Bridging the gap between the linear and nonlinear predictive control: Adaptations fo refficient building climate control

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F16%3A00460306" target="_blank" >RIV/67985556:_____/16:00460306 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/68407700:21230/16:00239848

Výsledek na webu

<a href="http://dx.doi.org/10.1016/j.conengprac.2016.01.007" target="_blank" >http://dx.doi.org/10.1016/j.conengprac.2016.01.007</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.conengprac.2016.01.007" target="_blank" >10.1016/j.conengprac.2016.01.007</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Bridging the gap between the linear and nonlinear predictive control: Adaptations fo refficient building climate control

Popis výsledku v původním jazyce

The linear model predictive control which is frequently used for building climate control benefits from the fact that the resulting optimization task is convex (thus easily and quickly solvable). On the other hand, the nonlinear model predictive control enables the use of a more detailed nonlinear model and it takes advantage of the fact that it addresses the optimization task more directly, however, it requires a more computationally complex algorithm for solving the non-convex optimization problem. In this paper,the gap between the linear and the nonlinear one is bridged by introducing apredictive controller with linear time-dependent model. Making use of linear time-dependent model of the building, the newly proposed controller obtains predictions which are closer to reality than those of linear time in-variant model, however,the computational complexity is still kept low since the optimization task remains convex.

Název v anglickém jazyce

Bridging the gap between the linear and nonlinear predictive control: Adaptations fo refficient building climate control

Popis výsledku anglicky

The linear model predictive control which is frequently used for building climate control benefits from the fact that the resulting optimization task is convex (thus easily and quickly solvable). On the other hand, the nonlinear model predictive control enables the use of a more detailed nonlinear model and it takes advantage of the fact that it addresses the optimization task more directly, however, it requires a more computationally complex algorithm for solving the non-convex optimization problem. In this paper,the gap between the linear and the nonlinear one is bridged by introducing apredictive controller with linear time-dependent model. Making use of linear time-dependent model of the building, the newly proposed controller obtains predictions which are closer to reality than those of linear time in-variant model, however,the computational complexity is still kept low since the optimization task remains convex.

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

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2016

Kód důvěrnosti údajů

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

Název periodika

Control Engineering Practice

ISSN

0967-0661

e-ISSN

—

Svazek periodika

53

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

GB - Spojené království Velké Británie a Severního Irska

Počet stran výsledku

15

Strana od-do

124-138

Kód UT WoS článku

000378955700012

EID výsledku v databázi Scopus

2-s2.0-84956865804