System Identification of Industrial Debutanizer Column
Development of a suitable model is the most challenging problem for the distillation columns due to their nonlinear and complex behavior. First Order Plus Time Delay (FOPTD) models using transfer functions and Nonlinear Autoregressive with Exogenous Input (NLARX) models described by sigmoid function...
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Institute of Electrical and Electronics Engineers Inc.
2019
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my.utp.eprints.235882021-08-19T07:55:59Z System Identification of Industrial Debutanizer Column Fatima, S.A. Zabiri, H. Ammar Taqvi, S.A. Ramli, N. Development of a suitable model is the most challenging problem for the distillation columns due to their nonlinear and complex behavior. First Order Plus Time Delay (FOPTD) models using transfer functions and Nonlinear Autoregressive with Exogenous Input (NLARX) models described by sigmoid function were used in this study to identify the dynamics of the industrial debutanizer column. The results demonstrated that linear models were not able to approximate the behavior of system whereas the NLARX models performed well in capturing the nonlinear dynamics of debutanizer column. The prediction capability of the developed NLARX model was found to be 91.26 and 86.56 for top and bottom composition respectively. © 2019 IEEE. Institute of Electrical and Electronics Engineers Inc. 2019 Conference or Workshop Item NonPeerReviewed https://www.scopus.com/inward/record.uri?eid=2-s2.0-85084319549&doi=10.1109%2fICCSCE47578.2019.9068541&partnerID=40&md5=133aab77a35783ee65e219366d701af6 Fatima, S.A. and Zabiri, H. and Ammar Taqvi, S.A. and Ramli, N. (2019) System Identification of Industrial Debutanizer Column. In: UNSPECIFIED. http://eprints.utp.edu.my/23588/ |
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Development of a suitable model is the most challenging problem for the distillation columns due to their nonlinear and complex behavior. First Order Plus Time Delay (FOPTD) models using transfer functions and Nonlinear Autoregressive with Exogenous Input (NLARX) models described by sigmoid function were used in this study to identify the dynamics of the industrial debutanizer column. The results demonstrated that linear models were not able to approximate the behavior of system whereas the NLARX models performed well in capturing the nonlinear dynamics of debutanizer column. The prediction capability of the developed NLARX model was found to be 91.26 and 86.56 for top and bottom composition respectively. © 2019 IEEE. |
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Conference or Workshop Item |
author |
Fatima, S.A. Zabiri, H. Ammar Taqvi, S.A. Ramli, N. |
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Fatima, S.A. Zabiri, H. Ammar Taqvi, S.A. Ramli, N. System Identification of Industrial Debutanizer Column |
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Fatima, S.A. Zabiri, H. Ammar Taqvi, S.A. Ramli, N. |
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Fatima, S.A. |
title |
System Identification of Industrial Debutanizer Column |
title_short |
System Identification of Industrial Debutanizer Column |
title_full |
System Identification of Industrial Debutanizer Column |
title_fullStr |
System Identification of Industrial Debutanizer Column |
title_full_unstemmed |
System Identification of Industrial Debutanizer Column |
title_sort |
system identification of industrial debutanizer column |
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Institute of Electrical and Electronics Engineers Inc. |
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2019 |
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https://www.scopus.com/inward/record.uri?eid=2-s2.0-85084319549&doi=10.1109%2fICCSCE47578.2019.9068541&partnerID=40&md5=133aab77a35783ee65e219366d701af6 http://eprints.utp.edu.my/23588/ |
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