Systematic Methodology for Reproducible Optimizing Batch Operation

Dennis Bonné, Sten Bay Jørgensen

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Abstract

This contribution presents a systematic methodology for rapid acquirement of discrete-time state space model representations of batch processes based on their historical operation data. These state space models are parsimoniously parameterized as a set of local, interdependent models. The present contribution furthermore presents how the asymptotic convergence of Iterative Learning Control is combined with the closed-loop performance of Model Predictive Control to form a robust and asymptotically stable optimal controller for ensuring reliable and reproducible operation of batch processes. This controller may also be used for Optimizing control. The modeling and control performance is demonstrated on a fed-batch protein cultivation example. The presented methodologies lend themselves directly for application as Process Analytical Technologies (PAT).
Original languageEnglish
Title of host publication16th European Symposium on Computer Aided Process Engineering and 9th Symposium on Process Systems Engineering
Publication date2006
Pages1275-1280
ISBN (Print)978-0-444-52969-5
Publication statusPublished - 2006
Event16th European Symposium on Computer Aided Process Engineering and 9th International Symposium on Process Systems Engineering: Joint Conference Event - Garmisch-Partenkirchen, Germany
Duration: 9 Jul 200613 Jul 2006
Conference number: 16 and 9

Conference

Conference16th European Symposium on Computer Aided Process Engineering and 9th International Symposium on Process Systems Engineering
Number16 and 9
CountryGermany
CityGarmisch-Partenkirchen
Period09/07/200613/07/2006
SeriesComputer Aided Chemical Engineering
Volume21B
ISSN1570-7946

Fingerprint Dive into the research topics of 'Systematic Methodology for Reproducible Optimizing Batch Operation'. Together they form a unique fingerprint.

Cite this