Nonlinear Model Predictive Control of a Distillation Column Using Wavenet Based Hammerstein Model

Nonlinear Model Predictive Control of a Distillation Column Using Wavenet Based Hammerstein Model

Distillation columns are fairly complex multivariable systems and needs to be controlled close to optimum operating conditions because of economic incentives. Nonlinear Model Predictive Control (NMPC) scheme is one of the best options to be explored for proper control of distillation columns. In th...

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Main Authors: K., Ramesh, Anwaruddin, Hisyam, N., Aziz, S. R., Abd Shukor
Format: Article
Language:English
English
Published: International Association of Engineers 2012
Subjects:
QD Chemistry
Online Access:http://umpir.ump.edu.my/id/eprint/6772/
http://umpir.ump.edu.my/id/eprint/6772/
http://umpir.ump.edu.my/id/eprint/6772/1/Nonlinear_model_predictive_control.pdf
http://umpir.ump.edu.my/id/eprint/6772/3/fkksa-2012-ramesh-Nonlinear%20Model%20Predictive%20Control%20of%20a%20Distillation.pdf
id ump-6772
recordtype eprints
spelling ump-67722018-01-11T01:04:07Z http://umpir.ump.edu.my/id/eprint/6772/ Nonlinear Model Predictive Control of a Distillation Column Using Wavenet Based Hammerstein Model K., Ramesh Anwaruddin, Hisyam N., Aziz S. R., Abd Shukor QD Chemistry Distillation columns are fairly complex multivariable systems and needs to be controlled close to optimum operating conditions because of economic incentives. Nonlinear Model Predictive Control (NMPC) scheme is one of the best options to be explored for proper control of distillation columns. In the present work, a new wavenet based Hammerstein model NMPC has been developed to control distillation column. An experimentally validated equilibrium model was used as plant model in nonlinear system identification and in NMPC. Two multiple-input-single-output (MISO) wavenet based Hammerstein models are developed to model the dynamics of the distillation column. The nonlinear model parameters were estimated using iterative prediction error minimization method. The Unscented Kalman Filter (UKF) was used to estimate the state variables in NMPC and the NLP problem was solved using sequential quadratic programming (SQP) method. The closed loop control studies have indicated that the performance of developed NMPC scheme was good in controlling the distillation column International Association of Engineers 2012 Article PeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/6772/1/Nonlinear_model_predictive_control.pdf application/pdf en http://umpir.ump.edu.my/id/eprint/6772/3/fkksa-2012-ramesh-Nonlinear%20Model%20Predictive%20Control%20of%20a%20Distillation.pdf K., Ramesh and Anwaruddin, Hisyam and N., Aziz and S. R., Abd Shukor (2012) Nonlinear Model Predictive Control of a Distillation Column Using Wavenet Based Hammerstein Model. Engineering Letters, 20 (4). pp. 1-6. ISSN 1816-093X (Print); 1816-0948 (Online) http://www.engineeringletters.com/issues_v20/issue_4/EL_20_4_04.pdf
repository_type Digital Repository
institution_category Local University
institution Universiti Malaysia Pahang
building UMP Institutional Repository
collection Online Access
language English
English
topic QD Chemistry
spellingShingle QD Chemistry
K., Ramesh
Anwaruddin, Hisyam
N., Aziz
S. R., Abd Shukor
Nonlinear Model Predictive Control of a Distillation Column Using Wavenet Based Hammerstein Model
description Distillation columns are fairly complex multivariable systems and needs to be controlled close to optimum operating conditions because of economic incentives. Nonlinear Model Predictive Control (NMPC) scheme is one of the best options to be explored for proper control of distillation columns. In the present work, a new wavenet based Hammerstein model NMPC has been developed to control distillation column. An experimentally validated equilibrium model was used as plant model in nonlinear system identification and in NMPC. Two multiple-input-single-output (MISO) wavenet based Hammerstein models are developed to model the dynamics of the distillation column. The nonlinear model parameters were estimated using iterative prediction error minimization method. The Unscented Kalman Filter (UKF) was used to estimate the state variables in NMPC and the NLP problem was solved using sequential quadratic programming (SQP) method. The closed loop control studies have indicated that the performance of developed NMPC scheme was good in controlling the distillation column
format Article
author K., Ramesh
Anwaruddin, Hisyam
N., Aziz
S. R., Abd Shukor
author_facet K., Ramesh
Anwaruddin, Hisyam
N., Aziz
S. R., Abd Shukor
author_sort K., Ramesh
title Nonlinear Model Predictive Control of a Distillation Column Using Wavenet Based Hammerstein Model
title_short Nonlinear Model Predictive Control of a Distillation Column Using Wavenet Based Hammerstein Model
title_full Nonlinear Model Predictive Control of a Distillation Column Using Wavenet Based Hammerstein Model
title_fullStr Nonlinear Model Predictive Control of a Distillation Column Using Wavenet Based Hammerstein Model
title_full_unstemmed Nonlinear Model Predictive Control of a Distillation Column Using Wavenet Based Hammerstein Model
title_sort nonlinear model predictive control of a distillation column using wavenet based hammerstein model
publisher International Association of Engineers
publishDate 2012
url http://umpir.ump.edu.my/id/eprint/6772/
http://umpir.ump.edu.my/id/eprint/6772/
http://umpir.ump.edu.my/id/eprint/6772/1/Nonlinear_model_predictive_control.pdf
http://umpir.ump.edu.my/id/eprint/6772/3/fkksa-2012-ramesh-Nonlinear%20Model%20Predictive%20Control%20of%20a%20Distillation.pdf
first_indexed 2023-09-18T22:02:50Z
last_indexed 2023-09-18T22:02:50Z
_version_ 1777414512815636480

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