Adaptive vector control of a three-phase induction motor using neural networks

Author

Von Zuben, Fernando J. ; Netto, Márcio L A ; Bim, Edson ; Szajner, Jaime

Author_Institution

Sch. of Electr. Eng., Univ. Estadual de Campinas, Sao Paulo, Brazil

Volume

6

fYear

1994

fDate

27 Jun- 2 Jul 1994

Firstpage

3750

Abstract

This work presents nonlinear techniques applied to the speed control of a three-phase squirrel-cage induction motor. Artificial neural networks are used to develop adaptive control strategies based on nonlinear dynamic system identification and nonlinear parameter estimation. The principal results include a nonlinear rotor flux observer based on recurrent neural networks, and a nonlinear rotor time constant estimator based on nonrecurrent neural networks. Computer simulation results are obtained and the performance of the resulting adaptive field-oriented controller is analyzed

Keywords

adaptive control; machine control; parameter estimation; recurrent neural nets; squirrel cage motors; velocity control; adaptive vector control; field-oriented controller; nonlinear dynamic system identification; nonlinear parameter estimation; nonlinear rotor flux observer; nonlinear rotor time constant estimator; nonlinear techniques; nonrecurrent neural networks; recurrent neural networks; speed control; three-phase squirrel-cage induction motor; Adaptive control; Artificial neural networks; Induction motors; Machine vector control; Nonlinear dynamical systems; Programmable control; Recurrent neural networks; Rotors; System identification; Velocity control;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks, 1994. IEEE World Congress on Computational Intelligence., 1994 IEEE International Conference on

Conference_Location

Orlando, FL

Print_ISBN

0-7803-1901-X

Type

conf

DOI

10.1109/ICNN.1994.374806

Filename

374806