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Statements

Subject Item
n2:RIV%2F61989100%3A27740%2F14%3A86092520%21RIV15-MSM-27740___
rdf:type
n20:Vysledek skos:Concept
dcterms:description
System identification is one of the necessary tasks in controller design and its adaptation. Many identification methods are known, and new ones are still being developed in order to find a better solution for huge scale of cases. In the paper identification of system of 2nd order systems using genetic algorithms is demonstrated. In presented case genetic algorithms are used for finding parameters of difference equation of the controlled system and it substitutes classic, conventional optimization methods. Proposed method can be used for continuous identification or it can be activated in defined time points on stored data. And on the other hand, presented task is also a case of a specific usage of genetic algorithms and it can serve as a proof of efficiency of this non-conventional optimization method (simulated in the Matlab&Simulink software environment). System identification is one of the necessary tasks in controller design and its adaptation. Many identification methods are known, and new ones are still being developed in order to find a better solution for huge scale of cases. In the paper identification of system of 2nd order systems using genetic algorithms is demonstrated. In presented case genetic algorithms are used for finding parameters of difference equation of the controlled system and it substitutes classic, conventional optimization methods. Proposed method can be used for continuous identification or it can be activated in defined time points on stored data. And on the other hand, presented task is also a case of a specific usage of genetic algorithms and it can serve as a proof of efficiency of this non-conventional optimization method (simulated in the Matlab&Simulink software environment).
dcterms:title
System Identification Using Genetics Algorithm System Identification Using Genetics Algorithm
skos:prefLabel
System Identification Using Genetics Algorithm System Identification Using Genetics Algorithm
skos:notation
RIV/61989100:27740/14:86092520!RIV15-MSM-27740___
n4:aktivita
n9:S n9:P
n4:aktivity
P(ED1.1.00/02.0070), P(EE.2.3.20.0072), S
n4:dodaniDat
n14:2015
n4:domaciTvurceVysledku
n8:6390277
n4:druhVysledku
n16:D
n4:duvernostUdaju
n21:S
n4:entitaPredkladatele
n6:predkladatel
n4:idSjednocenehoVysledku
49120
n4:idVysledku
RIV/61989100:27740/14:86092520
n4:jazykVysledku
n17:eng
n4:klicovaSlova
optimization; genetic algorithms; system; Identification
n4:klicoveSlovo
n10:system n10:genetic%20algorithms n10:optimization n10:Identification
n4:kontrolniKodProRIV
[9A6A092A5125]
n4:mistoKonaniAkce
Ostrava
n4:mistoVydani
Berlin Heidelberg
n4:nazevZdroje
Advances in Intelligent Systems and Computing. Volume 303
n4:obor
n19:JB
n4:pocetDomacichTvurcuVysledku
1
n4:pocetTvurcuVysledku
2
n4:projekt
n7:ED1.1.00%2F02.0070 n7:EE.2.3.20.0072
n4:rokUplatneniVysledku
n14:2014
n4:tvurceVysledku
Nowaková, Jana Pokorný, Miroslav
n4:typAkce
n18:WRD
n4:wos
000342841800041
n4:zahajeniAkce
2014-06-23+02:00
s:issn
2194-5357
s:numberOfPages
6
n22:doi
10.1007/978-3-319-08156-4_41
n12:hasPublisher
Springer-Verlag. (Berlin; Heidelberg)
n13:isbn
978-3-319-08155-7
n5:organizacniJednotka
27740