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Effective parametric optimization of heating-cooling process with optimum near the domain border

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dc.title Effective parametric optimization of heating-cooling process with optimum near the domain border en
dc.contributor.author Guzowski, Hubert
dc.contributor.author Smołka, Maciej
dc.contributor.author Byrski, Aleksander
dc.contributor.author Pekař, Libor
dc.contributor.author Komínková Oplatková, Zuzana
dc.contributor.author Šenkeřík, Roman
dc.contributor.author Matušů, Radek
dc.contributor.author Gazdoš, František
dc.relation.ispartof 2022 IEEE 11th International Conference on Intelligent Systems, IS 2022
dc.identifier.isbn 978-1-6654-5656-2
dc.date.issued 2022
dc.event.title 11th IEEE International Conference on Intelligent Systems, IS 2022
dc.event.location Warsaw
utb.event.state-en Poland
utb.event.state-cs Polsko
dc.event.sdate 2022-10-12
dc.event.edate 2022-10-14
dc.type conferenceObject
dc.language.iso en
dc.publisher Institute of Electrical and Electronics Engineers Inc.
dc.identifier.doi 10.1109/IS57118.2022.10019630
dc.relation.uri https://ieeexplore.ieee.org/document/10019630
dc.relation.uri https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10019630
dc.subject metaheuristics en
dc.subject parametric optimization en
dc.subject time-delay systems en
dc.description.abstract Heating-cooling processes are widely used in industry and are often subject to latencies and delays. Although the parameters of such processes can be identified using mathematical and physical modeling, this technique is highly demanding both when it comes to the amount of a priori knowledge required and the time it takes to find a solution. In this work, we provide a robust formulation of a time-delay control problem and propose a numerical approach to finding its parameters in a form of an optimization task. Consequently, we apply various techniques and metaheuristics to obtain a high quality solution and discuss key observations made in the process. © 2022 IEEE. en
utb.faculty Faculty of Applied Informatics
dc.identifier.uri http://hdl.handle.net/10563/1011416
utb.identifier.obdid 43884297
utb.identifier.scopus 2-s2.0-85147711824
utb.source d-scopus
dc.date.accessioned 2023-02-25T13:54:26Z
dc.date.available 2023-02-25T13:54:26Z
dc.description.sponsorship 978-1-6654-5656-2/22; Grantová Agentura České Republiky, GA ČR: GF21-45465L; Narodowe Centrum Nauki, NCN: /35/O/ST6/00570, 2020/39/I/ST7/02285; Ministerstwo Edukacji i Nauki, MNiSW
dc.format.extent 6
utb.contributor.internalauthor Pekař, Libor
utb.contributor.internalauthor Komínková Oplatková, Zuzana
utb.contributor.internalauthor Šenkeřík, Roman
utb.contributor.internalauthor Matušů, Radek
utb.contributor.internalauthor Gazdoš, František
utb.fulltext.sponsorship The research presented in this paper was partially supported by: NCN project no: 2020/39/I/ST7/02285, NCN project: no: 2019/35/O/ST6/00570, Polish Ministry of Education and Science funds assigned to AGH University of Science and Technology. It was also supported by Czech Science Foundation (GACR) project no: GF21-45465L and resources of A.I.Lab at the Faculty of Applied Informatics, Tomas Bata University in Zlin (ailab.fai.utb.cz).
utb.scopus.affiliation Agh University of Science and Technology, Institute of Computer Science, Krakow, Poland; Tomas Bata University in Zlín, Faculty of Applied Informatics, Czech Republic
utb.fulltext.projects 2020/39/I/ST7/02285
utb.fulltext.projects 2019/35/O/ST6/00570
utb.fulltext.projects GF21-45465L
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