Building modeling: on selection of the model complexity for predictive control

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F13%3A00206010" target="_blank" >RIV/68407700:21230/13:00206010 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1016/B978-0-444-63234-0.50035-X" target="_blank" >http://dx.doi.org/10.1016/B978-0-444-63234-0.50035-X</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/B978-0-444-63234-0.50035-X" target="_blank" >10.1016/B978-0-444-63234-0.50035-X</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Building modeling: on selection of the model complexity for predictive control

Popis výsledku v původním jazyce

Model Predictive Control has become a wide-spread solution in many industrial applications and is gaining ground in the field of energy management of the buildings. A model with good prediction properties is an ultimate condition for good performance ofthe predictive controller. In this paper grey box modeling and model predictive control relevant identification are used for construction of candidate models of a building. We introduce a two-stage iterative procedure for model selection: in the first stage a minimum set of disturbance inputs is formed such that the resulting model is the best with respect to defined criterion; then the second stage comprises addition of states to obtain a final minimum parameter set maximizing the model quality. The procedure stops when it makes no sense to select more complex model as it brings no more quality improvements. Finally a case study is provided where all the above mentioned approaches are investigated.

Název v anglickém jazyce

Building modeling: on selection of the model complexity for predictive control

Popis výsledku anglicky

Model Predictive Control has become a wide-spread solution in many industrial applications and is gaining ground in the field of energy management of the buildings. A model with good prediction properties is an ultimate condition for good performance ofthe predictive controller. In this paper grey box modeling and model predictive control relevant identification are used for construction of candidate models of a building. We introduce a two-stage iterative procedure for model selection: in the first stage a minimum set of disturbance inputs is formed such that the resulting model is the best with respect to defined criterion; then the second stage comprises addition of states to obtain a final minimum parameter set maximizing the model quality. The procedure stops when it makes no sense to select more complex model as it brings no more quality improvements. Finally a case study is provided where all the above mentioned approaches are investigated.

Druh

D - Stať ve sborníku

CEP obor

BC - Teorie a systémy řízení

OECD FORD obor

—

Projekt

<a href="/cs/project/GAP103%2F12%2F1187" target="_blank" >GAP103/12/1187: Identifikace stochastických, nelineárních systémů pro pokročilé řízení</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2013

Kód důvěrnosti údajů

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

Název statě ve sborníku

Proceedings of 23rd European Symposium on Computer Aided Process Engineering

ISBN

978-0-444-63234-0

ISSN

1570-7946

e-ISSN

—

Počet stran výsledku

6

Strana od-do

205-210

Název nakladatele

Elsevier

Místo vydání

Kidlington Oxford OX GB

Místo konání akce

Lappeenranta

Datum konání akce

9. 6. 2013

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000329495800035