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

The result's identifiers

  • Result code in 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>

  • Result on the web

    <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>

Alternative languages

  • Result language

    angličtina

  • Original language name

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

  • Original language description

    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.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    BC - Theory and management systems

  • OECD FORD branch

Result continuities

  • Project

    <a href="/en/project/GAP103%2F12%2F1187" target="_blank" >GAP103/12/1187: Identification of Stochastic, Nonlinear Systems for Advanced Control</a><br>

  • Continuities

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

Others

  • Publication year

    2013

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    Proceedings of 23rd European Symposium on Computer Aided Process Engineering

  • ISBN

    978-0-444-63234-0

  • ISSN

    1570-7946

  • e-ISSN

  • Number of pages

    6

  • Pages from-to

    205-210

  • Publisher name

    Elsevier

  • Place of publication

    Kidlington Oxford OX GB

  • Event location

    Lappeenranta

  • Event date

    Jun 9, 2013

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article

    000329495800035