Title :
Switched reluctance motor modelling with on-line parameter identification
Author :
Mir, Sayeed ; Husain, Iqbal ; Elbuluk, Malik
Author_Institution :
Akron Univ., OH, USA
Abstract :
A nonlinear model with on-line parameter estimation using recursive identification for switched reluctance motors is presented. The model is robust towards parameter variations in the motor or any system disturbances. The parameters of the model are adjusted to account for errors in rotor position, which allows the use of crude inexpensive position sensors. The proposed modeling approach allows self-tuning of SRMs in a production unit. The model has been tested through simulation and experimentation, which demonstrated the accuracy of estimation of the model
Keywords :
machine control; machine theory; parameter estimation; recursive estimation; reluctance motors; self-adjusting systems; crude inexpensive position sensors; on-line parameter estimation; on-line parameter identification; parameter variations robustness; recursive identification; rotor position errors; switched reluctance motor modelling; system disturbances; AC machines; IEEE members; Parameter estimation; Production; Reluctance machines; Reluctance motors; Robustness; Rotors; Testing; Torque control;
Conference_Titel :
Industry Applications Conference, 1997. Thirty-Second IAS Annual Meeting, IAS '97., Conference Record of the 1997 IEEE
Conference_Location :
New Orleans, LA
Print_ISBN :
0-7803-4067-1
DOI :
10.1109/IAS.1997.643046
