Research on PMSM Parameter Identification Based on Improved Recursive Least Squares
YAN Xia
HE Yong
ZHANG Qingming
YAO Kaixue
YANG Xiuwen
Abstract：In view of the problems of"data saturation"and"system noise"in parameter identification of permanent magnet synchronous motor,the recursive least square method has slow convergence speed,large fluctuation range and biased identification results.In this paper,a recursive least square method based on adaptive forgetting factors and instrumental variables is proposed by analyzing the properties of forgetting factors and instrumental variables.In this method,the error between the predicted output value and the real value of the motor model is used to construct the dynamic adaptive forgetting factor adjustment function,so as to better balance the influence of the old and new data on the identification of motor parameters.At the same time,instrumental variables are added to solve the problem that the identification results are unbiased under the influence of colored noise.The simulation results show that the algorithm has good convergence ability and stability under the adaptive forgetting factor adjustment,and the instrumen-tal variables are used to ensure that the identification results are unbiased.
Keywords：permanent magnet synchronous motorparameter identificationrecursive least squaresadaptive forgetting fac-torinstrumental variable
Publication Date：2025-12-20
Online Publishing Date：2026-03-09(First online date of this platform, not the publication date of the document)
Pages：7( 3570-3576 )