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Description
  • The problem of estimating parameters of linear models from noisy time series measurements of continuous dynamical systems is considered. Additional prior information (grey box) is used to improve the quality of the estimate, which can be useful, when obtaining sufficiently excited input/output experiment data is impracticable or costly. The problem is solved with respect to optimal multistep prediction for better performance in advanced control (model predictive control). This leads to a nonconvex numerical optimization, where the solver can easily run out in one of the many local extremes. Two approaches, how to improve the convergence, are introduced. Finally an example of identification for combustion control, based on real power plant data, is presented.
  • The problem of estimating parameters of linear models from noisy time series measurements of continuous dynamical systems is considered. Additional prior information (grey box) is used to improve the quality of the estimate, which can be useful, when obtaining sufficiently excited input/output experiment data is impracticable or costly. The problem is solved with respect to optimal multistep prediction for better performance in advanced control (model predictive control). This leads to a nonconvex numerical optimization, where the solver can easily run out in one of the many local extremes. Two approaches, how to improve the convergence, are introduced. Finally an example of identification for combustion control, based on real power plant data, is presented. (en)
  • The problem of estimating parameters of linear models from noisy time series measurements of continuous dynamical systems is considered. Additional prior information (grey box) is used to improve the quality of the estimate, which can be useful, when obtaining sufficiently excited input/output experiment data is impracticable or costly. The problem is solved with respect to optimal multistep prediction for better performance in advanced control (model predictive control). This leads to a nonconvex numerical optimization, where the solver can easily run out in one of the many local extremes. Two approaches, how to improve the convergence, are introduced. Finally an example of identification for combustion control, based on real power plant data, is presented. (cs)
Title
  • Identifikace grey-box modelu s praktickou aplikací v průmyslu a energetice
  • Identifikace grey-box modelu s praktickou aplikací v průmyslu a energetice (cs)
  • Grey box model identification with practical application to combustion control (en)
skos:prefLabel
  • Identifikace grey-box modelu s praktickou aplikací v průmyslu a energetice
  • Identifikace grey-box modelu s praktickou aplikací v průmyslu a energetice (cs)
  • Grey box model identification with practical application to combustion control (en)
skos:notation
  • RIV/68407700:21230/09:00158517!RIV10-GA0-21230___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(GA102/08/0442)
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 318380
http://linked.open...ai/riv/idVysledku
  • RIV/68407700:21230/09:00158517
http://linked.open...riv/jazykVysledku
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  • System identification; grey box model; nonlinear least squares; Maximum likelihood (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [E2173C660761]
http://linked.open...v/mistoKonaniAkce
  • Stará Lesná, Vysoké Tatry
http://linked.open...i/riv/mistoVydani
  • Košice
http://linked.open...i/riv/nazevZdroje
  • Identifikace grey-box modelu s praktickou aplikací v průmyslu a energetice
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...vavai/riv/projekt
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Havlena, Vladimír
  • Řehoř, Jiří
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
number of pages
http://purl.org/ne...btex#hasPublisher
  • Technická univerzita v Košiciach
https://schema.org/isbn
  • 978-80-553-0237-9
http://localhost/t...ganizacniJednotka
  • 21230
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