Grey wolf optimization for intelligent parametric modeling of gradient flexible plate structure.
This paper presents the dynamic modeling of the gradient flexible plate system using System Identification method based on autoregressive with exogenous input model structure and estimated by Grey Wolf Optimization. The experimental rig of the gradient flexible plate was integrated with the data acq...
Saved in:
Main Authors: | , , , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
Tamkang University
2023
|
Subjects: | |
Online Access: | http://eprints.utm.my/106277/1/IZMatDarus2023_GreyWolfOptimizationforIntelligentParametricModeling.pdf http://eprints.utm.my/106277/ http://dx.doi.org/10.6180/jase.202309_26(9).0001 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
id |
my.utm.106277 |
---|---|
record_format |
eprints |
spelling |
my.utm.1062772024-06-20T06:06:53Z http://eprints.utm.my/106277/ Grey wolf optimization for intelligent parametric modeling of gradient flexible plate structure. Hassan, M. H. Jamali, A. R., Lidyana Suffian, M. S. Z. M. Hadi, M. S. Mat Darus, I. Z. TJ Mechanical engineering and machinery This paper presents the dynamic modeling of the gradient flexible plate system using System Identification method based on autoregressive with exogenous input model structure and estimated by Grey Wolf Optimization. The experimental rig of the gradient flexible plate was integrated with the data acquisition and instrumentation to obtain input-output vibration data. The performances of developed models were validated through one step ahead prediction, mean squared error, and correlation tests. The model was verified using the pole-zero diagram to confirm its stability for the controller development. Results indicated that the optimum model to represent the dynamic system of gradient flexible plate was achieved by model order 4 with the mean squared error of 8.0496×10-6. The correlation results proved that the model was unbiased, and falls within the 95% confidence level. Likewise, the model was found to be stable as all the poles of transfer function were within the unit circle. Therefore, the identified model can be confidently used for the controller development to suppress undesirable vibration in the gradient flexible plate structure. Tamkang University 2023 Article PeerReviewed application/pdf en http://eprints.utm.my/106277/1/IZMatDarus2023_GreyWolfOptimizationforIntelligentParametricModeling.pdf Hassan, M. H. and Jamali, A. and R., Lidyana and Suffian, M. S. Z. M. and Hadi, M. S. and Mat Darus, I. Z. (2023) Grey wolf optimization for intelligent parametric modeling of gradient flexible plate structure. Journal of Applied Science and Engineering (Taiwan), 26 (9). pp. 1207-1214. ISSN 2708-9967 http://dx.doi.org/10.6180/jase.202309_26(9).0001 DOI: 10.6180/jase.202309_26(9).0001 |
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 Hassan, M. H. Jamali, A. R., Lidyana Suffian, M. S. Z. M. Hadi, M. S. Mat Darus, I. Z. Grey wolf optimization for intelligent parametric modeling of gradient flexible plate structure. |
description |
This paper presents the dynamic modeling of the gradient flexible plate system using System Identification method based on autoregressive with exogenous input model structure and estimated by Grey Wolf Optimization. The experimental rig of the gradient flexible plate was integrated with the data acquisition and instrumentation to obtain input-output vibration data. The performances of developed models were validated through one step ahead prediction, mean squared error, and correlation tests. The model was verified using the pole-zero diagram to confirm its stability for the controller development. Results indicated that the optimum model to represent the dynamic system of gradient flexible plate was achieved by model order 4 with the mean squared error of 8.0496×10-6. The correlation results proved that the model was unbiased, and falls within the 95% confidence level. Likewise, the model was found to be stable as all the poles of transfer function were within the unit circle. Therefore, the identified model can be confidently used for the controller development to suppress undesirable vibration in the gradient flexible plate structure. |
format |
Article |
author |
Hassan, M. H. Jamali, A. R., Lidyana Suffian, M. S. Z. M. Hadi, M. S. Mat Darus, I. Z. |
author_facet |
Hassan, M. H. Jamali, A. R., Lidyana Suffian, M. S. Z. M. Hadi, M. S. Mat Darus, I. Z. |
author_sort |
Hassan, M. H. |
title |
Grey wolf optimization for intelligent parametric modeling of gradient flexible plate structure. |
title_short |
Grey wolf optimization for intelligent parametric modeling of gradient flexible plate structure. |
title_full |
Grey wolf optimization for intelligent parametric modeling of gradient flexible plate structure. |
title_fullStr |
Grey wolf optimization for intelligent parametric modeling of gradient flexible plate structure. |
title_full_unstemmed |
Grey wolf optimization for intelligent parametric modeling of gradient flexible plate structure. |
title_sort |
grey wolf optimization for intelligent parametric modeling of gradient flexible plate structure. |
publisher |
Tamkang University |
publishDate |
2023 |
url |
http://eprints.utm.my/106277/1/IZMatDarus2023_GreyWolfOptimizationforIntelligentParametricModeling.pdf http://eprints.utm.my/106277/ http://dx.doi.org/10.6180/jase.202309_26(9).0001 |
_version_ |
1802977255361609728 |
score |
13.18916 |