Sensorless Control of Synchronous Reluctance Motor Drives Based on the TLS EXIN Neuron

Abstract

This paper proposes a rotor speed and position estimation scheme for the synchronous reluctance motor (SynRM) drive system based on its active flux model in the stator reference frame and the total least squares (TLS) EXIN neuron. Firstly, the active flux model of the SynRM in the stator reference frame is reconstructed to the overdetermined matrix equations. On the basis of that, the estimation of the rotor speed of the SynRM is transferred into solving a TLS problem. The TLS EXIN neuron, which is a recursive TLS algorithm, is used to solve this problem online to extract the rotor speed. The estimated rotor position is obtained from the estimated rotor speed based on the integrator. The feasibility and effectiveness of the proposed rotor speed estimation scheme have been verified by the simulation results.