Identification algorithms of flexible structure using neural networks
This paper present an investigation into the development of identification system approaches for dynamic modelling characterization of a two dimensional flexible plate structures. The least square and recursive least square are used to obtain linear parametric model of the system. Furthermore, non-p...
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| Format: | Conference or Workshop Item |
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2006
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| _version_ | 1825909995046174720 |
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| author | Ismail, R. Ismail, A. Y. Mat Darus, I. Z. |
| author_facet | Ismail, R. Ismail, A. Y. Mat Darus, I. Z. |
| author_sort | Ismail, R. |
| collection | ePrints |
| description | This paper present an investigation into the development of identification system approaches for dynamic modelling characterization of a two dimensional flexible plate structures. The least square and recursive least square are used to obtain linear parametric model of the system. Furthermore, non-parametric models of the system are developed using Multi-layer Perceptron Neural Networks (MLP-NN) and Elman Neural Networks (ENN). A simulation algorithm of the plate is developed through a discretisation of the governing partial differential equation formulation of the plate dynamics using finite difference methods. The finite duration step input is applied to simulation algorithm of the plate. Finally a comparative performance of the approaches used is presented and discussed. |
| first_indexed | 2024-03-05T18:10:28Z |
| format | Conference or Workshop Item |
| id | utm.eprints-7130 |
| institution | Universiti Teknologi Malaysia - ePrints |
| last_indexed | 2024-03-05T18:10:28Z |
| publishDate | 2006 |
| record_format | dspace |
| spelling | utm.eprints-71302017-08-31T15:23:37Z http://eprints.utm.my/7130/ Identification algorithms of flexible structure using neural networks Ismail, R. Ismail, A. Y. Mat Darus, I. Z. TJ Mechanical engineering and machinery This paper present an investigation into the development of identification system approaches for dynamic modelling characterization of a two dimensional flexible plate structures. The least square and recursive least square are used to obtain linear parametric model of the system. Furthermore, non-parametric models of the system are developed using Multi-layer Perceptron Neural Networks (MLP-NN) and Elman Neural Networks (ENN). A simulation algorithm of the plate is developed through a discretisation of the governing partial differential equation formulation of the plate dynamics using finite difference methods. The finite duration step input is applied to simulation algorithm of the plate. Finally a comparative performance of the approaches used is presented and discussed. 2006 Conference or Workshop Item PeerReviewed Ismail, R. and Ismail, A. Y. and Mat Darus, I. Z. (2006) Identification algorithms of flexible structure using neural networks. In: Scored 2006 - Proceedings of 2006 4th Student Conference on Research and Development "Towards Enhancing Research Excellence in the Region", Malaysia. http://ieeexplore.ieee.org |
| spellingShingle | TJ Mechanical engineering and machinery Ismail, R. Ismail, A. Y. Mat Darus, I. Z. Identification algorithms of flexible structure using neural networks |
| title | Identification algorithms of flexible structure using neural networks |
| title_full | Identification algorithms of flexible structure using neural networks |
| title_fullStr | Identification algorithms of flexible structure using neural networks |
| title_full_unstemmed | Identification algorithms of flexible structure using neural networks |
| title_short | Identification algorithms of flexible structure using neural networks |
| title_sort | identification algorithms of flexible structure using neural networks |
| topic | TJ Mechanical engineering and machinery |
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