Parametric and non-parametric identification of a two dimensional flexible structure

An investigation into the parametric and non-parametric modelling of a two dimensional flexible plate structure is presented in this paper. The parametric approaches obtaining linear parametric models of the system using recursive least squares and genetic algorithms. The non-parametric models of th...

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Main Authors: Mat Darus, I. Z., Tokhi, M. O.
Format: Article
Published: Multi-Science Publishing Co Ltd. 2006
Subjects:
Online Access:http://eprints.utm.my/9042/
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author Mat Darus, I. Z.
Tokhi, M. O.
author_facet Mat Darus, I. Z.
Tokhi, M. O.
author_sort Mat Darus, I. Z.
building UTeM Institutional Repository
collection Online Access
description An investigation into the parametric and non-parametric modelling of a two dimensional flexible plate structure is presented in this paper. The parametric approaches obtaining linear parametric models of the system using recursive least squares and genetic algorithms. The non-parametric models of the system are developed using a non-linear AutoRegressive process with eXogeneous input model with multi-layered perceptron neural networks, Elman recurrent neural networks and adaptive neuro-fuzzy inference systems. The models are validated using several validation tests including input-output mapping, mean squares of error and correlation tests. A comparative assessment of the techniques used is presented and discussed in terms of accuracy, efficiency and performance in estimating the modes of vibration of the system.
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institution Universiti Teknologi Malaysia
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publisher Multi-Science Publishing Co Ltd.
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spelling utm-90422018-03-07T21:10:40Z http://eprints.utm.my/9042/ Parametric and non-parametric identification of a two dimensional flexible structure Mat Darus, I. Z. Tokhi, M. O. TJ Mechanical engineering and machinery An investigation into the parametric and non-parametric modelling of a two dimensional flexible plate structure is presented in this paper. The parametric approaches obtaining linear parametric models of the system using recursive least squares and genetic algorithms. The non-parametric models of the system are developed using a non-linear AutoRegressive process with eXogeneous input model with multi-layered perceptron neural networks, Elman recurrent neural networks and adaptive neuro-fuzzy inference systems. The models are validated using several validation tests including input-output mapping, mean squares of error and correlation tests. A comparative assessment of the techniques used is presented and discussed in terms of accuracy, efficiency and performance in estimating the modes of vibration of the system. Multi-Science Publishing Co Ltd. 2006 Article PeerReviewed Mat Darus, I. Z. and Tokhi, M. O. (2006) Parametric and non-parametric identification of a two dimensional flexible structure. Journal of Low Frequency Noise Vibration and Active Control, 25 (2). pp. 119-143. ISSN 1461-3484 http://dx.doi.org/10.1260/026309206778494274 10.1260/026309206778494274
spellingShingle TJ Mechanical engineering and machinery
Mat Darus, I. Z.
Tokhi, M. O.
Parametric and non-parametric identification of a two dimensional flexible structure
title Parametric and non-parametric identification of a two dimensional flexible structure
title_full Parametric and non-parametric identification of a two dimensional flexible structure
title_fullStr Parametric and non-parametric identification of a two dimensional flexible structure
title_full_unstemmed Parametric and non-parametric identification of a two dimensional flexible structure
title_short Parametric and non-parametric identification of a two dimensional flexible structure
title_sort parametric and non-parametric identification of a two dimensional flexible structure
topic TJ Mechanical engineering and machinery
url http://eprints.utm.my/9042/
http://eprints.utm.my/9042/
http://eprints.utm.my/9042/