Neural identification and control of a linear induction motor using an α - β model

Author

Benitez, Victor H. ; Loukianov, Alexander G. ; Sanchez, Edgar N.

Author_Institution

CINVESTAV, Mexico City, Mexico

Volume

5

fYear

2003

fDate

4-6 June 2003

Firstpage

4041

Abstract

We present a new method to control a linear induction motor (LIM) using dynamic neural networks. First, we propose a neural identifier of triangular form; this neural model has the structure of a nonlinear block controllable form (NBC). Then, a reduced order observer is designed in order to estimate the secondary fluxes. Finally, a sliding mode control is developed to track velocity and flux magnitude. Simulations are presented to illustrate the applicability of the proposed scheme.

Keywords

linear induction motors; machine control; neurocontrollers; nonlinear control systems; observers; reduced order systems; variable structure systems; velocity control; α-β model; dynamic neural networks; flux magnitude; linear induction motor control; neural identification; neural identifier; nonlinear block controllable form; nonlinear systems; reduced order observer; secondary fluxes; sliding mode control; triangular form; variable structure systems; velocity tracking; Control systems; Delay; Electric variables control; Feedforward neural networks; Fuzzy control; Inductance; Induction motors; Neural networks; Recurrent neural networks; Sliding mode control;

fLanguage

English

Publisher

ieee

Conference_Titel

American Control Conference, 2003. Proceedings of the 2003

ISSN

0743-1619

Print_ISBN

0-7803-7896-2

Type

conf

DOI

10.1109/ACC.2003.1240468

Filename

1240468