Disturbance estimation for sensorless PMSM drive with Unscented Kalman Filter

Abstract

This paper describes a study and experimental verification of sensorless control of Permanent Magnet Synchronous Motor in mechatronics application. 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 disturbance - load torque. Information about the load is important for complex drive control systems like robot arm. It is seldom obtained by estimation way 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 unscented algorithm, in real time requires a very efficient signal processor. Experimental results have been carried out to verify the effectiveness and applicability of the novel proposed estimation technique.