Title :
Observers for induction motor state and parameter estimation
Author :
Atkinson, David J. ; Acarnley, Paul P. ; Finch, John W.
Author_Institution :
Newcastle-upon-Tyne Univ., UK
Abstract :
The Kalman filter in its basic form is a state estimator and can be applied to the problem of estimating induction motor rotor currents in a vector control scheme. This filter is shown to combine information from the plant model with output measurements to produce an optimal estimate of the unmeasured states. Also described is the application of the extended Kalman filter algorithm to the online estimation of rotor resistance in an induction motor drive. Significant savings in computing requirements are obtained with a reduced-order model of the motor, in which measured, rather than computed, values of stator currents are used
Keywords :
Kalman filters; control system analysis computing; electric current control; electric drives; induction motors; machine control; machine theory; parameter estimation; rotors; state estimation; stators; Kalman filter; algorithm; control system analysis computing; drive; electric current control; induction motor; machine control; machine theory; parameter estimation; rotor currents; rotor resistance; state estimation; stator currents; vector control; Electrical resistance measurement; Induction motor drives; Induction motors; Information filtering; Information filters; Machine vector control; Observers; Parameter estimation; Rotors; State estimation;
Journal_Title :
Industry Applications, IEEE Transactions on
