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Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F06%3A03119471" target="_blank" >RIV/68407700:21230/06:03119471 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Recursive Subspace Identification in the Least Squares Framework

Popis výsledku v původním jazyce

In the recent years Subspace identification methods proved to be efficient for industrial applications, due to their good properties, such as: same complexity of identification for single input/output and multiple input/output systems, direct state spacemodel identification, numerical robustness (QR and SVD factorization) and implicit model order reduction. The algorithms are well developed for off-line identification, however on-line recursive identification is still rather an open topic. The problemlies in the recursification of SVD, which is impossible and several approximations are used instead. We use a different approach, exploiting the fact, that 4SID methods minimizes implicit optimality criterion, which is mean square error of multi-step predictions of the model. The criterion allows for recursification in the least squares framework and prior knowledge incorporation. We also address the problem of non-causality, which was recently pointed out in 4SID methods.

Název v anglickém jazyce

Recursive Subspace Identification in the Least Squares Framework

Popis výsledku anglicky

In the recent years Subspace identification methods proved to be efficient for industrial applications, due to their good properties, such as: same complexity of identification for single input/output and multiple input/output systems, direct state spacemodel identification, numerical robustness (QR and SVD factorization) and implicit model order reduction. The algorithms are well developed for off-line identification, however on-line recursive identification is still rather an open topic. The problemlies in the recursification of SVD, which is impossible and several approximations are used instead. We use a different approach, exploiting the fact, that 4SID methods minimizes implicit optimality criterion, which is mean square error of multi-step predictions of the model. The criterion allows for recursification in the least squares framework and prior knowledge incorporation. We also address the problem of non-causality, which was recently pointed out in 4SID methods.

Druh

A - Audiovizuální tvorba

CEP obor

BC - Teorie a systémy řízení

OECD FORD obor

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Projekt

<a href="/cs/project/GA102%2F05%2F0271" target="_blank" >GA102/05/0271: Metody prediktivního řízení: algoritmy a implementace</a><br>

Návaznosti

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

Rok uplatnění

2006

Kód důvěrnosti údajů

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

ISBN

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Místo vydání

Praha

Název nakladatele resp. objednatele

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Verze

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Identifikační číslo nosiče

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