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: | , |
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| Format: | Article |
| Published: |
Multi-Science Publishing Co Ltd.
2006
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| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/9042/ http://dx.doi.org/10.1260/026309206778494274 |
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| Summary: | 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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