Incorporation of system steady state properties into subspace identification algorithm

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F12%3A00193605" target="_blank" >RIV/68407700:21230/12:00193605 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1504/IJMIC.2012.047123" target="_blank" >http://dx.doi.org/10.1504/IJMIC.2012.047123</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1504/IJMIC.2012.047123" target="_blank" >10.1504/IJMIC.2012.047123</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Incorporation of system steady state properties into subspace identification algorithm

Popis výsledku v původním jazyce

Most of the industrial applications are multiple-input multiple-output (MIMO) systems that can be identified using the knowledge of the system's physics or from measured data employing statistical methods. Currently, there is the only class of statistical identification methods capable of handling the issue of the vast MIMO systems - subspace identification methods. These methods, however, as all the statistical methods, need data of a certain quality, i.e., excitation of the corresponding order, no data corruption, etc. Nevertheless, combination of the statistical methods and a physical knowledge of the system could significantly improve system identification. This paper presents a new algorithm which provides remedy to the insufficient data quality of a certain kind through incorporation of the prior information, namely a known static gain and an input-output feed-through. The presented algorithm naturally extends classical subspace identification algorithms, that is, it adds extra e

Název v anglickém jazyce

Incorporation of system steady state properties into subspace identification algorithm

Popis výsledku anglicky

Most of the industrial applications are multiple-input multiple-output (MIMO) systems that can be identified using the knowledge of the system's physics or from measured data employing statistical methods. Currently, there is the only class of statistical identification methods capable of handling the issue of the vast MIMO systems - subspace identification methods. These methods, however, as all the statistical methods, need data of a certain quality, i.e., excitation of the corresponding order, no data corruption, etc. Nevertheless, combination of the statistical methods and a physical knowledge of the system could significantly improve system identification. This paper presents a new algorithm which provides remedy to the insufficient data quality of a certain kind through incorporation of the prior information, namely a known static gain and an input-output feed-through. The presented algorithm naturally extends classical subspace identification algorithms, that is, it adds extra e

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

BC - Teorie a systémy řízení

OECD FORD obor

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Projekt

<a href="/cs/project/2A-1TP1%2F084" target="_blank" >2A-1TP1/084: *Integrace systémů budov, výzkum a aplikace inteligentních algoritmů ovlivňujících spotřeby energií budov a obytných domů.</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2012

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

International Journal of Modelling, Identification and Control

ISSN

1746-6172

e-ISSN

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Svazek periodika

16

Číslo periodika v rámci svazku

2

Stát vydavatele periodika

CH - Švýcarská konfederace

Počet stran výsledku

19

Strana od-do

149-167

Kód UT WoS článku

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EID výsledku v databázi Scopus

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