University of Oulu

Pulkkinen, Jari; Louis, Jean-Nicolas (2020) Impacts of demand side management programs to domestic hot water heating load profiles in smart buildings. In : In E. Juuso, B. Lie, E. Dahlquist & J. Ruuska (Eds.), Proceedings of The 61st SIMS Conference on Simulation and Modelling SIMS 2020, Virtual Conference, Finland, 22-24 September 2020. Linköping electronic conference proceedings, 176, 1-8.

Adaptation framework for an industrial digital twin

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Author: Koistinen, Antti1; Ohenoja, Markku1; Tomperi, Jani1;
Organizations: 1Control Engineering, Environmental and Chemical Engineering Research Unit, University of Oulu, Finland
Format: article
Version: published version
Access: open
Online Access: PDF Full Text (PDF, 0.4 MB)
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Language: English
Published: Linköping University Electronic Press, 2020
Publish Date: 2021-12-01


Digital twins for performance-oriented applications in industrial environments require systematic model maintenance. Model adaptation requires efficient optimization tools and continuous evaluation of measurement quality. The adaptation and model performance evaluation are based on the modeling error, making the adaptation prone also to the measurement errors. In this paper, a framework for combining model adaptation and measurement quality assurance are discussed. Two examples with simulated industrialscale biopharmaceutical penicillin fermentation are presented to illustrate the usability of the framework.

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Series: Linköping electronic conference proceedings
ISSN: 1650-3686
ISSN-E: 1650-3740
ISSN-L: 1650-3686
ISBN: 978-91-7929-731-2
Volume: 176
Pages: 1 - 8
DOI: 10.3384/ecp20176365
Host publication: Proceedings of The 61st SIMS Conference on Simulation and Modelling SIMS 2020, September 22-24, Virtual Conference, Finland
Type of Publication: A4 Article in conference proceedings
Field of Science: 113 Computer and information sciences
213 Electronic, automation and communications engineering, electronics
215 Chemical engineering
Funding: This work belongs to project ‘Autonomous Processes Facilitated by Artificial Sensing Intelligence (APASSI)’, funded by Business Finland.
Copyright information: © 2020 The authors. Creative Commons Attribution 4.0 (CC-BY) licence.