Title :
Robust rotor flux, rotor resistance and speed estimation of an induction machine using the extended Kalman filter
Author :
El Moucary, Ch. ; Soto, G. Garcia ; Mendes, E.
Author_Institution :
Lab. de Genie Electr. de Paris, Univ. de Paris-Sud, Orsay, France
Abstract :
This paper deals with robust flux, speed, and rotor resistance estimation of sensorless induction motor drives using the extended Kalman filter (EKF) algorithm. A reduced dynamic motor model is used which reduces the computational requirements of the EKF. The originality of the proposed structure lies in the simultaneous estimation of the shaft speed and rotor resistance. Due to this aim, the state-space vector is extended to the shaft speed and the rotor resistance. Since these two quantities are correlated, a small high frequency signal is added to the flux reference in order to permit the estimation of both quantities. Computer simulations and experimental tests have been carried out to show the effectiveness of the proposed method
Keywords :
Kalman filters; control system analysis computing; control system synthesis; electric machine analysis computing; induction motor drives; machine testing; machine theory; machine vector control; parameter estimation; robust control; rotors; state-space methods; velocity control; computational requirements; computer simulation; control performance; control simulation; extended Kalman filter; high frequency signal; reduced dynamic motor model; rotor flux estimation; rotor resistance estimation; rotor speed estimation; sensorless induction motor drives; shaft speed estimation; state-space vector; Computer simulation; Covariance matrix; Frequency estimation; Induction machines; Induction motor drives; Machine vector control; Robustness; Rotors; Shafts; Stators;
Conference_Titel :
Industrial Electronics, 1999. ISIE '99. Proceedings of the IEEE International Symposium on
Conference_Location :
Bled
Print_ISBN :
0-7803-5662-4
DOI :
10.1109/ISIE.1999.798705
