About: Modelling and Predictive Control of an Evaporator using Local Model Network

Facets (new session)
Description
Metadata
Settings
- owl:sameAs
- Inference Rule:

About: Modelling and Predictive Control of an Evaporator using Local Model Network Goto Sponge NotDistinct Permalink

An Entity of Type : http://linked.opendata.cz/ontology/domain/vavai/Vysledek, within Data Space : linked.opendata.cz associated with source document(s)

Attributes	Values
rdf:type	skos:Concept http://linked.opendata.cz/ontology/domain/vavai/Vysledek
Description	The application of fuzzy clustering and local models for modelling and control of an evaporator is studied in the paper. The main idea is based on development of the local linear models for the whole operating range of the controlled process. The number of local models is iteratively increased until the modelling performance is reached. The position of the local model is obtained via clustering and parameters of the local models are identified using local least squares method. The nonlinear plant is then approximated by a set of locally valid sub-models, which are smoothly connected using the validity function. The parameters for the GPC controller are computed at each sampling interval from the linearization of LMN. The proposed identification and control method is illustrated by the simulation study on the evaporator. The application of fuzzy clustering and local models for modelling and control of an evaporator is studied in the paper. The main idea is based on development of the local linear models for the whole operating range of the controlled process. The number of local models is iteratively increased until the modelling performance is reached. The position of the local model is obtained via clustering and parameters of the local models are identified using local least squares method. The nonlinear plant is then approximated by a set of locally valid sub-models, which are smoothly connected using the validity function. The parameters for the GPC controller are computed at each sampling interval from the linearization of LMN. The proposed identification and control method is illustrated by the simulation study on the evaporator. (en)
Title	Modelling and Predictive Control of an Evaporator using Local Model Network Modelling and Predictive Control of an Evaporator using Local Model Network (en)
skos:prefLabel	Modelling and Predictive Control of an Evaporator using Local Model Network Modelling and Predictive Control of an Evaporator using Local Model Network (en)
skos:notation	RIV/70883521:28140/10:63508847!RIV11-GA0-28140___
http://linked.open...avai/riv/aktivita	P
http://linked.open...avai/riv/aktivity	P(GP102/09/P243)
http://linked.open...vai/riv/dodaniDat	2011
http://linked.open...aciTvurceVysledku	Novák, Jakub Chalupa, Petr Bobál, Vladimír
http://linked.open.../riv/druhVysledku	O - Ostatní výsledky nezařaditelné do žádného z výše uvedených druhů výsledku
http://linked.open...iv/duvernostUdaju	S - Úplné a pravdivé údaje nepodléhající ochraně podle zvláštních právních předpisů
http://linked.open...titaPredkladatele	Univerzita Tomáše Bati ve Zlíně / Fakulta aplikované informatiky
http://linked.open...dnocenehoVysledku	271921
http://linked.open...ai/riv/idVysledku	RIV/70883521:28140/10:63508847
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	fuzzy modelling; nonlinear models; neural networks; least-squares identification; predictive control (en)
http://linked.open.../riv/klicoveSlovo	predictive control least-squares identification nonlinear models neural networks fuzzy modelling
http://linked.open...ontrolniKodProRIV	[691BAB262E89]
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	Nonlinear System Predictive Control using Local Model Networks
http://linked.open...UplatneniVysledku	2010
http://linked.open...iv/tvurceVysledku	Bobál, Vladimír Chalupa, Petr Novák, Jakub
http://localhost/t...ganizacniJednotka	28140

Faceted Search & Find service v1.16.118 as of Jun 21 2024

Alternative Linked Data Documents: ODE Content Formats:

RDF

ODATA

Microdata

About

OpenLink Virtuoso version 07.20.3240 as of Jun 21 2024, on Linux (x86_64-pc-linux-gnu), Single-Server Edition (126 GB total memory, 85 GB memory in use)
Data on this page belongs to its respective rights holders.
Virtuoso Faceted Browser Copyright © 2009-2024 OpenLink Software