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Radial basis function (RBF) for non-linear dynamic system identification

One of the key problem in system identification is finding a suitable model structure. In this paper, radial basis function (RBF) network using various basis functions are trained to represent discrete-time nonlinear dynamic systems and the results are compared. The orthogonal least squarealgorithm...

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Main Authors: Ahmad, Robiah, Jamaluddin, Hishamuddin
Format: Article
Language:English
Published: Penerbit UTM Press 2002
Subjects:
TJ Mechanical engineering and machinery
Online Access:http://eprints.utm.my/id/eprint/1301/1/JT36A4.pdf
http://eprints.utm.my/id/eprint/1301/
http://www.penerbit.utm.my/onlinejournal/36/A/JT36A4.pdf
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id my.utm.1301
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spelling my.utm.13012017-11-01T04:17:44Z http://eprints.utm.my/id/eprint/1301/ Radial basis function (RBF) for non-linear dynamic system identification Ahmad, Robiah Jamaluddin, Hishamuddin TJ Mechanical engineering and machinery One of the key problem in system identification is finding a suitable model structure. In this paper, radial basis function (RBF) network using various basis functions are trained to represent discrete-time nonlinear dynamic systems and the results are compared. The orthogonal least squarealgorithm is employed to select parsimonious RBF models. To demonstrate the identification procedure two examples of modelling on linear system were included. Penerbit UTM Press 2002-06 Article PeerReviewed application/pdf en http://eprints.utm.my/id/eprint/1301/1/JT36A4.pdf Ahmad, Robiah and Jamaluddin, Hishamuddin (2002) Radial basis function (RBF) for non-linear dynamic system identification. Jurnal Teknologi A (36A). pp. 39-54. ISSN 0127-9696 http://www.penerbit.utm.my/onlinejournal/36/A/JT36A4.pdf
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
language English
topic TJ Mechanical engineering and machinery
spellingShingle TJ Mechanical engineering and machinery
Ahmad, Robiah
Jamaluddin, Hishamuddin
Radial basis function (RBF) for non-linear dynamic system identification
description One of the key problem in system identification is finding a suitable model structure. In this paper, radial basis function (RBF) network using various basis functions are trained to represent discrete-time nonlinear dynamic systems and the results are compared. The orthogonal least squarealgorithm is employed to select parsimonious RBF models. To demonstrate the identification procedure two examples of modelling on linear system were included.
format Article
author Ahmad, Robiah
Jamaluddin, Hishamuddin
author_facet Ahmad, Robiah
Jamaluddin, Hishamuddin
author_sort Ahmad, Robiah
title Radial basis function (RBF) for non-linear dynamic system identification
title_short Radial basis function (RBF) for non-linear dynamic system identification
title_full Radial basis function (RBF) for non-linear dynamic system identification
title_fullStr Radial basis function (RBF) for non-linear dynamic system identification
title_full_unstemmed Radial basis function (RBF) for non-linear dynamic system identification
title_sort radial basis function (rbf) for non-linear dynamic system identification
publisher Penerbit UTM Press
publishDate 2002
url http://eprints.utm.my/id/eprint/1301/1/JT36A4.pdf
http://eprints.utm.my/id/eprint/1301/
http://www.penerbit.utm.my/onlinejournal/36/A/JT36A4.pdf
_version_ 1643643296300400640
score 13.159267

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