Title :
Discrete-time Neural Network Control for a Linear Induction Motor
Author :
Hernandez-Gonzalez, M. ; Sanchez, E.N. ; Loukianov, A.G.
Author_Institution :
CINVESTAV, Unidad Guadalajara, Guadalajara
Abstract :
This paper presents a discrete-time control for a linear induction motor (LIM). First, an identifier is proposed with a nonlinear block controllable form (NBC) structure. This identifier is based on a discrete-time high order neural network trained on-line with an extended Kalman filter (EKF)-based algorithm. Then, a sliding mode control is used to achieve the purpose of tracking velocity and magnitude flux. The neural control performance is illustrated via simulations.
Keywords :
Kalman filters; discrete time systems; learning (artificial intelligence); linear induction motors; neurocontrollers; velocity control; discrete-time control; extended Kalman filter; linear induction motor; magnitude flux; neural network; nonlinear block control; velocity tracking; Control systems; Induction motors; Intelligent control; Neural networks; Nonlinear control systems; Nonlinear systems; Recurrent neural networks; Sliding mode control; Switching frequency; USA Councils;
Conference_Titel :
Intelligent Control, 2008. ISIC 2008. IEEE International Symposium on
Conference_Location :
San Antonio, TX
Print_ISBN :
978-1-4244-2224-1
Electronic_ISBN :
2158-9860
DOI :
10.1109/ISIC.2008.4635945
