Research on control strategy of permanent magnet synchronous motor based on improved MRAS
by Haigang Zhang; Xuan Chen; Piao Liu; Decheng Zhao; Bulai Wang
International Journal of Information and Communication Technology (IJICT), Vol. 21, No. 2, 2022

Abstract: The identification of internal parameters of PMSM has become a research hotspot in PMSM control system. In this paper, a limited memory least squares identification module is configured inside the traditional model reference adaptive system to identify the parameters of the stator resistance R*, the stator inductance L_s^* and the rotor flux chain ϕ_f^* of the permanent magnet synchronous motor. This method improves the accuracy and speed of identification. The real-time update of the nonlinear variables of the adjustable model improves the accuracy of the speed estimation ω_e^* and reduces the error of calculating the rotation angle and speed. Finally, the proposed method is validated by using MATLAB/Simulink. The results show that the improved model reference adaptive control strategy based on the limited memory least squares identification algorithm reduces the steady-state error. The dynamic performance and control accuracy are improved to some extent compared with the traditional model reference adaptive control method.

Online publication date: Tue, 09-Aug-2022

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