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Statements

Subject Item
n2:RIV%2F00216275%3A25530%2F07%3A00005212%21RIV08-MSM-25530___
rdf:type
n15:Vysledek skos:Concept
dcterms:description
Briefly theory is given to introduce Model Predictive Control (MPC) concept. Method called Generalized Predictive Control (GPC) published in [1], [2] and [3] is based on Controller Auto-Regressive Integrated Moving-Average (CARIMA) model. Resulting controller has integrating character. In white noise case (without data filtering) the controller is rather sensitive to the measurement noise and model uncertainties. Polynomial C in process model is usually used as a controller parameter (as a filter) to increase controller robustness and it is called as T-polynomial. Different approaches how to design this polynomial coming out from the process model and controller parameters are suggested in the literature [4]. In the paper Kalman estimator is designed and its characteristic polynomial is used as a polynomial T. Prediction abilities of the models with and without data filtering are compared. Briefly theory is given to introduce Model Predictive Control (MPC) concept. Method called Generalized Predictive Control (GPC) published in [1], [2] and [3] is based on Controller Auto-Regressive Integrated Moving-Average (CARIMA) model. Resulting controller has integrating character. In white noise case (without data filtering) the controller is rather sensitive to the measurement noise and model uncertainties. Polynomial C in process model is usually used as a controller parameter (as a filter) to increase controller robustness and it is called as T-polynomial. Different approaches how to design this polynomial coming out from the process model and controller parameters are suggested in the literature [4]. In the paper Kalman estimator is designed and its characteristic polynomial is used as a polynomial T. Prediction abilities of the models with and without data filtering are compared. Metoda Generalized Predictive Control je založena na CARIMA modelu procesu - regulátor má integrační charakter. V případě, že data nejsou filtrována, je regulátor poměrně citlivý na šum měření, který způsobuje kmitání akčních veličin a snížení kvality regulačního pochodu. T-polynom v modelu procesu, lze použít jako návrhový parametr - jako filtr dat. V článku je navržen postup výpočtu polynumu T tak, aby predikce výstupu soustavy byly identické s Kalmánovým pozorovatelem. Metoda je demonstrována na dvou jednoduchých příkladech.
dcterms:title
T-POLYNOMIAL IN GENERALIZED PREDICTIVE CONTROL Význam T-polynomu v prediktivním řízení T-POLYNOMIAL IN GENERALIZED PREDICTIVE CONTROL
skos:prefLabel
T-POLYNOMIAL IN GENERALIZED PREDICTIVE CONTROL T-POLYNOMIAL IN GENERALIZED PREDICTIVE CONTROL Význam T-polynomu v prediktivním řízení
skos:notation
RIV/00216275:25530/07:00005212!RIV08-MSM-25530___
n5:strany
55
n5:aktivita
n19:Z
n5:aktivity
Z(MSM0021627505)
n5:dodaniDat
n7:2008
n5:domaciTvurceVysledku
n18:1607111 n18:4112245
n5:druhVysledku
n8:D
n5:duvernostUdaju
n17:S
n5:entitaPredkladatele
n14:predkladatel
n5:idSjednocenehoVysledku
455433
n5:idVysledku
RIV/00216275:25530/07:00005212
n5:jazykVysledku
n10:eng
n5:klicovaSlova
Generalized Predictive Control; CARIMA model; T-polynomial; filtering
n5:klicoveSlovo
n6:filtering n6:CARIMA%20model n6:Generalized%20Predictive%20Control n6:T-polynomial
n5:kontrolniKodProRIV
[2930ED950A27]
n5:mistoKonaniAkce
Kongresové centrum ČVUT, Praha
n5:mistoVydani
Praha
n5:nazevZdroje
Sborník příspěvků 15. ročníku konference Technical Computing Prague 2007
n5:obor
n12:BC
n5:pocetDomacichTvurcuVysledku
2
n5:pocetTvurcuVysledku
2
n5:rokUplatneniVysledku
n7:2007
n5:tvurceVysledku
Honc, Daniel Dušek, František
n5:typAkce
n21:EUR
n5:zahajeniAkce
2007-11-14+01:00
n5:zamer
n9:MSM0021627505
s:numberOfPages
11
n13:hasPublisher
Humusoft s.r.o.
n3:isbn
978-80-7080-658-6
n20:organizacniJednotka
25530