Paper Info
Title
Discrete-Time Neural Sliding-Mode Block Control for a DC Motor With Controlled Flux
Abstract
An adaptive discrete-time tracking controller for a direct current motor with controlled excitation flux is presented. A recurrent neural network is used to identify the plant model; this neural identifier is trained with an extended Kalman filter algorithm. Then, the discrete-time block-control and sliding-mode techniques are used to develop the trajectory tracking. This paper also includes the respective stability analysis for the whole closed-loop system. The effectiveness of the proposed control scheme is verified via real-time implementation.
Year
DOI
Venue
2012
10.1109/TIE.2011.2161246
IEEE Transactions on Industrial Electronics
Keywords
Field
DocType
DC motors,Kalman filters,adaptive control,closed loop systems,discrete time systems,machine control,neurocontrollers,nonlinear filters,position control,recurrent neural nets,stability,variable structure systems,adaptive controller,closed-loop system,controlled excitation flux,dc motor,direct current motor,discrete-time neural control,extended Kalman filter algorithm,neural identifier,plant model,recurrent neural network,sliding-mode block control,stability analysis,tracking controller,trajectory tracking,Direct current (dc) motor,neural networks (NNs),sliding-mode (SM) control
Control theory,Control theory,Recurrent neural network,DC motor,Control engineering,Kalman filter,Discrete time and continuous time,Adaptive control,Engineering,Artificial neural network,Machine control
Journal
Volume
Issue
ISSN
59
2
0278-0046
Citations 
PageRank 
References 
11
0.85
15
Authors
4
Name
Order
Citations
PageRank
Carlos E. Castañeda1234.19
Loukianov, Alexander G.23010.04
Sanchez, Edgar N.3789.09
Castillo-Toledo, Bernardino4121.58