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

Authors: Haigang Zhang; Xuan Chen; Piao Liu; Decheng Zhao; Bulai Wang

Addresses: School of Rail Transit, Shanghai Institute of Technology, Shanghai, China ' School of Rail Transit, Shanghai Institute of Technology, Shanghai, China ' School of Rail Transit, Shanghai Institute of Technology, Shanghai, China ' School of Rail Transit, Shanghai Institute of Technology, Shanghai, China ' School of Rail Transit, Shanghai Institute of Technology, Shanghai, China

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.

Keywords: limited memory least square method; parameter identification; PMSM; model reference adaptation system.

DOI: 10.1504/IJICT.2022.124808

International Journal of Information and Communication Technology, 2022 Vol.21 No.2, pp.154 - 169

Received: 11 May 2020
Accepted: 05 Nov 2020
Published online: 09 Aug 2022 *

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