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Statements

Subject Item
n2:RIV%2F00216305%3A26220%2F10%3APU88662%21RIV11-GA0-26220___
rdf:type
n16:Vysledek skos:Concept
dcterms:description
This article deals with process identification, using nonlinear ARX model via feed-forward multilayer neural network. Estimation of network parameters is achieved using the Levenberg-Marquardt (LM) method in iterative batch mode adaptation. In order to obtain consistent estimate, original implementations of LM algorithm - which include instrumental variables (IV) technique - are suggested. Basic and extended IV methods are presented as some of the IV methods. Advantages of the proposed approach are illustrated in the example simulations on the real process, using B&R PLC. This article deals with process identification, using nonlinear ARX model via feed-forward multilayer neural network. Estimation of network parameters is achieved using the Levenberg-Marquardt (LM) method in iterative batch mode adaptation. In order to obtain consistent estimate, original implementations of LM algorithm - which include instrumental variables (IV) technique - are suggested. Basic and extended IV methods are presented as some of the IV methods. Advantages of the proposed approach are illustrated in the example simulations on the real process, using B&R PLC.
dcterms:title
A Levenberg-Marquardt algorithm with instrumental variables and its application on the identification of dynamic system A Levenberg-Marquardt algorithm with instrumental variables and its application on the identification of dynamic system
skos:prefLabel
A Levenberg-Marquardt algorithm with instrumental variables and its application on the identification of dynamic system A Levenberg-Marquardt algorithm with instrumental variables and its application on the identification of dynamic system
skos:notation
RIV/00216305:26220/10:PU88662!RIV11-GA0-26220___
n7:aktivita
n9:Z n9:P
n7:aktivity
P(GA102/09/1680), Z(MSM0021630529)
n7:dodaniDat
n10:2011
n7:domaciTvurceVysledku
n17:9304010 n17:5567696
n7:druhVysledku
n19:D
n7:duvernostUdaju
n12:S
n7:entitaPredkladatele
n21:predkladatel
n7:idSjednocenehoVysledku
244663
n7:idVysledku
RIV/00216305:26220/10:PU88662
n7:jazykVysledku
n18:eng
n7:klicovaSlova
Neural networks, Levenberg-Marquardt, NARX, Instrumental variables, System identification
n7:klicoveSlovo
n13:System%20identification n13:Levenberg-Marquardt n13:NARX n13:Neural%20networks n13:Instrumental%20variables
n7:kontrolniKodProRIV
[0A297B0E7A9A]
n7:mistoKonaniAkce
Zadar
n7:mistoVydani
TU Wien Karlsplatz 13/311 A-1040 Vienna Austria
n7:nazevZdroje
Annals of DAAAM for 2010 & Proceedings of the 21st International DAAAM Symposium, No1
n7:obor
n15:BC
n7:pocetDomacichTvurcuVysledku
2
n7:pocetTvurcuVysledku
2
n7:projekt
n11:GA102%2F09%2F1680
n7:rokUplatneniVysledku
n10:2010
n7:tvurceVysledku
Dokoupil, Jakub Pivoňka, Petr
n7:typAkce
n22:WRD
n7:zahajeniAkce
2010-10-20+02:00
n7:zamer
n8:MSM0021630529
s:numberOfPages
2
n5:hasPublisher
DAAAM International Vienna
n20:isbn
978-3-901509-73-5
n14:organizacniJednotka
26220