Load torque estimation in sensorless PMSM drive using Unscented Kalmana Filter

Abstract

This paper describes a study and experimental verification of sensorless control of Permanent Magnet Synchronous Motor. There are proposed novel estimation strategy based on the Unscented Kalman Filter, using only the measurement of the motor current for on-line estimation of speed, rotor position and load torque. Information about the load is important for complex drive control systems like robot arm. It is rarely obtained by estimation especially in sensorless systems. Used Kalman filter is an optimal state estimator and is usually applied to a dynamic system that involves a random noise environment. Control structure with Kalman filtering algorithm, in real time requires a very efficient signal processor, adapted to perform complex matrix calculations. Experimental results have been carried out to verify the effectiveness and applicability of the novel proposed estimation technique.