An architecture for fuzzy logic controllers evolution and learning in microcontrollers based environments

The growing number of control models based on combinations of neural networks, fuzzy systems and evolutionary algorithms shows that they represent a flexible and powerful approach. However, most of these models assume that there is enough CPU power for the evolutionary and learning algorithms, which...

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Detalles Bibliográficos
Autores principales: Kavka, Carlos, Roggero, Patricia, Apolloni, Javier
Formato: Objeto de conferencia
Lenguaje:Inglés
Publicado: 2003
Materias:
Ciencias Informáticas
Neural nets
Algorithms
Environments
Learning
ARTIFICIAL INTELLIGENCE
Intelligent agents
neural networks
evolutionary algorithms
fuzzy systems
control
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/22747
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-22747
record_format dspace
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Ciencias Informáticas
Neural nets
Algorithms
Environments
Learning
ARTIFICIAL INTELLIGENCE
Intelligent agents
neural networks
evolutionary algorithms
fuzzy systems
control
spellingShingle Ciencias Informáticas
Neural nets
Algorithms
Environments
Learning
ARTIFICIAL INTELLIGENCE
Intelligent agents
neural networks
evolutionary algorithms
fuzzy systems
control
Kavka, Carlos
Roggero, Patricia
Apolloni, Javier
An architecture for fuzzy logic controllers evolution and learning in microcontrollers based environments
topic_facet Ciencias Informáticas
Neural nets
Algorithms
Environments
Learning
ARTIFICIAL INTELLIGENCE
Intelligent agents
neural networks
evolutionary algorithms
fuzzy systems
control
description The growing number of control models based on combinations of neural networks, fuzzy systems and evolutionary algorithms shows that they represent a flexible and powerful approach. However, most of these models assume that there is enough CPU power for the evolutionary and learning algorithms, which in a large number of cases is an unrealistic assumption. It is usual that the control tasks are performed by small microcontrollers, which are very near to or embedded in the plant, with low power, low cost and dedicated to a single task. This work proposes an architecture for evolution and learning in adaptive control, specifically designed to operate in microcontrollers based environments. An evaluation on a simulated temperature control environment is provided, together with details on the current hardware implementation.
format Objeto de conferencia
Objeto de conferencia
author Kavka, Carlos
Roggero, Patricia
Apolloni, Javier
author_facet Kavka, Carlos
Roggero, Patricia
Apolloni, Javier
author_sort Kavka, Carlos
title An architecture for fuzzy logic controllers evolution and learning in microcontrollers based environments
title_short An architecture for fuzzy logic controllers evolution and learning in microcontrollers based environments
title_full An architecture for fuzzy logic controllers evolution and learning in microcontrollers based environments
title_fullStr An architecture for fuzzy logic controllers evolution and learning in microcontrollers based environments
title_full_unstemmed An architecture for fuzzy logic controllers evolution and learning in microcontrollers based environments
title_sort architecture for fuzzy logic controllers evolution and learning in microcontrollers based environments
publishDate 2003
url http://sedici.unlp.edu.ar/handle/10915/22747
work_keys_str_mv AT kavkacarlos anarchitectureforfuzzylogiccontrollersevolutionandlearninginmicrocontrollersbasedenvironments
AT roggeropatricia anarchitectureforfuzzylogiccontrollersevolutionandlearninginmicrocontrollersbasedenvironments
AT apollonijavier anarchitectureforfuzzylogiccontrollersevolutionandlearninginmicrocontrollersbasedenvironments
AT kavkacarlos architectureforfuzzylogiccontrollersevolutionandlearninginmicrocontrollersbasedenvironments
AT roggeropatricia architectureforfuzzylogiccontrollersevolutionandlearninginmicrocontrollersbasedenvironments
AT apollonijavier architectureforfuzzylogiccontrollersevolutionandlearninginmicrocontrollersbasedenvironments
bdutipo_str Repositorios
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