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Interval Type-2 Fuzzy Logic for Hybrid Intelligent Control

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On Fuzziness

Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 298))

Abstract

We provide in this paper a short review of my research work on developing new methods for building intelligent control systems using type-2 fuzzy logic and soft computing techniques. Soft Computing (SC) consists of several computing paradigms, including fuzzy logic, neural networks, and genetic algorithms, which can be used to create powerful hybrid intelligent systems. Combining type-2 fuzzy logic with traditional SC techniques powerful hybrid intelligent systems can be built for solving complex control problems.

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References

  1. Castillo, O., Melin, P.: Soft Computing for Control of Non-Linear Dynamical Systems. Springer, Heidelberg (2001)

    Book  MATH  Google Scholar 

  2. Castillo, O., Melin, P.: Soft Computing and Fractal Theory for Intelligent Manufacturing. Physica-Verlag, Heidelberg (2003)

    Book  MATH  Google Scholar 

  3. Castillo, O., Melin, P.: Type-2 Fuzzy Logic: Theory and Applications, vol. 223. Springer, Heidelberg (2008)

    MATH  Google Scholar 

  4. Melin, P., Castillo, O.: Modelling, Simulation and Control of Non-Linear Dynamical Systems. Springer, Heidelberg (2002)

    Google Scholar 

  5. Castillo, O.: Type-2 Fuzzy Logic in Intelligent Control Applications. Springer, Heidelberg (2012)

    Book  MATH  Google Scholar 

  6. Melin, P., Castillo, O.: Hybrid Intelligent Systems for Pattern Recognition. Springer, Heidelberg (2005)

    MATH  Google Scholar 

  7. Zadeh, L.A.: Fuzzy Logic = Computing with Words. IEEE Transactions on Fuzzy Systems 4(2), 103 (1996)

    Article  MathSciNet  Google Scholar 

  8. Zadeh, L.A.: Knowledge Representation in Fuzzy Logic. IEEE Transactions on Knowledge Data Engineering 1, 89 (1989)

    Article  Google Scholar 

  9. Zadeh, L.A.: Fuzzy Logic. Computer 1(4), 83–93 (1998)

    Google Scholar 

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Castillo, O. (2013). Interval Type-2 Fuzzy Logic for Hybrid Intelligent Control. In: Seising, R., Trillas, E., Moraga, C., Termini, S. (eds) On Fuzziness. Studies in Fuzziness and Soft Computing, vol 298. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35641-4_14

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  • DOI: https://doi.org/10.1007/978-3-642-35641-4_14

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-35640-7

  • Online ISBN: 978-3-642-35641-4

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