Design of Advanced Targeting Cost Function for Evolutionary Optimization of Chaos Control

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F70883521%3A28140%2F09%3A63507982" target="_blank" >RIV/70883521:28140/09:63507982 - 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

Design of Advanced Targeting Cost Function for Evolutionary Optimization of Chaos Control

Popis výsledku v původním jazyce

This research deals with the optimization of the control of chaos by means of evolutionary algorithms. The main aim of this work is to show that powerful optimizing tools like evolutionary algorithms can in reality be used for the optimization of deterministic chaos control. This work is aimed on an explanation of how to use evolutionary algorithms (EAs) and how to properly define the advanced targeting cost function (CF) securing very fast and precise stabilization of desired state for any initial conditions. As a model of deterministic chaotic system, the two dimensional Henon map was used. The evolutionary algorithm Self-Organizing Migrating Algorithm (SOMA) was used in four versions. For each version, repeated simulations were conducted to outlinethe effectiveness and robustness of used method and targeting CF.

Název v anglickém jazyce

Design of Advanced Targeting Cost Function for Evolutionary Optimization of Chaos Control

Popis výsledku anglicky

This research deals with the optimization of the control of chaos by means of evolutionary algorithms. The main aim of this work is to show that powerful optimizing tools like evolutionary algorithms can in reality be used for the optimization of deterministic chaos control. This work is aimed on an explanation of how to use evolutionary algorithms (EAs) and how to properly define the advanced targeting cost function (CF) securing very fast and precise stabilization of desired state for any initial conditions. As a model of deterministic chaotic system, the two dimensional Henon map was used. The evolutionary algorithm Self-Organizing Migrating Algorithm (SOMA) was used in four versions. For each version, repeated simulations were conducted to outlinethe effectiveness and robustness of used method and targeting CF.

Druh

D - Stať ve sborníku

CEP obor

IN - Informatika

OECD FORD obor

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Projekt

<a href="/cs/project/GA102%2F09%2F1680" target="_blank" >GA102/09/1680: Evoluční návrh řídicích algoritmů</a><br>

Návaznosti

Z - Vyzkumny zamer (s odkazem do CEZ)

Rok uplatnění

2009

Kód důvěrnosti údajů

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

Název statě ve sborníku

23rd European Conference on Modelling and Simulation

ISBN

978-0-9553018-8-9

ISSN

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e-ISSN

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Počet stran výsledku

7

Strana od-do

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Název nakladatele

ECMS Sp.

Místo vydání

Madrid

Místo konání akce

Madrid, Spain

Datum konání akce

12. 6. 2009

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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