Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Autonomous maintenance of advanced process control: Application to an industrial depropanizer
KTH, School of Electrical Engineering (EES), Automatic Control.
Show others and affiliations
2014 (English)In: Fuels and Petrochemicals Division 2014 - Core Programming Area at the 2014 AIChE Spring Meeting and 10th Global Congress on Process Safety, AIChE , 2014, Vol. 2, 923-932 p.Conference paper, Published paper (Refereed)
Abstract [en]

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.

Place, publisher, year, edition, pages
AIChE , 2014. Vol. 2, 923-932 p.
Keyword [en]
Automation, Intelligent control, Maintenance, Predictive control systems, Advanced Process Control, Automated support, Corrective actions, Performance degradation, Plant dynamics, Re identifications, Re-tuning, Unified framework, Model predictive control
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:kth:diva-168126Scopus ID: 2-s2.0-84912124826ISBN: 978-163439073-6 (print)OAI: oai:DiVA.org:kth-168126DiVA: diva2:815676
Conference
Fuels and Petrochemicals Division 2014 - Core Programming Area at the 2014 AIChE Spring Meeting and 10th Global Congress on Process Safety, New Orleans, United States, 30 March 2014 through 3 April 2014
Note

QC 20150601

Available from: 2015-06-01 Created: 2015-05-27 Last updated: 2017-01-13Bibliographically approved

Open Access in DiVA

No full text

Scopus

Search in DiVA

By author/editor
Larsson, Christian
By organisation
Automatic Control
Electrical Engineering, Electronic Engineering, Information Engineering

Search outside of DiVA

GoogleGoogle Scholar

isbn
urn-nbn

Altmetric score

isbn
urn-nbn
Total: 271 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf