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Comparison of stabilization with P/I-delayed controllers for second-order systems using built-in MATLAB heuristic optimization methods

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dc.title Comparison of stabilization with P/I-delayed controllers for second-order systems using built-in MATLAB heuristic optimization methods en
dc.contributor.author Strmiska, Martin
dc.contributor.author Araújo, José Mário
dc.contributor.author Pekař, Libor
dc.relation.ispartof Lecture Notes in Networks and Systems
dc.identifier.issn 2367-3370 Scopus Sources, Sherpa/RoMEO, JCR
dc.identifier.isbn 978-3-031-21434-9
dc.date.issued 2023
utb.relation.volume 596 LNNS
dc.citation.spage 652
dc.citation.epage 662
dc.event.title 6th Computational Methods in Systems and Software, CoMeSySo 2022
dc.event.location online
dc.event.sdate 2022-10-10
dc.event.edate 2022-10-15
dc.type conferenceObject
dc.language.iso en
dc.publisher Springer Science and Business Media Deutschland GmbH
dc.identifier.doi 10.1007/978-3-031-21435-6_55
dc.relation.uri https://link.springer.com/chapter/10.1007/978-3-031-21435-6_55
dc.subject heuristic optimalization en
dc.subject second-order systems en
dc.subject stabilization en
dc.description.abstract In control theory, optimization is a process that makes some system behavior as likelihood, functional, or practical as possible (depending on the design requirements). From a mathematical point of view, optimization is a way to find the minimum or maximum of the mathematical function by which the system is described. Moreover, if there is a time delay in the feedback loops inside a controlled system, the system has an infinite spectrum – infinitely many roots (poles); this degrades the control's quality, especially in terms of stability, robustness, and oscillation response. For these reasons, it is necessary to optimize the system transient response. This paper will compare selected heuristic methods of optimization of linear-time invariant (LTI) systems with time delay in an integral part of the P/I-delayed controller. Some examples are chosen as benchmarks to verify the effectiveness of the optimization. In future research, we would like to focus on implementing selected modern optimization algorithms for solving non-smooth, non-convex, and non-Lipschitz optimization problems. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG. en
utb.faculty Faculty of Applied Informatics
dc.identifier.uri http://hdl.handle.net/10563/1011431
utb.identifier.obdid 43884035
utb.identifier.scopus 2-s2.0-85148019819
utb.source d-scopus
dc.date.accessioned 2023-03-15T07:46:34Z
dc.date.available 2023-03-15T07:46:34Z
dc.description.sponsorship IGA/FAI/2022/008
utb.contributor.internalauthor Strmiska, Martin
utb.contributor.internalauthor Pekař, Libor
utb.fulltext.sponsorship The paper was supported by the Internal Grant Agency of Tomas Bata University in Zlín under the project number IGA/FAI/2022/008.
utb.scopus.affiliation Tomas Bata University, Zlín, Czech Republic; Federal Institute of Bahia, Salvador, Brazil
utb.fulltext.projects IGA/FAI/2022/008
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