A neural-network-based adaptive estimator of rotor position and speed for permanent magnet synchronous motor

Abstract

In this paper, by measuring the phase voltages and currents of the permanent magnet synchronous motor (PMSM) drive, a neural-network-based rotor position and speed estimation method for PMSM is described. The proposed estimator includes two recurrent neural networks, one is used to estimate rotor speed and rotor position, and the other is used to estimate stator current. Through using an improved recursive prediction error algorithm, on-line adaptative estimation is realized. The simulation results show that the proposed approach gives a good estimation of rotor speed and position. Especially, the proposed approach has low sensitivity to perturbations of the mechanical parameters and torque disturbances.