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Statements

Subject Item
n2:RIV%2F00216305%3A26220%2F04%3APU44010%21RIV11-MSM-26220___
rdf:type
n8:Vysledek skos:Concept
dcterms:description
The algorithm for the semi-inversion controller has been designed for adaptive control based on neural networks. This controller originally designed for linear systems proved to have favorable characteristics also for considerably non-linear systems. The algorithm deals with extreme inversion controlling actions occurring in inversion control. We used the semi-inversion controller for control a real system – laboratory hot-air system model. The efficient of control algorithm we demonstrate by control MIMO system with two parameters – the airflow and the temperature inside the tunnel. The hot-air system displays negative effects commonly occurring in industrial applications – different static amplifications at different operating points, large offset increasing with time, dead zone and noise. The algorithm for the semi-inversion controller has been designed for adaptive control based on neural networks. This controller originally designed for linear systems proved to have favorable characteristics also for considerably non-linear systems. The algorithm deals with extreme inversion controlling actions occurring in inversion control. We used the semi-inversion controller for control a real system – laboratory hot-air system model. The efficient of control algorithm we demonstrate by control MIMO system with two parameters – the airflow and the temperature inside the tunnel. The hot-air system displays negative effects commonly occurring in industrial applications – different static amplifications at different operating points, large offset increasing with time, dead zone and noise.
dcterms:title
Simple Neural Network-Based Adaptive Controller for Heating System Simple Neural Network-Based Adaptive Controller for Heating System
skos:prefLabel
Simple Neural Network-Based Adaptive Controller for Heating System Simple Neural Network-Based Adaptive Controller for Heating System
skos:notation
RIV/00216305:26220/04:PU44010!RIV11-MSM-26220___
n3:aktivita
n5:P n5:V n5:Z
n3:aktivity
P(GD102/03/H116), V, Z(MSM 260000013)
n3:dodaniDat
n15:2011
n3:domaciTvurceVysledku
n11:5109965 n11:9304010
n3:druhVysledku
n19:D
n3:duvernostUdaju
n13:S
n3:entitaPredkladatele
n10:predkladatel
n3:idSjednocenehoVysledku
586225
n3:idVysledku
RIV/00216305:26220/04:PU44010
n3:jazykVysledku
n18:eng
n3:klicovaSlova
Adaptive Control, Neural Networks, Simple Neural Controller
n3:klicoveSlovo
n12:Neural%20Networks n12:Adaptive%20Control n12:Simple%20Neural%20Controller
n3:kontrolniKodProRIV
[3A6EDB14AA5B]
n3:mistoKonaniAkce
Zittau
n3:mistoVydani
Zittau, Germany
n3:nazevZdroje
Proceedings East West Fuzzy Colloquium 2004
n3:obor
n22:BC
n3:pocetDomacichTvurcuVysledku
2
n3:pocetTvurcuVysledku
2
n3:projekt
n21:GD102%2F03%2FH116
n3:rokUplatneniVysledku
n15:2004
n3:tvurceVysledku
Pivoňka, Petr Veleba, Václav
n3:typAkce
n9:EUR
n3:zahajeniAkce
2004-11-08+01:00
n3:zamer
n4:MSM%20260000013
s:numberOfPages
6
n16:hasPublisher
Rektor der Hochschule Zitttau/Görlitz
n17:isbn
3-9808089-5-5
n20:organizacniJednotka
26220