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Tuning Fuzzy Control Rules via Genetic Algorithms: An Experimental Evaluation

Author Affiliations

  • 1Departamento de Ingeniería Industrial-Programa ingenieríamecatrónica, Universidad de Sonora, Unidad Regional Centro, Hermosillo, Sonora,MÉXICO
  • 2 Facultad De Ingeniería Universidad Autónoma De Campeche, Campeche, Campeche, MÉXICO
  • 3 Facultad de Ingeniería Campus Mexicali, Universidad Autónoma de baja California, Mexicali, Baja California, MÉXICO

Res. J. Recent Sci., Volume 2, Issue (10), Pages 81-87, October,2 (2013)

Abstract

In this article, a simple genetic algorithm is used to solve an optimization problem that minimizes an objective function, with the purpose of obtaining the rule base of a fuzzy controller. The plant under consideration is an experimental direct current servosystem. The variable to be controlled is the load angular position. The objective function used here is the criterion IAE (Integrated Absolute Error). The genetic algorithm operates with populations who respond to consequents of the rule base.

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