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Advance Trends in Soft Computing pp 293–300Cite as

Takagi-Sugeno Approximation of a Mamdani Fuzzy System

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Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 312))

Abstract

In the present paper we construct a higher order Takagi-Sugeno fuzzy system that approximates a Mamdani fuzzy system, with arbitrary accuracy. The goal of this construction is to reduce the computational complexity of a fuzzy systems considered, also to replace a nonlinear operator by an approximate linear operator. The proposed methodology is fully constructive, so it does not require training of the Takagi-Sugeno fuzzy system. The construction combines Takagi-Sugeno systems with the classical Lagrange interpolation.

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Author information

Authors and Affiliations

  1. Department of Mathematics, DigiPen Institute of technology, 9931 Willows Rd. NE, Redmond, WA, 98052, USA

    Barnabas Bede

  2. Óbuda University, Bécsi út 96/B, H-1034, Budapest, Hungary

    Imre J. Rudas

Authors
  1. Barnabas Bede
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  2. Imre J. Rudas
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Corresponding author

Correspondence to Barnabas Bede .

Editor information

Editors and Affiliations

  1. The University of Texas, San Antonio, Texas, USA

    Mo Jamshidi

  2. Department of Computer Science, University of Texas at El Paso, El Paso, Texas, USA

    Vladik Kreinovich

  3. Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland

    Janusz Kacprzyk

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Bede, B., Rudas, I.J. (2014). Takagi-Sugeno Approximation of a Mamdani Fuzzy System. In: Jamshidi, M., Kreinovich, V., Kacprzyk, J. (eds) Advance Trends in Soft Computing. Studies in Fuzziness and Soft Computing, vol 312. Springer, Cham. https://doi.org/10.1007/978-3-319-03674-8_28

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  • DOI: https://doi.org/10.1007/978-3-319-03674-8_28

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-03673-1

  • Online ISBN: 978-3-319-03674-8

  • eBook Packages: EngineeringEngineering (R0)

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