Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • 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
Fast Estimation of Plant Steady State for Imperfectly Known Dynamic Systems, with Application to Real-Time Optimization
Laboratoire d'Automatique, Ecole Polytechnique Fédérale de Lausanne, Lausanne, 1015, Switzerland.
2018 (English)In: Industrial & Engineering Chemistry Research, ISSN 0888-5885, E-ISSN 1520-5045, Vol. 57, no 10, p. 3699-3716Article in journal (Refereed) Published
Abstract [en]

Experimental assessment or prediction of plant steady state is important for many applications in the area of modeling and operation of continuous processes. For example, the iterative implementation of static real-time optimization requires reaching steady state for each successive operating point, which may be quite time-consuming. This paper presents an approach to speed up the estimation of plant steady state for imperfectly known dynamic systems that are characterized by (i) the presence of fast and slow states, with no effect of the slow states on the fast states, and (ii) the fact that the unknown part of the dynamics depends only on the fast states. The proposed approach takes advantage of measurement-based rate estimation, which consists in estimating rate signals without the knowledge or identification of rate models. Since one can use feedback control to speed up the convergence to steady state of the fast part of the plant, this rate estimation allows estimating the steady state of the slow part during transient operation. It is shown how this approach can be used to speed up the static real-time optimization of continuous processes. A simulated example illustrates its application to a continuous stirred-tank reactor.

Place, publisher, year, edition, pages
American Chemical Society (ACS), 2018. Vol. 57, no 10, p. 3699-3716
National Category
Control Engineering Chemical Process Engineering
Identifiers
URN: urn:nbn:se:kth:diva-248581DOI: 10.1021/acs.iecr.7b04631ISI: 000427910300025Scopus ID: 2-s2.0-85043984656OAI: oai:DiVA.org:kth-248581DiVA, id: diva2:1303430
Note

QC 20190618

Available from: 2019-04-09 Created: 2019-04-09 Last updated: 2019-06-18Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus

Search in DiVA

By author/editor
Rodrigues, Diogo
In the same journal
Industrial & Engineering Chemistry Research
Control EngineeringChemical Process Engineering

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 2 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • 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