Title :
Application of an extended Kalman filter to rotor speed and resistance estimation in induction motor vector control
Author :
Ouhrouche, M.A. ; Lefebvre, S. ; Do, X.D.
Author_Institution :
Lab. des Technol. Electrochimiques, Hydro-Quebec, Shawinigan, Que., Canada
Abstract :
The vector control method allows high performance control of torque and speed to be achieved from an induction machine. The decoupling of the flux and the electromagnetic torque, obtained by field orientation, depends on the precision and the accuracy of the estimated states. This paper presents the application of the extended Kalman filter (EKF) to the online estimation of the rotor resistance, electrical speed and flux components. The EKF algorithm combines information from the process or the plant model with output measurements to produce an optimal estimate of the unmeasured states. The estimation of the rotor speed allows the implementation of sensorless control
Keywords :
Kalman filters; control system analysis; induction motors; machine control; machine theory; parameter estimation; rotors; electromagnetic torque decoupling; extended Kalman filter; flux decoupling; induction motor vector control; rotor resistance estimation; rotor speed estimation; sensorless control; DC machines; Inductance; Induction machines; Induction motors; Machine vector control; Rotors; Samarium; State estimation; Stators; Torque control;
Conference_Titel :
Electrical and Computer Engineering, 1998. IEEE Canadian Conference on
Conference_Location :
Waterloo, Ont.
Print_ISBN :
0-7803-4314-X
DOI :
10.1109/CCECE.1998.682743