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New Method for Nonlinear Fuzzy Correction Modelling of Dynamic Objects

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Artificial Intelligence and Soft Computing (ICAISC 2014)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8467))

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Abstract

In the paper a method to use the equivalent linearization technique of the nonlinear state equation with the coefficients generated by the fuzzy rules for current operating point is proposed. On the basis of the evolutionary strategy and properly defined identification procedure, the fuzzy rules are automatically designed to maximize the accuracy of the resulting linear model.

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Author information

Authors and Affiliations

  1. Institute of Computational Intelligence, Czȩstochowa University of Technology, Poland

    Łukasz Bartczuk & Andrzej Przybył

  2. Institute of Control and System Research, Bulgarian Academy of Sciences, Bulgaria

    Petia Koprinkova-Hristova

Authors
  1. Łukasz Bartczuk
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  2. Andrzej Przybył
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  3. Petia Koprinkova-Hristova
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Editor information

Editors and Affiliations

  1. Częstochowa University of Technology, Armii Krajowej 36, 42-200, Częstochowa, Poland

    Leszek Rutkowski , Marcin Korytkowski  & Rafał Scherer ,  & 

  2. AGH University of Science and Technology, Mickiewicza 30, 30-059, Kraków, Poland

    Ryszard Tadeusiewicz

  3. Computer Science Division, Department of Electrical Engineering and Computer Sciences, University of California Berkeley, 94720-1776, Berkeley, CA, USA

    Lotfi A. Zadeh

  4. Computational Intelligence Laboratory, Electrical and Computer Engineering, University of Louisville, 405 Lutz Hall, 40292, Louisville, KY, USA

    Jacek M. Zurada

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Bartczuk, Ł., Przybył, A., Koprinkova-Hristova, P. (2014). New Method for Nonlinear Fuzzy Correction Modelling of Dynamic Objects. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds) Artificial Intelligence and Soft Computing. ICAISC 2014. Lecture Notes in Computer Science(), vol 8467. Springer, Cham. https://doi.org/10.1007/978-3-319-07173-2_16

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  • DOI: https://doi.org/10.1007/978-3-319-07173-2_16

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