Title :
Speed estimation of an induction motor drive using extended Kalman filter
Author :
Shi, K.L. ; Chan, T.F. ; Wong, Y.K. ; Ho, S.L.
Author_Institution :
Dept. of Electr. Eng., Hong Kong Polytech., Hung Hom, China
Abstract :
This paper presents a detailed study of the extended Kalman filter (EKF) far estimating the rotor speed of an induction motor drive. The general structure of the Kalman filter is reviewed and the various system vectors and matrices are defined. By including the rotor speed as a state variable, the EKF equations are established from a discrete two-axis model of the three-phase induction motor. Using the software MATLAB/Simulink, simulation of the EKF speed estimation algorithm is carried out for an induction motor drive with constant V/Hz frequency control and an induction motor drive with direct self control. The investigations show that the EKF is capable of tracking the actual rotor speed provided that the elements of the covariance matrices are properly selected. Moreover, the performance of the EKF is satisfactory even in the presence of noise or when there are variations in the induction machine parameters
Keywords :
Kalman filters; covariance matrices; digital simulation; electric machine analysis computing; frequency control; induction motor drives; machine control; parameter estimation; rotors; MATLAB/Simulink software; constant V/Hz frequency control; covariance matrices; direct self control; discrete two-axis model; extended Kalman filter; induction motor drive; rotor speed estimation; three-phase induction motor; Equations; Frequency control; Frequency estimation; Induction motor drives; Induction motors; Kalman filters; MATLAB; Mathematical model; Rotors; Software algorithms;
Conference_Titel :
Power Engineering Society Winter Meeting, 2000. IEEE
Print_ISBN :
0-7803-5935-6
DOI :
10.1109/PESW.2000.849963