Dual adaptive control for non-minimum phase systems with functional uncertainties

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F13%3A43919235" target="_blank" >RIV/49777513:23520/13:43919235 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.3182/20130904-3-FR-2041.00126" target="_blank" >http://dx.doi.org/10.3182/20130904-3-FR-2041.00126</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3182/20130904-3-FR-2041.00126" target="_blank" >10.3182/20130904-3-FR-2041.00126</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Dual adaptive control for non-minimum phase systems with functional uncertainties

Popis výsledku v původním jazyce

A dual control for a nonlinear system with non-minimum phase based on the bicriterial approach is proposed and discussed. A particular class of the nonlinear input/output recursive model is composed of linear and nonlinear blocks, the latter being implemented with a multi-layered perceptron neural network. The unknown parameters of the model are estimated in real-time by the extended Kalman filter. The chosen nonlinear model with the affine structure in inputs together with the certainty equivalence principle utilization allow to obtain an analytical solution to control based on generalised minimum variance method. Behaviour of the system based on the enforcement of the certainty equivalence can negatively be affected, especially in a presence of disturbances and functional uncertainties. For that, the control action is enhanced about dual property based on the bicriterial approach that uses two separate criteria to introduce one of the opposing aspects between estimation and control.

Název v anglickém jazyce

Dual adaptive control for non-minimum phase systems with functional uncertainties

Popis výsledku anglicky

A dual control for a nonlinear system with non-minimum phase based on the bicriterial approach is proposed and discussed. A particular class of the nonlinear input/output recursive model is composed of linear and nonlinear blocks, the latter being implemented with a multi-layered perceptron neural network. The unknown parameters of the model are estimated in real-time by the extended Kalman filter. The chosen nonlinear model with the affine structure in inputs together with the certainty equivalence principle utilization allow to obtain an analytical solution to control based on generalised minimum variance method. Behaviour of the system based on the enforcement of the certainty equivalence can negatively be affected, especially in a presence of disturbances and functional uncertainties. For that, the control action is enhanced about dual property based on the bicriterial approach that uses two separate criteria to introduce one of the opposing aspects between estimation and control.

Druh

D - Stať ve sborníku

CEP obor

BC - Teorie a systémy řízení

OECD FORD obor

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Projekt

<a href="/cs/project/GAP103%2F11%2F1353" target="_blank" >GAP103/11/1353: Odhad stavu dynamických stochastických systémů</a><br>

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2013

Kód důvěrnosti údajů

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

Název statě ve sborníku

Proceeding of the 9th IFAC Symposium on Nonlinear Control Systems

ISBN

978-3-902823-47-2

ISSN

1474-6670

e-ISSN

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Počet stran výsledku

6

Strana od-do

815-820

Název nakladatele

International Federation of Automatic Control

Místo vydání

Toulouse

Místo konání akce

Toulouse, France

Datum konání akce

4. 9. 2013

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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