used to dynamically adjust the forgetting factor in the recursive least square algorithm to make the identification of direct axis and quadrature axis inductance parameters more accurate. Finally, the effectiveness and accuracy of the proposed parameter identification algorithm are verified on the platform, and the good performance of the proposed algorithm in decoupling control is verified. The experimental results show that the identification method can accurately identify the motor parameters in static state and dynamic state. At the same time, the forgetting factor is dynamically adjusted to improve the parameter identification effect and decoupling control performance of the motor.


Xin Liu, Yanfei Pan, Yilin Zhu, Hui Han, and Lei Ji, "Decoupling Control of Permanent Magnet Synchronous Motor Based on Parameter Identification of Fuzzy Least Square Method," Progress In Electromagnetics Research M, Vol. 103, 49-60, 2021.


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