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Fuzzy Modeling and Control: Theory and Applications pp 191–204Cite as

Neuro-Fuzzy Modeling and Fuzzy Control of a Fast Ferry

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

Abstract

Intelligent control achieves automation via the emulation of biological intelligence. It either seeks to replace a human who performs a control task (e.g., a chemical process operator) or it borrows ideas from how biological systems solve problems and applies them to the solution of control problems (e.g., the use of neural networks for control) (Passino 2001; Santos 2011).

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Acknowledgments

Author would like to thank the support of the CICYT DPI2009-14552-C02-01 project and the collaboration of the CEHIPAR staff.

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Authors and Affiliations

  1. Computer Architecture and Automatic Control Department, Universidad Complutense de Madrid, Madrid, Spain

    Matilde Santos

Authors
  1. Matilde Santos
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Correspondence to Matilde Santos .

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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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Santos, M. (2014). Neuro-Fuzzy Modeling and Fuzzy Control of a Fast Ferry. 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_10

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  • DOI: https://doi.org/10.2991/978-94-6239-082-9_10

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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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