About: Using of Neural Network Based Identification for Short Sampling Period in Adaptive Control

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rdf:type	skos:Concept http://linked.opendata.cz/ontology/domain/vavai/Vysledek
Description	The new approach to analysis of on-line identification methods based on one-step-ahead prediction clears up their sensitivity to disturbances in control loop and explain why should be neural network based identification better then classical by using of short sampling period. The use of short sampling period in adaptive control has not been described properly when controlling the real process by adaptive controller. On one hand faster disturbance rejection due to short sampling period can be an advantage but on the other hand it brings us some practical problems. Particularly, quantization error and finite numerical precision of industrial controller must be considered in the real process control. We concentrate our attention on dealing with adverse effects that work on real-time identification of process, especially quantization. It is shown; that a neural network applied to on-line identification process produces more stable solution in the rapid sampling. The new approach to analysis of on-line identification methods based on one-step-ahead prediction clears up their sensitivity to disturbances in control loop and explain why should be neural network based identification better then classical by using of short sampling period. The use of short sampling period in adaptive control has not been described properly when controlling the real process by adaptive controller. On one hand faster disturbance rejection due to short sampling period can be an advantage but on the other hand it brings us some practical problems. Particularly, quantization error and finite numerical precision of industrial controller must be considered in the real process control. We concentrate our attention on dealing with adverse effects that work on real-time identification of process, especially quantization. It is shown; that a neural network applied to on-line identification process produces more stable solution in the rapid sampling. (en) Nový přístup pro identifikaci dynamických systémů s neuronovými sítěmi dovoluje použití krátké periody vzorkování. (cs)
Title	Using of Neural Network Based Identification for Short Sampling Period in Adaptive Control Using of Neural Network Based Identification for Short Sampling Period in Adaptive Control (en) Použití neuronových sítí v adaptivním řízení při krátké periodě vzorkování (cs)
skos:prefLabel	Using of Neural Network Based Identification for Short Sampling Period in Adaptive Control Using of Neural Network Based Identification for Short Sampling Period in Adaptive Control (en) Použití neuronových sítí v adaptivním řízení při krátké periodě vzorkování (cs)
skos:notation	RIV/00216305:26220/07:PU69904!RIV08-GA0-26220___
http://linked.open.../vavai/riv/strany	217-222
http://linked.open...avai/riv/aktivita	P Z
http://linked.open...avai/riv/aktivity	P(GA102/06/1132), Z(MSM0021630503)
http://linked.open...vai/riv/dodaniDat	2008
http://linked.open...aciTvurceVysledku	Veleba, Václav Pivoňka, Petr Ošmera, Pavel
http://linked.open.../riv/druhVysledku	D - Článek ve sborníku
http://linked.open...iv/duvernostUdaju	S - Úplné a pravdivé údaje nepodléhající ochraně podle zvláštních právních předpisů
http://linked.open...titaPredkladatele	Vysoké učení technické v Brně / Fakulta elektrotechniky a komunikačních technologií
http://linked.open...dnocenehoVysledku	457028
http://linked.open...ai/riv/idVysledku	RIV/00216305:26220/07:PU69904
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	Rapid sampling domain, Neural networks for identification, Comparison of identifications methods (en)
http://linked.open.../riv/klicoveSlovo	Comparison of identifications methods Neural networks for identification Rapid sampling domain
http://linked.open...ontrolniKodProRIV	[F9DF93ADA84F]
http://linked.open...v/mistoKonaniAkce	Crete, Greece
http://linked.open...i/riv/mistoVydani	Řecko
http://linked.open...i/riv/nazevZdroje	Systems Theory and Applications
http://linked.open...in/vavai/riv/obor	BC
http://linked.open...ichTvurcuVysledku	3 (xsd:int)
http://linked.open...cetTvurcuVysledku	3 (xsd:int)
http://linked.open...vavai/riv/projekt	Softcomputing in Control
http://linked.open...UplatneniVysledku	2007
http://linked.open...iv/tvurceVysledku	Pivoňka, Petr Ošmera, Pavel Veleba, Václav
http://linked.open...vavai/riv/typAkce	WRD - Světová
http://linked.open.../riv/zahajeniAkce	2007-07-23 (xsd:date)
http://linked.open...n/vavai/riv/zamer	Nové trendy v mikroelektronických systémech a nanotechnologiích (MIKROSYN)
number of pages	6 (xsd:int)
http://purl.org/ne...btex#hasPublisher	WSEAS
https://schema.org/isbn	978-960-8457-90-4
http://localhost/t...ganizacniJednotka	26220
is http://linked.open...avai/riv/vysledek of	Using of Neural Network Based Identification for Short Sampling Period in Adaptive Control Using of Neural Network Based Identification for Short Sampling Period in Adaptive Control Using of Neural Network Based Identification for Short Sampling Period in Adaptive Control

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