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Statements

Subject Item
n2:RIV%2F48361143%3A_____%2F10%3A%230000002%21RIV12-MSM-48361143
rdf:type
skos:Concept n13:Vysledek
rdfs:seeAlso
http://library.utia.cas.cz/separaty/2010/AS/karny-parallel%20estimation%20respecting%20constraints%20of%20parametric%20models%20of%20cold%20rolling.pdf
dcterms:description
Model-based predictors and controllers frequently depend on efficient recursive estimation of model parameters. Similarly often, there are known hard bounds on parameter values. Adaptive control applied for rolling mills represents a typical example of such case. While common estimation algorithms are elaborated enough to be utilized in industrial practice, it is difficult to find implementation of bounded estimation, which is both formally consistent and suitable for reliable applications. Solution offered in this paper is based on simultaneous run of two or more proven estimators different in applied process models. Both simulated and real data examples are provided. Model-based predictors and controllers frequently depend on efficient recursive estimation of model parameters. Similarly often, there are known hard bounds on parameter values. Adaptive control applied for rolling mills represents a typical example of such case. While common estimation algorithms are elaborated enough to be utilized in industrial practice, it is difficult to find implementation of bounded estimation, which is both formally consistent and suitable for reliable applications. Solution offered in this paper is based on simultaneous run of two or more proven estimators different in applied process models. Both simulated and real data examples are provided.
dcterms:title
Parallel Estimation Respecting Constraints of Parametric Models of Cold Rolling Parallel Estimation Respecting Constraints of Parametric Models of Cold Rolling
skos:prefLabel
Parallel Estimation Respecting Constraints of Parametric Models of Cold Rolling Parallel Estimation Respecting Constraints of Parametric Models of Cold Rolling
skos:notation
RIV/48361143:_____/10:#0000002!RIV12-MSM-48361143
n3:aktivita
n17:P
n3:aktivity
P(7D09008)
n3:dodaniDat
n7:2012
n3:domaciTvurceVysledku
n11:6585256 n11:2092298
n3:druhVysledku
n19:D
n3:duvernostUdaju
n14:S
n3:entitaPredkladatele
n8:predkladatel
n3:idSjednocenehoVysledku
278050
n3:idVysledku
RIV/48361143:_____/10:#0000002
n3:jazykVysledku
n21:eng
n3:klicovaSlova
parameter estimation; process model; identification; steel industry
n3:klicoveSlovo
n4:identification n4:process%20model n4:parameter%20estimation n4:steel%20industry
n3:kontrolniKodProRIV
[481174D2A22C]
n3:mistoKonaniAkce
Cape Town, South Africa
n3:mistoVydani
Cape Town, South Africa
n3:nazevZdroje
13th IFAC Symposium on Automation in Mineral, Mining and Metal Processing
n3:obor
n18:BC
n3:pocetDomacichTvurcuVysledku
2
n3:pocetTvurcuVysledku
2
n3:projekt
n20:7D09008
n3:rokUplatneniVysledku
n7:2010
n3:tvurceVysledku
Ettler, Pavel Kárný, Miroslav
n3:typAkce
n9:WRD
n3:zahajeniAkce
2010-01-01+01:00
s:numberOfPages
6
n5:doi
10.3182/20100802-3-ZA-2014.00007
n22:hasPublisher
University of Stellenbosch, South Africa
n15:isbn
978-3-902661-73-9