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Neural-Wiener-based Model Predictive Control (NWMPC) for Methyl Tert-butyl Ether Catalytic Distillation

The reactive distillation of methyl tert-butyl ether (MTBE) involves strong interactions between variables and is a highly nonlinear process. Here, a nonlinear model predictive control (MPC) was proposed to tackle the nonlinearity and the interaction involved in controlling the tray temperature i...

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Main Authors: Sudibyo, Sudibyo, Murat , Muhamad Nazri, Aziz, Norashid
Format: Article
Language:English
Published: Taylor's University 2015
Subjects:
TA1-2040 Engineering (General). Civil engineering (General)
Online Access:http://eprints.usm.my/42780/1/JES_Vol._11_2015_-_Art._1%281-8%29.pdf
http://eprints.usm.my/42780/
http://web.usm.my/jes/11_2015/JES%20Vol.%2011%202015%20-%20Art.%201(1-8).pdf
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spelling my.usm.eprints.42780 http://eprints.usm.my/42780/ Neural-Wiener-based Model Predictive Control (NWMPC) for Methyl Tert-butyl Ether Catalytic Distillation Sudibyo, Sudibyo Murat , Muhamad Nazri Aziz, Norashid TA1-2040 Engineering (General). Civil engineering (General) The reactive distillation of methyl tert-butyl ether (MTBE) involves strong interactions between variables and is a highly nonlinear process. Here, a nonlinear model predictive control (MPC) was proposed to tackle the nonlinearity and the interaction involved in controlling the tray temperature in MTBE reactive distillation. To improve the performance of the MPC, an advanced nonlinear block-oriented model known as the neural Wiener model was employed. The control study was successfully simulated using Simulink (Matlab), which is integrated with the Aspen dynamic model. Set-point tracking, disturbance rejection and robustness tests were conducted to evaluate the neural-Wiener-based MPC (NWMPC) performance. The results achieved show that the NWMPC is able to maintain the product purity at its set-point of 99%, with isobutene conversion exceeding 99.98%. NWMPC is also able to reject disturbances, as shown in disturbance rejection study performed by changing the feed flowrate to 30% of the nominal value. This controller is also very robust and thus able to control the MTBE reactive distillation, even when the column efficiency was reduced to 80%. Taylor's University 2015 Article PeerReviewed application/pdf en http://eprints.usm.my/42780/1/JES_Vol._11_2015_-_Art._1%281-8%29.pdf Sudibyo, Sudibyo and Murat , Muhamad Nazri and Aziz, Norashid (2015) Neural-Wiener-based Model Predictive Control (NWMPC) for Methyl Tert-butyl Ether Catalytic Distillation. Journal of Engineering Science and Technology, 11. pp. 1-8. ISSN 1823-4690 http://web.usm.my/jes/11_2015/JES%20Vol.%2011%202015%20-%20Art.%201(1-8).pdf
institution Universiti Sains Malaysia
building Hamzah Sendut Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Sains Malaysia
content_source USM Institutional Repository
url_provider http://eprints.usm.my/
language English
topic TA1-2040 Engineering (General). Civil engineering (General)
spellingShingle TA1-2040 Engineering (General). Civil engineering (General)
Sudibyo, Sudibyo
Murat , Muhamad Nazri
Aziz, Norashid
Neural-Wiener-based Model Predictive Control (NWMPC) for Methyl Tert-butyl Ether Catalytic Distillation
description The reactive distillation of methyl tert-butyl ether (MTBE) involves strong interactions between variables and is a highly nonlinear process. Here, a nonlinear model predictive control (MPC) was proposed to tackle the nonlinearity and the interaction involved in controlling the tray temperature in MTBE reactive distillation. To improve the performance of the MPC, an advanced nonlinear block-oriented model known as the neural Wiener model was employed. The control study was successfully simulated using Simulink (Matlab), which is integrated with the Aspen dynamic model. Set-point tracking, disturbance rejection and robustness tests were conducted to evaluate the neural-Wiener-based MPC (NWMPC) performance. The results achieved show that the NWMPC is able to maintain the product purity at its set-point of 99%, with isobutene conversion exceeding 99.98%. NWMPC is also able to reject disturbances, as shown in disturbance rejection study performed by changing the feed flowrate to 30% of the nominal value. This controller is also very robust and thus able to control the MTBE reactive distillation, even when the column efficiency was reduced to 80%.
format Article
author Sudibyo, Sudibyo
Murat , Muhamad Nazri
Aziz, Norashid
author_facet Sudibyo, Sudibyo
Murat , Muhamad Nazri
Aziz, Norashid
author_sort Sudibyo, Sudibyo
title Neural-Wiener-based Model Predictive Control (NWMPC) for Methyl Tert-butyl Ether Catalytic Distillation
title_short Neural-Wiener-based Model Predictive Control (NWMPC) for Methyl Tert-butyl Ether Catalytic Distillation
title_full Neural-Wiener-based Model Predictive Control (NWMPC) for Methyl Tert-butyl Ether Catalytic Distillation
title_fullStr Neural-Wiener-based Model Predictive Control (NWMPC) for Methyl Tert-butyl Ether Catalytic Distillation
title_full_unstemmed Neural-Wiener-based Model Predictive Control (NWMPC) for Methyl Tert-butyl Ether Catalytic Distillation
title_sort neural-wiener-based model predictive control (nwmpc) for methyl tert-butyl ether catalytic distillation
publisher Taylor's University
publishDate 2015
url http://eprints.usm.my/42780/1/JES_Vol._11_2015_-_Art._1%281-8%29.pdf
http://eprints.usm.my/42780/
http://web.usm.my/jes/11_2015/JES%20Vol.%2011%202015%20-%20Art.%201(1-8).pdf
_version_ 1643710573833093120
score 13.211869

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