Autonomous maintenance of advanced process control: application to an industrial depropanizer

H. Guidi, C.A. Larsson, Q.N. Tran, L. Ozkan, A.C.P.M. Backx

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdrageAcademicpeer review

1 Citaat (Scopus)

Uittreksel

Although Model Predictive Control (MPC) has been widely accepted as a main technology for Advanced Process Control (APC) due to its ability of operating the system closely to the constraints, proper maintenance of MPC systems is still a challenge. Based on this observation, this research aims to develop an automated support strategy for the autonomous maintenance of MPC. In this work, re-tuning and re-identification components of the automated support strategy are considered as corrective action to retain the performance of the system after a change in the plant dynamics causes performance degradation. An industrial FT-depropanizer is used to test the implementation of these components. Results successfully show that an automated unified framework approach to MPC maintenance can successfully be used in further securing the economic leverage of MPC in industry.

TaalEngels
TitelFuels and Petrochemicals Division 2014 - Core Programming Area at the 2014 AIChE Spring Meeting and 10th Global Congress on Process Safety
UitgeverijAmerican Institute of Chemical Engineers (AIChE)
Pagina's923-932
Aantal pagina's10
Volume2
ISBN van elektronische versie9781634390736
StatusGepubliceerd - 1 jan 2014
EvenementFuels and Petrochemicals Division 2014 - Core Programming Area at the 2014 AIChE Spring Meeting and 10th Global Congress on Process Safety - New Orleans, Verenigde Staten van Amerika
Duur: 30 mrt 20143 apr 2014

Congres

CongresFuels and Petrochemicals Division 2014 - Core Programming Area at the 2014 AIChE Spring Meeting and 10th Global Congress on Process Safety
LandVerenigde Staten van Amerika
StadNew Orleans
Periode30/03/143/04/14

Vingerafdruk

Model predictive control
Process control
Predictive control systems
Tuning
Degradation
Economics
Industry

Citeer dit

Guidi, H., Larsson, C. A., Tran, Q. N., Ozkan, L., & Backx, A. C. P. M. (2014). Autonomous maintenance of advanced process control: application to an industrial depropanizer. In Fuels and Petrochemicals Division 2014 - Core Programming Area at the 2014 AIChE Spring Meeting and 10th Global Congress on Process Safety (Vol. 2, blz. 923-932). American Institute of Chemical Engineers (AIChE).
Guidi, H. ; Larsson, C.A. ; Tran, Q.N. ; Ozkan, L. ; Backx, A.C.P.M./ Autonomous maintenance of advanced process control : application to an industrial depropanizer. Fuels and Petrochemicals Division 2014 - Core Programming Area at the 2014 AIChE Spring Meeting and 10th Global Congress on Process Safety. Vol. 2 American Institute of Chemical Engineers (AIChE), 2014. blz. 923-932
@inproceedings{422aeffd49b441d1aa7c18296eba24c5,
title = "Autonomous maintenance of advanced process control: application to an industrial depropanizer",
abstract = "Although Model Predictive Control (MPC) has been widely accepted as a main technology for Advanced Process Control (APC) due to its ability of operating the system closely to the constraints, proper maintenance of MPC systems is still a challenge. Based on this observation, this research aims to develop an automated support strategy for the autonomous maintenance of MPC. In this work, re-tuning and re-identification components of the automated support strategy are considered as corrective action to retain the performance of the system after a change in the plant dynamics causes performance degradation. An industrial FT-depropanizer is used to test the implementation of these components. Results successfully show that an automated unified framework approach to MPC maintenance can successfully be used in further securing the economic leverage of MPC in industry.",
author = "H. Guidi and C.A. Larsson and Q.N. Tran and L. Ozkan and A.C.P.M. Backx",
year = "2014",
month = "1",
day = "1",
language = "English",
volume = "2",
pages = "923--932",
booktitle = "Fuels and Petrochemicals Division 2014 - Core Programming Area at the 2014 AIChE Spring Meeting and 10th Global Congress on Process Safety",
publisher = "American Institute of Chemical Engineers (AIChE)",
address = "United States",

}

Guidi, H, Larsson, CA, Tran, QN, Ozkan, L & Backx, ACPM 2014, Autonomous maintenance of advanced process control: application to an industrial depropanizer. in Fuels and Petrochemicals Division 2014 - Core Programming Area at the 2014 AIChE Spring Meeting and 10th Global Congress on Process Safety. vol. 2, American Institute of Chemical Engineers (AIChE), blz. 923-932, New Orleans, Verenigde Staten van Amerika, 30/03/14.

Autonomous maintenance of advanced process control : application to an industrial depropanizer. / Guidi, H.; Larsson, C.A.; Tran, Q.N.; Ozkan, L.; Backx, A.C.P.M.

Fuels and Petrochemicals Division 2014 - Core Programming Area at the 2014 AIChE Spring Meeting and 10th Global Congress on Process Safety. Vol. 2 American Institute of Chemical Engineers (AIChE), 2014. blz. 923-932.

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdrageAcademicpeer review

TY - GEN

T1 - Autonomous maintenance of advanced process control

T2 - application to an industrial depropanizer

AU - Guidi,H.

AU - Larsson,C.A.

AU - Tran,Q.N.

AU - Ozkan,L.

AU - Backx,A.C.P.M.

PY - 2014/1/1

Y1 - 2014/1/1

N2 - Although Model Predictive Control (MPC) has been widely accepted as a main technology for Advanced Process Control (APC) due to its ability of operating the system closely to the constraints, proper maintenance of MPC systems is still a challenge. Based on this observation, this research aims to develop an automated support strategy for the autonomous maintenance of MPC. In this work, re-tuning and re-identification components of the automated support strategy are considered as corrective action to retain the performance of the system after a change in the plant dynamics causes performance degradation. An industrial FT-depropanizer is used to test the implementation of these components. Results successfully show that an automated unified framework approach to MPC maintenance can successfully be used in further securing the economic leverage of MPC in industry.

AB - Although Model Predictive Control (MPC) has been widely accepted as a main technology for Advanced Process Control (APC) due to its ability of operating the system closely to the constraints, proper maintenance of MPC systems is still a challenge. Based on this observation, this research aims to develop an automated support strategy for the autonomous maintenance of MPC. In this work, re-tuning and re-identification components of the automated support strategy are considered as corrective action to retain the performance of the system after a change in the plant dynamics causes performance degradation. An industrial FT-depropanizer is used to test the implementation of these components. Results successfully show that an automated unified framework approach to MPC maintenance can successfully be used in further securing the economic leverage of MPC in industry.

UR - http://www.scopus.com/inward/record.url?scp=84912124826&partnerID=8YFLogxK

M3 - Conference contribution

VL - 2

SP - 923

EP - 932

BT - Fuels and Petrochemicals Division 2014 - Core Programming Area at the 2014 AIChE Spring Meeting and 10th Global Congress on Process Safety

PB - American Institute of Chemical Engineers (AIChE)

ER -

Guidi H, Larsson CA, Tran QN, Ozkan L, Backx ACPM. Autonomous maintenance of advanced process control: application to an industrial depropanizer. In Fuels and Petrochemicals Division 2014 - Core Programming Area at the 2014 AIChE Spring Meeting and 10th Global Congress on Process Safety. Vol. 2. American Institute of Chemical Engineers (AIChE). 2014. blz. 923-932.