Title :
Real-time Discrete Backstepping Neural Control for Induction Motors
Author :
Alanis, Alma Y. ; Sanchez, Edgar N. ; Loukianov, Alexander G.
Author_Institution :
Dept. de Cienc. Computacionales, Univ. de Guadalajara, Guadalajara, Mexico
fDate :
3/1/2011 12:00:00 AM
Abstract :
This brief focuses on real-time implementation, as applied to a three-phase induction motor, of results already published in 2007. The proposed controller is based on a high-order neural network, trained online using Kalman filter learning, to approximate a control law designed by the backstepping technique.
Keywords :
Kalman filters; control system synthesis; induction motors; machine control; neurocontrollers; real-time systems; Kalman filter learning; control law design; high order neural network; real-time discrete backstepping neural control; three phase induction motor; Backstepping; Kalman filter learning; high-order neural networks (HONN); real-time implementation; three-phase induction motors;
Journal_Title :
Control Systems Technology, IEEE Transactions on
DOI :
10.1109/TCST.2010.2041780
