Wartungsarbeiten: Am 16.01.2025 von ca. 8:00 bis 11:00 Uhr steht Ihnen das System nicht zur Verfügung. Bitte stellen Sie sich entsprechend darauf ein.
 

Control of an industrial distillation column using a hybrid model with adaptation of the range of validity and an ANN-based soft sensor

Simple item page
dc.contributor.authorElsheikh, Mohamed
dc.contributor.authorOrtmanns, Yak
dc.contributor.authorHecht, Felix
dc.contributor.authorRoßmann, Volker
dc.contributor.authorKrämer, Stefan
dc.contributor.authorEngell, Sebastian
dc.date.accessioned2025-01-15T13:05:36Z
dc.date.available2025-01-15T13:05:36Z
dc.date.issued2023-05-16
dc.description.abstractAdvanced control schemes such as model predictive control can be used to minimize the use of resources while guaranteeing the specified product quality. In this paper, we consider an industrial mother liquor distillation column varying flow rate and composition of the feed. There are specifications of the composition for all product streams. To address this challenging control problem, we employ a nonlinear model-predictive controller using a hybrid model, which consists of a simple phenomenological model augmented by a data-based component to compensate the plant-model mismatch. The trustworthiness of the data-based model is addressed using a domain of validity of the data-based model, which is estimated using a one-class support vector machine. During operation, it may turn out that the model is also reliable in a wider range, therefore, data of recently visited operating points is recorded and the domain of validity is extended if the model is sufficiently accurate. To improve the performance of the controller, an artificial neural network model is used to estimate the product composition from available measurements.en
dc.identifier.urihttp://hdl.handle.net/2003/43363
dc.identifier.urihttp://dx.doi.org/10.17877/DE290R-25195
dc.language.isoen
dc.relation.ispartofseriesChemie - Ingenieur - Technik; 95(7)
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectDistillation columnsen
dc.subjectDomain of validityen
dc.subjectHybrid modelingen
dc.subjectModel predictive controlen
dc.subjectNeural networksen
dc.subjectSoft sensingen
dc.subject.ddc660
dc.titleControl of an industrial distillation column using a hybrid model with adaptation of the range of validity and an ANN-based soft sensoren
dc.typeText
dc.type.publicationtypeResearchArticle
dcterms.accessRightsopen access
eldorado.secondarypublicationtrue
eldorado.secondarypublication.primarycitationElsheikh, M., Ortmanns, Y., Hecht, F., Roßmann, V., Krämer, S. and Engell, S. (2023), Control of an Industrial Distillation Column Using a Hybrid Model with Adaptation of the Range of Validity and an ANN-based Soft Sensor. Chemie Ingenieur Technik, 95: 1114-1124. https://doi.org/10.1002/cite.202200232
eldorado.secondarypublication.primaryidentifierhttps://doi.org/10.1002/cite.202200232

Files

Original bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
Chemie Ingenieur Technik - 2023 - Elsheikh - Control of an Industrial Distillation Column Using a Hybrid Model with.pdf
Size:
1.09 MB
Format:
Adobe Portable Document Format
Description:
DNB
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
4.82 KB
Format:
Item-specific license agreed upon to submission
Description:
Download

Collections

Lehrstuhl Systemdynamik und Prozessfuehrung