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Statements

Subject Item
n2:RIV%2F00216275%3A25530%2F07%3A00005213%21RIV08-MSM-25530___
rdf:type
skos:Concept n11:Vysledek
dcterms:description
Článek je věnován prediktivnímu řízení Generalized Predictive Control, které je založeno na CARIMA modelu procesu. Jsou uvedeny regulační experimenty na laboratorním zařízení. Polynom šumu je uvažován jako laditelný parametr regulátoru. Je ukázáno jak tento polynom (filtr dat) zvyšuje robustnost regulátoru proti vysokofrekvenčním poruchám - např. proti šumu měření. Popularity of Model Predictive Control techniques is growing in recent years. It is an intuitive and general design method convenient for controlling of multivariable plants, systems with dead-times and it enables simple constraints handling and future references. Authors deal with Generalized Predictive Control based on CARIMA process model. Control experiments with pilot plant are presented by considering the noise polynomial as a tuneable controller parameter. It is shown how the noise polynomial (data filter) improves the controller insensitivity against the high frequency uncertainties ? i.e. the measurement noise. Popularity of Model Predictive Control techniques is growing in recent years. It is an intuitive and general design method convenient for controlling of multivariable plants, systems with dead-times and it enables simple constraints handling and future references. Authors deal with Generalized Predictive Control based on CARIMA process model. Control experiments with pilot plant are presented by considering the noise polynomial as a tuneable controller parameter. It is shown how the noise polynomial (data filter) improves the controller insensitivity against the high frequency uncertainties ? i.e. the measurement noise.
dcterms:title
Application of noise filter with multivariable GPC Aplikace filtru šumu s vícerozměrovým prediktivním regulátorem Application of noise filter with multivariable GPC
skos:prefLabel
Aplikace filtru šumu s vícerozměrovým prediktivním regulátorem Application of noise filter with multivariable GPC Application of noise filter with multivariable GPC
skos:notation
RIV/00216275:25530/07:00005213!RIV08-MSM-25530___
n4:strany
112-117
n4:aktivita
n12:Z
n4:aktivity
Z(MSM0021627505)
n4:cisloPeriodika
2
n4:dodaniDat
n7:2008
n4:domaciTvurceVysledku
n5:4112245
n4:druhVysledku
n15:J
n4:duvernostUdaju
n13:S
n4:entitaPredkladatele
n14:predkladatel
n4:idSjednocenehoVysledku
410495
n4:idVysledku
RIV/00216275:25530/07:00005213
n4:jazykVysledku
n6:eng
n4:klicovaSlova
TITO control; generalized predictive control; CARIMA model; noise model; noise filtering
n4:klicoveSlovo
n10:generalized%20predictive%20control n10:CARIMA%20model n10:noise%20model n10:noise%20filtering n10:TITO%20control
n4:kodStatuVydavatele
SK - Slovenská republika
n4:kontrolniKodProRIV
[21996E606280]
n4:nazevZdroje
AT&P journal PLUS 2
n4:obor
n8:BC
n4:pocetDomacichTvurcuVysledku
1
n4:pocetTvurcuVysledku
2
n4:rokUplatneniVysledku
n7:2007
n4:svazekPeriodika
2
n4:tvurceVysledku
Haber, Robert Honc, Daniel
n4:zamer
n16:MSM0021627505
s:issn
1336-5010
s:numberOfPages
6
n17:organizacniJednotka
25530