Permanent Magnet Synchronous Motor Fuzzy Forgetting Factor Recursive Least Squares Parameter Identification

doi:10.16182/j.issn1004731x.joss.201809022

Abstract

Abstract: In order to improve the stability and convergence rate of permanent magnet synchronous motor (PMSM) on-line identification, this paper proposes a fuzzy forgetting factor least squares algorithm based on the least squares algorithm with forgetting factor. The linear regression model of permanent magnet synchronous motor is established by using the linearization technique of Pade approximation method. A fuzzy controller is designed by using the current error and the forgetting factor can be adjusted adaptively. The proposed method is applied to the field of on-line identification of permanent magnet synchronous motor stator resistance, which solves the contradiction between the result stability and the convergence rate of the forgetting factor least squares algorithm. Finally, the simulation results show the effectiveness of the proposed method.

Key words: forgetting factor, RLS, fuzzy control, parameter identification, PMSM

CLC Number:

N945.14

Shen Yanxia, Jin Baolong. Permanent Magnet Synchronous Motor Fuzzy Forgetting Factor Recursive Least Squares Parameter Identification[J]. Journal of System Simulation, 2018, 30(9): 3404-3410.

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