DocumentCode
2191871
Title
Identification of a nonlinear motor system with neural networks
Author
Sio, K.C. ; Lee, C.K.
Author_Institution
Dept. of Electron. Eng., Hong Kong Polytech. Univ., Hung Hom, Hong Kong
Volume
1
fYear
1996
fDate
18-21 Mar 1996
Firstpage
287
Abstract
In this paper, system identification with neural networks is studied. The insufficiency of a static feedforward neural network and a single-layer real-time recurrent neural network in system identification is discussed. Also, a modified recurrent network is proposed for a remedy. Derivations and simulations are provided to verify the beneficial properties of the proposed network
Keywords
feedforward neural nets; identification; machine control; multilayer perceptrons; nonlinear control systems; recurrent neural nets; servomotors; modified recurrent network; neural networks; nonlinear motor system; single-layer real-time recurrent neural network; static feedforward neural network; system identification; Algorithm design and analysis; Backpropagation algorithms; Multi-layer neural network; Network topology; Neural networks; Neurofeedback; Power system modeling; Real time systems; Recurrent neural networks; System identification;
fLanguage
English
Publisher
ieee
Conference_Titel
Advanced Motion Control, 1996. AMC '96-MIE. Proceedings., 1996 4th International Workshop on
Conference_Location
Mie
Print_ISBN
0-7803-3219-9
Type
conf
DOI
10.1109/AMC.1996.509420
Filename
509420
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