Comparative Study of Several Nonlinear Identification Algorithms for PMSM Rotor Flux Linkage

Abstract

Accurate identification of rotor flux linkage is an effective method to realize working status monitoring of permanent magnet and high-performance control of permanent magnet synchronous motor (PMSM) drive system. The current rotor flux linkage identification methods and their technical characteristics are reviewed firstly, and then, the identification method based on Unscented Kalman Filter (UKF), Particle Filter (PF), Unscented Particle Filter (UPF) and algebraic identification algorithm are also proposed to identify rotor flux linkage. The identification performance of UKF, PF, UPF and algebraic identification algorithm is studied and compared in gaussian distribution noise and non-gaussian distribution noise by means of simulation, and the identification performance of algebraic identification algorithm is verified by experiment. Research achievements provide some effective references for achieving high performance control and reliable permanent magnet demagnetization fault diagnosis of PMSM drive system.