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Cascade PID controller optimization using bison algorithm

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dc.title Cascade PID controller optimization using bison algorithm en
dc.contributor.author Kazíková, Anežka
dc.contributor.author Łapa, Krystian
dc.contributor.author Pluháček, Michal
dc.contributor.author Šenkeřík, Roman
dc.relation.ispartof Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
dc.identifier.issn 0302-9743 Scopus Sources, Sherpa/RoMEO, JCR
dc.identifier.isbn 978-3-03-061400-3
dc.date.issued 2020
utb.relation.volume 12415 LNAI
dc.citation.spage 406
dc.citation.epage 416
dc.event.title 19th International Conference on Artificial Intelligence and Soft Computing, ICAISC 2020
dc.event.location Zakopane
utb.event.state-en Poland
utb.event.state-cs Polsko
dc.event.sdate 2020-10-12
dc.event.edate 2020-10-14
dc.type conferenceObject
dc.language.iso en
dc.publisher Springer Science and Business Media Deutschland GmbH
dc.identifier.doi 10.1007/978-3-030-61401-0_38
dc.relation.uri https://link.springer.com/chapter/10.1007/978-3-030-61401-0_38
dc.subject cascade PID controllers en
dc.subject meta-heuristics en
dc.subject PID optimization en
dc.description.abstract Meta-heuristic algorithms are reliable tools for modern optimization. Yet their amount is so immense that it is hard to pick just one to solve a specific problem. Therefore many researchers hold on known, approved algorithms. But is it always beneficial? In this paper, we use the meta-heuristics for the design of cascade PID controllers and compare the performance of the newly developed Bison Algorithm with well-known algorithms like the Differential Evolution, the Genetics Algorithm, the Particle Swarm Optimization, and the Cuckoo Search. Also, in the proposed approach, the controller parameters were encoded to increase the chance of reducing the controller structure, and thus facilitate the automatic selection of its configuration. The simulations were performed for three different control problems and checked whether the use of cascade structures could bring significant benefits in comparison to the use of classic PID controllers. © 2020, Springer Nature Switzerland AG. en
utb.faculty Faculty of Applied Informatics
dc.identifier.uri http://hdl.handle.net/10563/1010049
utb.identifier.obdid 43881943
utb.identifier.scopus 2-s2.0-85096527536
utb.source d-scopus
dc.date.accessioned 2020-12-09T01:52:46Z
dc.date.available 2020-12-09T01:52:46Z
utb.ou Department of Informatics and Artificial Intelligence
utb.contributor.internalauthor Kazíková, Anežka
utb.contributor.internalauthor Pluháček, Michal
utb.contributor.internalauthor Šenkeřík, Roman
utb.fulltext.affiliation Anezka Kazikova 1, Krystian Lapa 2, Michal Pluhacek 1, Roman Senkerik 1 1 Department of Informatics and Artificial Intelligence, Tomas Bata University, Zlin, Czech Republic kazikova@utb.cz 2 Department of Computational Intelligence, Czestochowa University of Technology, Czestochowa, Poland krystian.lapa@pcz.pl
utb.fulltext.dates -
utb.fulltext.sponsorship This work was supported by the Internal Grant Agency of Tomas Bata University under the Projects no. IGA/CebiaTech/2020/001. This work is also based upon support by COST (European Cooperation in Science & Technology) under Action CA15140, Improving Applicability of Nature-Inspired Optimisation by Joining Theory and Practice (ImAppNIO). The work was further supported by resources of A.I.Lab at the Faculty of Applied Informatics, Tomas Bata University in Zlin (ailab.fai.utb.cz).
utb.scopus.affiliation Department of Informatics and Artificial Intelligence, Tomas Bata University, Zlin, Czech Republic; Department of Computational Intelligence, Czestochowa University of Technology, Czestochowa, Poland
utb.fulltext.projects IGA/CebiaTech/2020/001
utb.fulltext.projects CA15140
utb.fulltext.projects ImAppNIO
utb.fulltext.faculty Faculty of Applied Informatics
utb.fulltext.faculty Faculty of Applied Informatics
utb.fulltext.faculty Faculty of Applied Informatics
utb.fulltext.ou Department of Informatics and Artificial Intelligence
utb.fulltext.ou Department of Informatics and Artificial Intelligence
utb.fulltext.ou Department of Informatics and Artificial Intelligence
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