Research on control strategy of permanent magnet synchronous motor based on improved MRAS.

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.