A Novel Algorithm Based on EKF to Estimate Rotor Position and Speed for Sensorless PMSM Drivers

Author

Jiang Baojun

Author_Institution

Coll. of Electromech. & Automobile Eng., Chongqing Jiao Tong Univ., Chongqing, China

fYear

2009

fDate

19-20 Dec. 2009

Firstpage

1

Lastpage

4

Abstract

An algorithm based on extended Kalman filter applied to the sensorless PMSM drives to estimate rotor position and speed are described in this paper. The EKF is an optimal recursive estimation algorithm for estimating the states of dynamic nonlinear systems. The system simulation model is established in MATLAB/Simulink. And the sensorless PMSM drive system is implemented on the DSP employed field oriented control (FOC) method. The performance of the system is studied by means of simulation and experiment. The tests prove the effectiveness of the study.

Keywords

Kalman filters; machine vector control; nonlinear control systems; permanent magnet motors; position control; recursive estimation; rotors; sensorless machine control; synchronous motor drives; velocity control; DSP; dynamic nonlinear system; extended Kalman filter; field oriented control; optimal recursive estimation algorithm; permanent magnet synchronous motor; rotor position estimation; sensorless PMSM driver; speed estimation; Control systems; Digital signal processing; MATLAB; Mathematical model; Nonlinear dynamical systems; Nonlinear systems; Recursive estimation; Sensorless control; State estimation; Testing;

fLanguage

English

Publisher

ieee

Conference_Titel

Information Engineering and Computer Science, 2009. ICIECS 2009. International Conference on

Conference_Location

Wuhan

Print_ISBN

978-1-4244-4994-1

Type

conf

DOI

10.1109/ICIECS.2009.5362756

Filename

5362756