Real-Time Discrete Neural Block Control Using Sliding Modes for Electric Induction Motors

Author

Alanis, Alma Y. ; Sanchez, Edgar N. ; Loukianov, Alexander G. ; Perez-Cisneros, Marco A.

Author_Institution

Dept. de Cienc. Computacionales, Univ. de Guadalajara, Zapopan, Mexico

Volume

18

Issue

1

fYear

2010

Firstpage

11

Lastpage

21

Abstract

This paper deals with real-time adaptive tracking for discrete-time induction motors in the presence of bounded disturbances. A high-order neural-network structure is used to identify the plant model, and based on this model, a discrete-time control law is derived, which combines discrete-time block-control and sliding-mode techniques. This paper also includes the respective stability analysis for the whole system with a strategy to avoid adaptive weight zero-crossing. The scheme is implemented in real time using a three-phase induction motor.

Keywords

adaptive control; discrete time systems; induction motors; machine control; neurocontrollers; real-time systems; stability; variable structure systems; discrete-time block-control; discrete-time induction motors; electric induction motors; realtime adaptive tracking; realtime discrete neural block control; sliding modes; stability analysis; three-phase induction motor; Discrete-time nonlinear systems; electric induction motor; extended Kalman filtering (EKF) learning; neural block control (NBC); sliding modes;

fLanguage

English

Journal_Title

Control Systems Technology, IEEE Transactions on

Publisher

ieee

ISSN

1063-6536

Type

jour

DOI

10.1109/TCST.2008.2009466

Filename

4814535