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Master's Dissertation
DOI
https://doi.org/10.11606/D.18.2007.tde-26102007-184742
Document
Author
Full name
Roberto Santos Inoue
E-mail
Institute/School/College
Knowledge Area
Date of Defense
Published
São Carlos, 2007
Supervisor
Committee
Terra, Marco Henrique (President)
Borges, Geovany Araújo
Bueno, Samuel Siqueira
Title in Portuguese
Controle robusto de robôs móveis com rodas
Keywords in Portuguese
Controle adaptativo
Controle robusto
Modelo fuzzy Takagi-Sugeno
Redes neurais
Robôs móveis com rodas
Abstract in Portuguese
Nesta dissertação é apresentado um estudo comparativo entre seis controladores H 'infinito' não lineares aplicados em um robô móvel com rodas. Três estratégias de controle são avaliadas. Na primeira, o modelo do robô é considerado completamente conhecido. Na segunda, o modelo matemático é considerado desconhecido e é realizada uma estimativa baseada em métodos inteligentes. E finalmente, na terceira estratégia, o modelo nominal é conhecido e técnicas inteligentes são usadas para estimar somente incertezas paramétricas do robô. As técnicas inteligentes usadas são baseadas em redes neurais e em lógica fuzzy. Esses controladores são resolvidos através de desigualdades matriciais lineares (DMLs) e equações algébricas de Riccati. Todos os resultados obtidos são baseados em dados experimentais.
Title in English
Robust control applied to a wheeled mobile robot
Keywords in English
Adaptive control
Robust control
Wheeled mobile robot
Abstract in English
This dissertation is present a comparative study between six nonlinear H 'infinity' controllers applied to a wheeled mobile robot. Three control strategies are adopted. In the first, the model of the robot is considered completely known. In the second, the mathematical model is considered unknown and is accomplished an estimate based on intelligent methods. And finally, in the third strategy, the nominal model is known and intelligent techniques are used only to estimate parametric uncertainties of the robot. The intelligent techniques used are based in neural networks and in fuzzy logic. These controllers are solved via linear matrix inequalities (LMIs) and algebraic Riccati equations. All results obtained are based in experimental data.
 
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dissertacao.pdf (1.77 Mbytes)
Publishing Date
2007-11-01
 
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