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Statements

Subject Item
n2:RIV%2F00216275%3A25310%2F06%3A00004369%21RIV08-MSM-25310___
rdf:type
skos:Concept n15:Vysledek
dcterms:description
Briefly theory is given to introduce readers the Model Predictive Control concept. When Controller Auto-Regressive Integrated Moving-Average (CARIMA) model is used the solution is straightforward and resulting controller has integrating character (offset-free steady state control is archived). Admittedly the controller is rather sensitive to the measurement noise. This effect is lower when Auto-Regressive Moving-Average (CARMA) model is applied. Modifications of penalization matrix and plant output prediction computation are necessary in order to be the cost function identical as for the CARIMA model (to penalize the control increments). Simple comparative example is given to demonstrate measurement noise sensitivity of predictive controllers based on both discussed models. Briefly theory is given to introduce readers the Model Predictive Control concept. When Controller Auto-Regressive Integrated Moving-Average (CARIMA) model is used the solution is straightforward and resulting controller has integrating character (offset-free steady state control is archived). Admittedly the controller is rather sensitive to the measurement noise. This effect is lower when Auto-Regressive Moving-Average (CARMA) model is applied. Modifications of penalization matrix and plant output prediction computation are necessary in order to be the cost function identical as for the CARIMA model (to penalize the control increments). Simple comparative example is given to demonstrate measurement noise sensitivity of predictive controllers based on both discussed models. Čtenář je seznámen s konceptem prediktivního řízení. Řešení s Controller Auto-Regressive Integrated Moving-Average (CARIMA) modelem je přímočaré a regulátor má integrační character (nezanechává trvalou regulační odchylku). Tento regulátor je ovšem velmi citlivý na šum měření. Citlivost na šum je nižší, použijeme-li Auto-Regressive Moving-Average (CARMA) model. Teoretické závěry jsou demonstrovány na jednoduchém příkladu.
dcterms:title
CARIMA versus CARMA Model in Predictive Control CARIMA versus CARMA Model in Predictive Control CARIMA versus CARMA model v prediktivním řízení
skos:prefLabel
CARIMA versus CARMA model v prediktivním řízení CARIMA versus CARMA Model in Predictive Control CARIMA versus CARMA Model in Predictive Control
skos:notation
RIV/00216275:25310/06:00004369!RIV08-MSM-25310___
n3:strany
53-55
n3:aktivita
n14:Z
n3:aktivity
Z(MSM0021627505)
n3:cisloPeriodika
1
n3:dodaniDat
n12:2008
n3:domaciTvurceVysledku
n6:4112245
n3:druhVysledku
n4:J
n3:duvernostUdaju
n13:S
n3:entitaPredkladatele
n9:predkladatel
n3:idSjednocenehoVysledku
467783
n3:idVysledku
RIV/00216275:25310/06:00004369
n3:jazykVysledku
n18:eng
n3:klicovaSlova
Model Predictive Control; CARIMA model; CARMA model; measurement noise sensitivity
n3:klicoveSlovo
n11:CARMA%20model n11:Model%20Predictive%20Control n11:measurement%20noise%20sensitivity n11:CARIMA%20model
n3:kodStatuVydavatele
SK - Slovenská republika
n3:kontrolniKodProRIV
[D562C518DAB6]
n3:nazevZdroje
Manufacturing Engineering / Výrobné inžinierstvo
n3:obor
n16:BC
n3:pocetDomacichTvurcuVysledku
1
n3:pocetTvurcuVysledku
1
n3:rokUplatneniVysledku
n12:2006
n3:svazekPeriodika
5
n3:tvurceVysledku
Honc, Daniel
n3:zamer
n17:MSM0021627505
s:issn
1335-7972
s:numberOfPages
3
n8:organizacniJednotka
25310