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On the way to autonomous model predictive control: A distillation column simulation study
KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
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2013 (English)In: 10th IFAC Symposium on Dynamics and Control of Process Systems, DYCOPS 2013, IFAC Secretariat , 2013, no PART 1, 713-720 p.Conference paper, Published paper (Refereed)
Abstract [en]

Model Predictive Control (MPC) is a powerful tool in the control of large scale chemical processes and has become the standard method for constrained multivariable control problems. Hence, the number of MPC applications is increasing steadily and it is being used in application domains other than petrochemical industries. A common observation by the industrial practitioners is that success of any MPC application requires not only efficient initial deployment but also maintenance of initial effectiveness. To this end, we propose a novel high level automated support strategy for MPC systems. Such a strategy consists of components such as performance monitoring, performance diagnosis, least costly closed loop experiment design, re-identification and autotuning. This work presents the novel technological developments in each component and demonstrates them on a distillation column case study. We show that automated support strategy restores nominal performance after a performance drop is detected and takes the right course of action depending on its cause.

Place, publisher, year, edition, pages
IFAC Secretariat , 2013. no PART 1, 713-720 p.
Series
IFAC Proceedings Volumes (IFAC-PapersOnline), ISSN 1474-6670 ; Volume 10, Issue Part 1
Keyword [en]
Distillation columns, Model predictive control, Closed-loop experiments, Industrial practitioners, Initial deployments, Multivariable control, Performance diagnosis, Performance monitoring, Petrochemical industry, Technological development, Predictive control systems
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:kth:diva-147288DOI: 10.3182/20131218-3-IN-2045.00057Scopus ID: 2-s2.0-84896345936OAI: oai:DiVA.org:kth-147288DiVA: diva2:730068
Conference
10th IFAC Symposium on Dynamics and Control of Process Systems, DYCOPS 2013; Mumbai; India; 18 December 2013 through 20 December 2013
Note

QC 20140627

Available from: 2014-06-27 Created: 2014-06-25 Last updated: 2014-06-27Bibliographically approved

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CiteExportLink to record
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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
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  • Other locale
More languages
Output format
  • html
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  • asciidoc
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