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  Constrained Gaussian Process Learning for Model Predictive Control

Matschek, J., Himmel, A., Sundmacher, K., & Findeisen, R. (2020). Constrained Gaussian Process Learning for Model Predictive Control. IFAC-PapersOnLine, 53(2), 971-976.

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Genre: Conference Paper

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matschek_3316872.pdf (Publisher version), 468KB
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2020 The Authors. This is an open access article under the CC BY-NC-ND license.

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 Creators:
Matschek, Janine1, Author
Himmel, Andreas2, 3, Author              
Sundmacher, Kai3, 4, Author              
Findeisen, Rolf1, Author
Affiliations:
1Laboratory for Systems Theory and Automatic Control, Otto von Guericke University Magdeburg, Germany, ou_persistent22              
2International Max Planck Research School (IMPRS), Max Planck Institute for Dynamics of Complex Technical Systems, Max Planck Society, ou_1738143              
3Otto-von-Guericke-Universität Magdeburg, External Organizations, ou_1738156              
4Process Systems Engineering, Max Planck Institute for Dynamics of Complex Technical Systems, Max Planck Society, ou_1738151              

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Language(s): eng - English
 Dates: 2020
 Publication Status: Published in print
 Pages: -
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 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1016/j.ifacol.2020.12.1269
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Title: 21th IFAC World Congress
Place of Event: Virtual
Start-/End Date: 2020-07-11 - 2020-07-17

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Title: IFAC-PapersOnLine
Source Genre: Journal
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Pages: - Volume / Issue: 53 (2) Sequence Number: - Start / End Page: 971 - 976 Identifier: ISSN: 24058963