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Statements

Subject Item
n2:RIV%2F68407700%3A21230%2F12%3A00195004%21RIV13-MPO-21230___
rdf:type
n6:Vysledek skos:Concept
rdfs:seeAlso
http://www.sciencedirect.com/science/article/pii/S0167691112001375
dcterms:description
Model identification plays a central role in any activity associated with process operations. With control being done on different levels, different models are required for the same plant, each for a different range of dynamics. Besides that most identification methods apply to the linear models, they also do not allow for selecting a frequency range. Wavelet-based methods have the intrinsic ability to select time and frequency windows, and, to some extent, are also applicable to non-linear processes. The paper presents an approach, in which the wavelet transform is employed for system identification enabling the selection of the particular frequency range of interest. We will show the use of some wavelet filters with a property of superior selectivity in the frequency domain and having compact support in the time domain, which, in turn, influences an accurate implementation. These properties provide us with a possibility of the measured data analysis in the frequency domain without any loss of information. Selection of a proper filter allows us to identify the system on a desired frequency range, or to identify a number of systems for distinct frequency ranges. This is specifically convenient for the systems with dominant modes, such as singularly perturbed systems. The possibility of selection of the specific frequency range can be utilized for application-based identification such as control, when only a limited frequency range is required. We conclude with a case study, where the proposed algorithms are tested and results are presented. Model identification plays a central role in any activity associated with process operations. With control being done on different levels, different models are required for the same plant, each for a different range of dynamics. Besides that most identification methods apply to the linear models, they also do not allow for selecting a frequency range. Wavelet-based methods have the intrinsic ability to select time and frequency windows, and, to some extent, are also applicable to non-linear processes. The paper presents an approach, in which the wavelet transform is employed for system identification enabling the selection of the particular frequency range of interest. We will show the use of some wavelet filters with a property of superior selectivity in the frequency domain and having compact support in the time domain, which, in turn, influences an accurate implementation. These properties provide us with a possibility of the measured data analysis in the frequency domain without any loss of information. Selection of a proper filter allows us to identify the system on a desired frequency range, or to identify a number of systems for distinct frequency ranges. This is specifically convenient for the systems with dominant modes, such as singularly perturbed systems. The possibility of selection of the specific frequency range can be utilized for application-based identification such as control, when only a limited frequency range is required. We conclude with a case study, where the proposed algorithms are tested and results are presented.
dcterms:title
System identification in frequency domain using wavelets: Conceptual remarks System identification in frequency domain using wavelets: Conceptual remarks
skos:prefLabel
System identification in frequency domain using wavelets: Conceptual remarks System identification in frequency domain using wavelets: Conceptual remarks
skos:notation
RIV/68407700:21230/12:00195004!RIV13-MPO-21230___
n6:predkladatel
n18:orjk%3A21230
n4:aktivita
n8:P
n4:aktivity
P(FR-TI1/517)
n4:cisloPeriodika
10
n4:dodaniDat
n17:2013
n4:domaciTvurceVysledku
n21:3601315
n4:druhVysledku
n11:J
n4:duvernostUdaju
n15:S
n4:entitaPredkladatele
n12:predkladatel
n4:idSjednocenehoVysledku
173042
n4:idVysledku
RIV/68407700:21230/12:00195004
n4:jazykVysledku
n20:eng
n4:klicovaSlova
Wavelet transform; System identification; Singular perturbation
n4:klicoveSlovo
n13:System%20identification n13:Wavelet%20transform n13:Singular%20perturbation
n4:kodStatuVydavatele
NL - Nizozemsko
n4:kontrolniKodProRIV
[2F3B4F2B9EC8]
n4:nazevZdroje
Systems & Control Letters
n4:obor
n10:BC
n4:pocetDomacichTvurcuVysledku
1
n4:pocetTvurcuVysledku
2
n4:projekt
n16:FR-TI1%2F517
n4:rokUplatneniVysledku
n17:2012
n4:svazekPeriodika
61
n4:tvurceVysledku
Váňa, Zdeněk Preisig, H. A.
n4:wos
000309628000011
s:issn
0167-6911
s:numberOfPages
11
n19:doi
10.1016/j.sysconle.2012.07.004
n5:organizacniJednotka
21230