The Study Of Dynamic Response Using ARX Model In Extraction Process

This work presents a model using system identification approach namely as ARX to represent the dynamic response for essential oil extraction process. A fresh set of data under feed in disturbance was collected using MATLAB Simulink. The 3000 samples of data was collected by using PRBS as an input an...

Full description

Saved in:
Bibliographic Details
Main Authors: M. Yusoff, Z., A. Aziz, M. A., Razali, N. F., Nordin, S. A., Zainal Abidin, Amar Faiz, Zain, N. M.
Format: Article
Language:English
Published: J Fundam Appl Sci. 2017
Subjects:
Online Access:http://eprints.utem.edu.my/id/eprint/22716/2/%5B2017-10-05%5D%20The%20Study%20of%20Dynamic%20Response%20using%20ARX%20Model%20in%20Extraction%20Process.pdf
http://eprints.utem.edu.my/id/eprint/22716/
http://jfas.info/psjfas/index.php/jfas/article/view/2916/1535
http://dx.doi.org/10.4314/jfas.v9i4s.8
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.utem.eprints.22716
record_format eprints
spelling my.utem.eprints.227162021-08-22T16:22:11Z http://eprints.utem.edu.my/id/eprint/22716/ The Study Of Dynamic Response Using ARX Model In Extraction Process M. Yusoff, Z. A. Aziz, M. A. Razali, N. F. Nordin, S. A. Zainal Abidin, Amar Faiz Zain, N. M. T Technology (General) TA Engineering (General). Civil engineering (General) This work presents a model using system identification approach namely as ARX to represent the dynamic response for essential oil extraction process. A fresh set of data under feed in disturbance was collected using MATLAB Simulink. The 3000 samples of data was collected by using PRBS as an input and temperature in oC as an output. The collected data was separated into two groups; training data and estimation data by using interlacing technique. The model estimation was done by using linear regression method. The robustness of the model was evaluated by using best fit (R2), OSA, root mean square error (RMSE), correlation analysis and residual analysis (histogram). Based on validation results, the ARX model was successfully capturing the dynamic response of extraction process by provide the high best fit, low RMSE error and normally distributed by producing small mean and variance. J Fundam Appl Sci. 2017-05 Article PeerReviewed text en http://eprints.utem.edu.my/id/eprint/22716/2/%5B2017-10-05%5D%20The%20Study%20of%20Dynamic%20Response%20using%20ARX%20Model%20in%20Extraction%20Process.pdf M. Yusoff, Z. and A. Aziz, M. A. and Razali, N. F. and Nordin, S. A. and Zainal Abidin, Amar Faiz and Zain, N. M. (2017) The Study Of Dynamic Response Using ARX Model In Extraction Process. Journal Of Fundamental And Applied Sciences, 9 (4S). pp. 145-159. ISSN 1112-9867 http://jfas.info/psjfas/index.php/jfas/article/view/2916/1535 http://dx.doi.org/10.4314/jfas.v9i4s.8
institution Universiti Teknikal Malaysia Melaka
building UTEM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknikal Malaysia Melaka
content_source UTEM Institutional Repository
url_provider http://eprints.utem.edu.my/
language English
topic T Technology (General)
TA Engineering (General). Civil engineering (General)
spellingShingle T Technology (General)
TA Engineering (General). Civil engineering (General)
M. Yusoff, Z.
A. Aziz, M. A.
Razali, N. F.
Nordin, S. A.
Zainal Abidin, Amar Faiz
Zain, N. M.
The Study Of Dynamic Response Using ARX Model In Extraction Process
description This work presents a model using system identification approach namely as ARX to represent the dynamic response for essential oil extraction process. A fresh set of data under feed in disturbance was collected using MATLAB Simulink. The 3000 samples of data was collected by using PRBS as an input and temperature in oC as an output. The collected data was separated into two groups; training data and estimation data by using interlacing technique. The model estimation was done by using linear regression method. The robustness of the model was evaluated by using best fit (R2), OSA, root mean square error (RMSE), correlation analysis and residual analysis (histogram). Based on validation results, the ARX model was successfully capturing the dynamic response of extraction process by provide the high best fit, low RMSE error and normally distributed by producing small mean and variance.
format Article
author M. Yusoff, Z.
A. Aziz, M. A.
Razali, N. F.
Nordin, S. A.
Zainal Abidin, Amar Faiz
Zain, N. M.
author_facet M. Yusoff, Z.
A. Aziz, M. A.
Razali, N. F.
Nordin, S. A.
Zainal Abidin, Amar Faiz
Zain, N. M.
author_sort M. Yusoff, Z.
title The Study Of Dynamic Response Using ARX Model In Extraction Process
title_short The Study Of Dynamic Response Using ARX Model In Extraction Process
title_full The Study Of Dynamic Response Using ARX Model In Extraction Process
title_fullStr The Study Of Dynamic Response Using ARX Model In Extraction Process
title_full_unstemmed The Study Of Dynamic Response Using ARX Model In Extraction Process
title_sort study of dynamic response using arx model in extraction process
publisher J Fundam Appl Sci.
publishDate 2017
url http://eprints.utem.edu.my/id/eprint/22716/2/%5B2017-10-05%5D%20The%20Study%20of%20Dynamic%20Response%20using%20ARX%20Model%20in%20Extraction%20Process.pdf
http://eprints.utem.edu.my/id/eprint/22716/
http://jfas.info/psjfas/index.php/jfas/article/view/2916/1535
http://dx.doi.org/10.4314/jfas.v9i4s.8
_version_ 1709671900076048384
score 13.211869