A Genetic Approach to the Automatic Generation of Fuzzy Control Systems from Numerical Controllers

  • Authors:
  • Giuseppe Penna;Francesca Fallucchi;Benedetto Intrigila;Daniele Magazzeni

  • Affiliations:
  • Department of Computer Science, University of L'Aquila, Italy;DISP, University of Roma "Tor Vergata", Italy;Department of Mathematics, University of Roma "Tor Vergata", Italy;Department of Computer Science, University of L'Aquila, Italy

  • Venue:
  • AI*IA '07 Proceedings of the 10th Congress of the Italian Association for Artificial Intelligence on AI*IA 2007: Artificial Intelligence and Human-Oriented Computing
  • Year:
  • 2007

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Abstract

Control systems are small components that control the behavior of larger systems. In the last years, sophisticated controllers have been widely used in the hardware/software embedded systemscontained in a growing number of everyday products and appliances. Therefore, the problem of the automatic synthesis of controllers is extremely important. To this aim, several techniques have been applied, like cell-to-cell mapping, dynamic programmingand, more recently, model checking. The controllers generated using these techniques are typically numerical controllersthat, however, often have a huge size and not enough robustness. In this paper we present an automatic iterative process, based on genetic algorithms, that can be used to compress the huge information contained in such numerical controllers into smaller and more robust fuzzy control systems.