Parameter identification of induction motors. 1. The model-based concept

Author

Pappano, V. ; Lyshevski, S.E. ; Friedland, B.

Author_Institution

Dept. of Electr. & Comput. Eng., New Jersey Inst. of Technol., Newark, NJ, USA

Volume

1

fYear

1998

fDate

1-4 Sep 1998

Firstpage

466

Abstract

The model-based identification concept is applied to the problem of parameter identification in induction motors. The convergence of the identification algorithm is investigated using extended and partial data acquisition. The developed approach to parameter identification requires full state measurement. A parameter subset identification methodology and online implementation issues are also introduced using the identification method developed by Lyshevski (1997). These very important side-aspects of the model-based identification concept have not been emphasized in the current literature

Keywords

Lyapunov methods; convergence; induction motors; machine theory; nonlinear systems; parameter estimation; Lyapunov method; convergence; identification; induction motors; model-based method; nonlinear systems; parameter estimation; Data acquisition; Differential equations; Induction machines; Induction motors; Kirchhoff´s Law; Lagrangian functions; Lyapunov method; Machine vector control; Parameter estimation; Stators;

fLanguage

English

Publisher

ieee

Conference_Titel

Control Applications, 1998. Proceedings of the 1998 IEEE International Conference on

Conference_Location

Trieste

Print_ISBN

0-7803-4104-X

Type

conf

DOI

10.1109/CCA.1998.728492

Filename

728492