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  Efficient and Simple Gaussian Process Supported Stochastic Model Predictive Control for Bioreactors using HILO-MPC

Morabito, B., Pohlodek, J., Kranert, L., Espinel-Rios, S., & Findeisen, R. (2022). Efficient and Simple Gaussian Process Supported Stochastic Model Predictive Control for Bioreactors using HILO-MPC. In IFAC-PapersOnLine (pp. 922-927).

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Item Permalink: https://hdl.handle.net/21.11116/0000-000B-226F-3 Version Permalink: https://hdl.handle.net/21.11116/0000-000B-2270-0
Genre: Conference Paper

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espinel_rios_3424023.pdf (Publisher version), 477KB
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https://hdl.handle.net/21.11116/0000-000B-2271-F
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espinel_rios_3424023.pdf
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Copyright © 2022 The Authors. This is an open access article under the CC BY-NC-ND license.
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 Creators:
Morabito, Bruno1, Author
Pohlodek, Johannes1, Author
Kranert, Lena1, Author
Espinel-Rios, Sebastian1, 2, Author           
Findeisen, Rolf3, Author
Affiliations:
1Otto-von-Guericke-Universität Magdeburg, External Organizations, ou_1738156              
2Analysis and Redesign of Biological Networks, Max Planck Institute for Dynamics of Complex Technical Systems, Max Planck Society, ou_1738139              
3Control and Cyber-Physical Systems Laboratory, TU Darmstadt, Germany, ou_persistent22              

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Language(s): eng - English
 Dates: 2022
 Publication Status: Issued
 Pages: -
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 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1016/j.ifacol.2022.07.562
 Degree: -

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Title: 13th IFAC Symposium on Dynamics and Control of Process Systems, including Biosystems, DYCOPS 2022
Place of Event: Busan, Korea
Start-/End Date: 2022-06-14 - 2022-06-17

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Title: IFAC-PapersOnLine
Source Genre: Proceedings
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Pages: - Volume / Issue: 55 (7) Sequence Number: - Start / End Page: 922 - 927 Identifier: -