Combination of Evolutionary and Gradient Optimization Techniques in Model Predictive Control

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F70883521%3A28140%2F16%3A43875103" target="_blank" >RIV/70883521:28140/16:43875103 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Combination of Evolutionary and Gradient Optimization Techniques in Model Predictive Control
Original language description
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 principleis 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
Czech name
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Czech description
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Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
BC - Theory and management systems
OECD FORD branch
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Publication year
2016
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical
International Journal of Mathematical Models and Methods in Applied Sciences
ISSN
1998-0140
e-ISSN
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Volume of the periodical
10
Issue of the periodical within the volume
1
Country of publishing house
GB - UNITED KINGDOM
Number of pages
8
Pages from-to
34-41
UT code for WoS article
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EID of the result in the Scopus database
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