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  • Controller design method Generalized Predictive Control is based on Controller Auto-Regressive Integrated Moving-Average (CARIMA) process model. Noise polynomial is usually used as a controller parameter (as a data filter) to increase controller robustness and it is called T-polynomial. Different approaches how to design this polynomial coming out from the process model and controller parameters are referred in literature. In the paper steady-state Kalman estimator is computed and its characteristic polynomial is used as a Tpolynomial. Suggested method is demonstrated on simulated control experiments with second order process.
  • Controller design method Generalized Predictive Control is based on Controller Auto-Regressive Integrated Moving-Average (CARIMA) process model. Noise polynomial is usually used as a controller parameter (as a data filter) to increase controller robustness and it is called T-polynomial. Different approaches how to design this polynomial coming out from the process model and controller parameters are referred in literature. In the paper steady-state Kalman estimator is computed and its characteristic polynomial is used as a Tpolynomial. Suggested method is demonstrated on simulated control experiments with second order process. (en)
  • Návrh regulátoru Generalized Predictive Control je založen na CARIMA modelu procesu. Polynom C je často uvažován jako parametr regulátoru (jako filtr dat) pro zvýšení robustnosti regulátoru. Nejprve je navržen Kalmánův filtr a jeho charakteristický polynom je použit v modelu procesu. Je uveden simulační experiment se soustavou druhého řádu. (cs)
Title
  • KALMAN FILTERING AND GENERALIZED PREDICTIVE CONTROL
  • KALMAN FILTERING AND GENERALIZED PREDICTIVE CONTROL (en)
  • Kalmánův filtr a prediktivní řízení (cs)
skos:prefLabel
  • KALMAN FILTERING AND GENERALIZED PREDICTIVE CONTROL
  • KALMAN FILTERING AND GENERALIZED PREDICTIVE CONTROL (en)
  • Kalmánův filtr a prediktivní řízení (cs)
skos:notation
  • RIV/00216275:25530/08:00005217!RIV08-MSM-25530___
http://linked.open.../vavai/riv/strany
  • 133-138
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • Z(MSM0021627505)
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
  • 374462
http://linked.open...ai/riv/idVysledku
  • RIV/00216275:25530/08:00005217
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  • predictive controller; Kalman estimator; data filtration (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [5215FD3DCFBD]
http://linked.open...i/riv/mistoVydani
  • Brno
http://linked.open...i/riv/nazevZdroje
  • Teorie dopravních systémů (soubor odborných statí)
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Havlíček, Libor
  • Honc, Daniel
  • Haber, Robert
http://linked.open...n/vavai/riv/zamer
number of pages
http://purl.org/ne...btex#hasPublisher
  • Tribun EU
https://schema.org/isbn
  • 978-80-7399-347-4
http://localhost/t...ganizacniJednotka
  • 25530
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