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Modifications of optimization algorithms applied in multivariable predictive control

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dc.title Modifications of optimization algorithms applied in multivariable predictive control en
dc.contributor.author Kubalčík, Marek
dc.contributor.author Bobál, Vladimír
dc.contributor.author Barot, Tomáš
dc.relation.ispartof WSEAS Transactions on Systems and Control
dc.identifier.issn 1991-8763 Scopus Sources, Sherpa/RoMEO, JCR
dc.date.issued 2018
utb.relation.volume 13
dc.citation.spage 497
dc.citation.epage 505
dc.type article
dc.language.iso en
dc.publisher World Scientific and Engineering Academy and Society (WSEAS)
dc.subject Constraints en
dc.subject Hildreth’s method en
dc.subject Model predictive control en
dc.subject Multivariable control en
dc.subject Optimization en
dc.subject Quadratic programming en
dc.description.abstract Non-linear optimization, particularly quadratic programming (QP), is a mathematical method which is widely applicable in model predictive control (MPC). It is significantly important if constraints of variables are considered in MPC and the optimization task is then computationally demanding. The result of the optimization is a vector of future increments of a manipulated variable. The first element of this vector is applied in the next sampling period of MPC in the framework of a receding horizon strategy. In practical realization of a multivariable MPC, the optimization is characterized by higher computational complexity. Therefore, reduction of the computational complexity of the optimization methods has been widely researched. Besides the generally used numerical Hildreth’s method of QP, a possible suitable modification is based on precomputing operations proposed by Wang, L. This general optimization strategy is further modified. Two modifications, which could be applied separately each, were interconnected in this paper. The first modification was published previously; however, its application can be more efficient in connection with the second proposed approach, which modifies precomputing operations. Decreasing of the computational complexity of the optimization by using of the proposal is discussed and analyzed by measurements of floating point operations and control quality criterions using hypotheses tests – paired T-test and Wilcoxon test. © 2018, World Scientific and Engineering Academy and Society. All rights reserved. en
utb.faculty Faculty of Applied Informatics
dc.identifier.uri http://hdl.handle.net/10563/1008502
utb.identifier.obdid 43878742
utb.identifier.scopus 2-s2.0-85061282662
utb.source j-scopus
dc.date.accessioned 2019-07-08T11:59:52Z
dc.date.available 2019-07-08T11:59:52Z
dc.rights Attribution 4.0 International
dc.rights.uri http://creativecommons.org/licenses/by/4.0/
dc.rights.access openAccess
utb.contributor.internalauthor Kubalčík, Marek
utb.contributor.internalauthor Bobál, Vladimír
utb.scopus.affiliation Department of Process Control Faculty of Applied Informatics Tomas, Bata University in Zlin, Nad Stranemi 4511, Zlin, 76005, Czech Republic; Department of Mathematics with Didactics Faculty of Education, University of Ostrava, Frani Sramka 3, Ostrava, 709 00, Czech Republic
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