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Testing hypotheses used in analysis of control quality

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dc.title Testing hypotheses used in analysis of control quality en
dc.contributor.author Kubalčík, Marek
dc.contributor.author Barot, Tomáš
dc.relation.ispartof Proceedings of the 33rd International ECMS Conference on Modelling and Simulation (ECMS 2019)
dc.identifier.issn 2522-2414 Scopus Sources, Sherpa/RoMEO, JCR
dc.date.issued 2019
utb.relation.volume 33
utb.relation.issue 1
dc.citation.spage 132
dc.citation.epage 137
dc.event.title 33rd International ECMS Conference on Modelling and Simulation, ECMS 2019
dc.event.location Napoli
utb.event.state-en Italy
utb.event.state-cs Itálie
dc.event.sdate 2019-06-11
dc.event.edate 2019-06-14
dc.type conferenceObject
dc.language.iso en
dc.publisher European Council for Modelling and Simulation
dc.identifier.doi 10.7148/2019-0132
dc.relation.uri http://www.scs-europe.net/dlib/2019/2019-0132.htm
dc.relation.uri http://www.scs-europe.net/dlib/2019/ecms2019acceptedpapers/0132_mct_ecms2019_0012.pdf
dc.subject Simulation en
dc.subject Control Quality Criterions en
dc.subject Multivariable Model Predictive Control en
dc.subject Optimization en
dc.subject Testing Hypothesis en
dc.description.abstract Simulation is an important tool for testing and verification of newly designed or modified control algorithms. One of the aims of the simulation verification is a comparison of control quality achieved with new or modified methods with control quality achieved with known methods. For an analysis of control quality, criterions based namely on sum of powers of control errors and sum of powers of control increments are commonly used. These criterions can result only in descriptive attributes of control quality. It means that on the basis of particular values of the criterions it is not possible to identify if the control quality achieved with one algorithm is statistically significantly different from control quality achieved with another algorithm. The aim of this paper is examining of control quality with use of testing hypotheses on existence of statistically significant differences between partial values of the control quality criterions in individual sampling periods. The analysis was performed on a strictly defined significance level 0.001, which is a standardly used value in technical applications. A realization is presented on a simulation of a multivariable predictive control with a modified optimization technique. ©ECMS Mauro Iacono, Francesco Palmieri, Marco Gribaudo, Massimo Ficco (Editors). en
utb.faculty Faculty of Applied Informatics
dc.identifier.uri http://hdl.handle.net/10563/1008963
utb.identifier.obdid 43880843
utb.identifier.scopus 2-s2.0-85068806663
utb.identifier.wok 000477784500019
utb.source d-scopus
dc.date.accessioned 2019-08-16T09:30:13Z
dc.date.available 2019-08-16T09:30:13Z
utb.contributor.internalauthor Kubalčík, Marek
utb.wos.affiliation [Kubalcik, Marek] Tomas Bata Univ Zlin, Fac Appl Informat, Stranemi 4511, Zlin 76005, Czech Republic; [Barot, Tomas] Univ Ostrava, Fac Educ, Dept Math Didact, Fr Sramka 3, Ostrava 70900, Czech Republic
utb.scopus.affiliation Tomas Bata University in Zlin, Faculty of Applied Informatics, Nad Stranemi 4511, Zlin, 760 05, Czech Republic; Department of Mathematics with Didactics, University of Ostrava, Faculty of Education, Fr. Sramka 3, Ostrava, 709 00, Czech Republic
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