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Inicio Revista Iberoamericana de Automática e Informática Industrial RIAI Hibridación de sistemas borrosos para el modelado y control
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Vol. 11. Núm. 2.
Páginas 127-141 (abril - julio 2014)
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Vol. 11. Núm. 2.
Páginas 127-141 (abril - julio 2014)
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Hibridación de sistemas borrosos para el modelado y control
Hybridization of fuzzy systems for modeling and control
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José Manuel Andújar1,
Autor para correspondencia
andujar@diesia.uhu.es

Autor para correspondencia.
, Antonio Javier Barragán
Dep. de Ing. Electrónica, de Sistemas Electrónicos y Automática, Universidad de Huelva
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La lógica borrosa ha conseguido en un breve periodo de tiempo revolucionar la tecnología mediante la conjunción de los fundamentos matemáticos, la lógica y el razonamiento. Su inherente capacidad de hibridación y su robustez intrínseca han permitido a la lógica borrosa cosechar numerosos éxitos en el campo del modelado y el control de sistemas, impulsando el control inteligente. En este artículo se estudian los sistemas borrosos híbridos más usuales y su importancia en el campo del modelado y control de sistemas dinámicos. El trabajo presenta varios ejemplos que ilustran, para diferentes técnicas de hibridación, cómo éstas potencian las cualidades innatas de la lógica borrosa para el modelado y control de sistemas dinámicos. Así mismo, se incluyen más de ciento cincuenta referencias bibliográficas que permitirán al lector interesado profundizar en el campo de la lógica borrosa, y más concretamente en el de sus técnicas de hibridación con aplicación al modelado y control borroso.

Palabras clave:
Algoritmos bioinspirados
control borroso
control inteligente
modelado borroso
redes neuronales
sistemas borrosos
sistemas híbridos
Abstract

Fuzzy logic has revolutionized, in a short period of time, the technology through a combination of mathematical fundamentals, logic and reasoning. Its inherent hybridization ability and intrinsic robustness, have allowed to fuzzy logic get numerous successes in the field of modeling and control of systems, impulsing the intelligent control. In this paper, the more usual hybrid fuzzy systems and its importance in the field of modeling and control of dynamic systems are studied. The paper presents several examples that illustrate, for different hybridization techniques, how these enhance the innate qualities of fuzzy logic for modeling and control of dynamic systems. Also, more than a hundred and fifty references are included, which allow the interested reader to delve into the field of fuzzy logic, and more specifically, in its hybridization techniques with application to modeling and fuzzy control.

Keywords:
Bioinspired algorithms fuzzy control fuzzy modeling fuzzy systems hybrid systems intelligent control neuronal networks
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