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A Method for Non-linear Modelling Based on the Capabilities of PSO and GA Algorithms

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Artificial Intelligence and Soft Computing (ICAISC 2017)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10246))

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Abstract

The most nonlinear dynamic objects have their Approximate Nonlinear Model (ANM). Their parameters are known or can be determined by one of the typical identification procedures. The model obtained in this way describes well the main features of the identified dynamic object only in some Operating Point (OP). In this approach we use hybrid model increasing accuracy of the modeling. The hybrid model is composed of two parts: base ANM and Takagi-Sugeno (TS) fuzzy system. A Particle Swarm Optimization with Genetic Algorithm (PSO-GA) was used for identification of the parameters of the ANM and TS fuzzy system. An important advantage of the proposed approach is the obtained characteristics of the unknown parameters of the ANM described by the Fuzzy Rules (FR) of the TS fuzzy system. They provide the valuable knowledge for the experts about the nature of the unknown phenomena.

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Acknowledgment

The project was financed by the National Science Centre (Poland) on the basis of the decision number DEC-2012/05/B/ST7/02138. Also, this publication was made possible by NPRP grant #8-274-2-107 from the Qatar National Research Fund (a member of Qatar Foundation).

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Authors and Affiliations

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

    Piotr Dziwiński & Łukasz Bartczuk

  2. Texas A&M University at Qatar, Doha, Qatar

    Huang Tingwen

Authors
  1. Piotr Dziwiński
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  2. Łukasz Bartczuk
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  3. Huang Tingwen
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Corresponding author

Correspondence to Piotr Dziwiński .

Editor information

Editors and Affiliations

  1. Częstochowa University of Technology, Częstochowa, Poland

    Leszek Rutkowski

  2. Częstochowa University of Technology, Częstochowa, Poland

    Marcin Korytkowski

  3. Częstochowa University of Technology, Częstochowa, Poland

    Rafał Scherer

  4. AGH University of Science and Technology, Kraków, Poland

    Ryszard Tadeusiewicz

  5. University of California, Berkeley, California, USA

    Lotfi A. Zadeh

  6. University of Louisville, Louisville, Kentucky, USA

    Jacek M. Zurada

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Dziwiński, P., Bartczuk, Ł., Tingwen, H. (2017). A Method for Non-linear Modelling Based on the Capabilities of PSO and GA Algorithms. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L., Zurada, J. (eds) Artificial Intelligence and Soft Computing. ICAISC 2017. Lecture Notes in Computer Science(), vol 10246. Springer, Cham. https://doi.org/10.1007/978-3-319-59060-8_21

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  • DOI: https://doi.org/10.1007/978-3-319-59060-8_21

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