Combination of Evolutionary and Gradient Optimization Techniques in Model Predictive Control

Kód výsledku v 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>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Combination of Evolutionary and Gradient Optimization Techniques in Model Predictive Control

Popis výsledku v původním jazyce

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

Název v anglickém jazyce

Combination of Evolutionary and Gradient Optimization Techniques in Model Predictive Control

Popis výsledku anglicky

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

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

BC - Teorie a systémy řízení

OECD FORD obor

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Projekt

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Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2016

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

International Journal of Mathematical Models and Methods in Applied Sciences

ISSN

1998-0140

e-ISSN

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Svazek periodika

10

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

GB - Spojené království Velké Británie a Severního Irska

Počet stran výsledku

8

Strana od-do

34-41

Kód UT WoS článku

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EID výsledku v databázi Scopus

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