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DC Field | Value | Language |
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dc.contributor.author | Ismail, Razali | - |
dc.contributor.author | Ismail, A.Y | - |
dc.contributor.author | Mat Darus, I.Z. | - |
dc.date.accessioned | 2009-08-03T08:17:05Z | - |
dc.date.available | 2009-08-03T08:17:05Z | - |
dc.date.issued | 2006 | - |
dc.identifier.citation | p.162-168 | en_US |
dc.identifier.isbn | 1-4244-0527-0 | - |
dc.identifier.uri | http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=04339331 | - |
dc.identifier.uri | http://dspace.unimap.edu.my/123456789/6667 | - |
dc.description | Link to publisher's homepage at http://ieeexplore.ieee.org | en_US |
dc.description.abstract | 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. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Institute of Electrical and Electronics Engineering (IEEE) | en_US |
dc.relation.ispartofseries | Proceedings of 2006 4th Student Conference on Research and Development "Towards Enhancing Research Excellence in the Region" (SCOReD 2006) | en_US |
dc.subject | Indentification system | en_US |
dc.subject | Differential equation | en_US |
dc.subject | Neural networks (Computer science) | en_US |
dc.subject | Digital simulation | en_US |
dc.subject | Finite difference methods | en_US |
dc.subject | Plates (Engineering) | en_US |
dc.title | Identification algorithms of flexible structure using neural networks | en_US |
dc.type | Article | en_US |
Appears in Collections: | School of Mechatronic Engineering (Articles) |
Files in This Item:
File | Description | Size | Format | |
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Abstract.pdf | 7.48 kB | Adobe PDF | View/Open |
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