Combination of evolutionary and gradient optimization techniques in model predictive control

Antoš, Jan; Kubalčík, Marek

dc.title	Combination of evolutionary and gradient optimization techniques in model predictive control	en
dc.contributor.author	Antoš, Jan
dc.contributor.author	Kubalčík, Marek
dc.relation.ispartof	International Journal of Mathematical Models and Methods in Applied Sciences
dc.identifier.issn	1998-0140 Scopus Sources, Sherpa/RoMEO, JCR
dc.date.issued	2016
utb.relation.volume	10
dc.citation.spage	34
dc.citation.epage	41
dc.type	article
dc.language.iso	en
dc.publisher	North Atlantic University Union (NAUN)
dc.relation.uri	http://naun.org/cms.action?id=12152
dc.subject	Control process	en
dc.subject	Evolutionary algorithms	en
dc.subject	Gradients algorithms	en
dc.subject	Model predictive control	en
dc.subject	Optimization	en
dc.description.abstract	Model predictive control (MPC) designates a control method based on the model. This method is suitable for controlling of various kinds of systems. The basic principle is to calculate the future behaviour of a system and to use this prediction for the optimization of a control process. The optimization problem must be then solved in each sampling period. One of the advantages of MPC is its ability to do online constraints handling systematically. These constraints may, however, cause that the optimization problem is more complex. In this case, some iterative algorithms must be applied in order to solve this problem effectively. This paper is focus on the combination of the optimization techniques. The basic idea is to combine the advantages of gradient and evolutionary algorithms. © 2016, North Atlantic University Union NAUN. All rights reserved.	en
utb.faculty	Faculty of Applied Informatics
dc.identifier.uri	http://hdl.handle.net/10563/1006814
utb.identifier.obdid	43875818
utb.identifier.scopus	2-s2.0-85000399439
utb.source	j-scopus
dc.date.accessioned	2017-02-28T15:11:29Z
dc.date.available	2017-02-28T15:11:29Z
utb.ou	CEBIA-Tech
utb.contributor.internalauthor	Antoš, Jan
utb.contributor.internalauthor	Kubalčík, Marek
utb.fulltext.affiliation	Jan Antos and Marek Kubalcik Jan Antos is with the Tomas Bata University in Zlín, Faculty of Applied Informatics, Nám. T. G. Masaryka 5555, 760 05 Zlín (e-mail: antos@fai.utb.cz). Marek Kubalcik is with the Tomas Bata University in Zlín, Faculty of Applied Informatics, Nám. T. G. Masaryka 5555, 760 05 Zlín (corresponding author to provide phone: +420 57-603-5198; e-mail: kubalcik@fai.utb.cz).
utb.fulltext.dates	-
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utb.fulltext.sponsorship	Authors are thankful to Internal Grant Agency (IGA/CebiaTech/2015/026) of Tomas Bata University in Zlín, Czech Republic for financial support.