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Complexity Reduction in Fuzzy Systems Using Functional Principal Component Analysis

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Fuzzy Modeling and Control: Theory and Applications

Part of the book series: Atlantis Computational Intelligence Systems ((ATLANTISCIS,volume 9))

Abstract

The ability to build fuzzy logic applications for control problems has been hindered by well-known problem of combinatorial rules explosion, causing complexity in modeling

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Acknowledgments

Part of the work was supported by the project DPI2010-21589-C05-01 of the Spanish Ministry of Economy and Competitiveness.

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Authors and Affiliations

  1. Nimbus Centre, Cork Institute of Technology, Cork, Ireland

    Juan Manuel Escaño

  2. Department of Systems Engineering and Automatic Control, University of Seville, Seville, Spain

    Carlos Bordons

Authors
  1. Juan Manuel Escaño
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  2. Carlos Bordons
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Correspondence to Juan Manuel Escaño .

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Editors and Affiliations

  1. Center for Automation and Robotics, Universidad Politécnica de Madrid— Consejo Superior de Investigaciones Científicas (UPM—CSIC), Madrid, Madrid, Spain

    Fernando Matía

  2. DPolytechnic School of Engineering, Universidad de La Laguna, La Laguna, Sta. Cruz Tenerife, Spain

    G. Nicolás Marichal

  3. Universidad de La RiojaDepartamento de Ingeniería Eléctrica, Universidad de La Rioja, La Rioja, Navarra, Spain

    Emilio Jiménez

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Escaño, J.M., Bordons, C. (2014). Complexity Reduction in Fuzzy Systems Using Functional Principal Component Analysis. In: Matía, F., Marichal, G., Jiménez, E. (eds) Fuzzy Modeling and Control: Theory and Applications. Atlantis Computational Intelligence Systems, vol 9. Atlantis Press, Paris. https://doi.org/10.2991/978-94-6239-082-9_3

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  • DOI: https://doi.org/10.2991/978-94-6239-082-9_3

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  • Publisher Name: Atlantis Press, Paris

  • Print ISBN: 978-94-6239-081-2

  • Online ISBN: 978-94-6239-082-9

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