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Discovering the dynamic behavior of unknown systems using fuzzy logic

Author

Listed:
  • A. Javier Barragán

    (Universidad de Huelva)

  • Juan M. Enrique

    (Universidad de Huelva)

  • Antonio J. Calderón

    (Universidad de Extremadura)

  • José M. Andújar

    (Universidad de Huelva)

Abstract

To know the dynamic behavior of a system it is convenient to have a good dynamic model of it. However, in many cases it is not possible either because of its complexity or because of the lack of knowledge of the laws involved in its operation. In these cases, obtaining models from input–output data is shown as a highly effective technique. Specifically, intelligent modeling techniques have become important in recent years in this field. Among these techniques, fuzzy logic is especially interesting because it allows to incorporate to the model the knowledge that is possessed of the system, besides offering a more interpretable model than other techniques. A fuzzy model is, formally speaking, a mathematical model. Therefore, this model can be used to analyze the original system using known systems analysis techniques. In this paper a methodology for extract information from unknown systems using fuzzy logic is presented. More precisely, it is presented the exact linearization of a Takagi–Sugeno fuzzy model with no restrictions in use or distribution of its membership functions, as well as obtaining its equilibrium states, the study of its local behavior and the search for periodic orbits by the application of Poincaré.

Suggested Citation

  • A. Javier Barragán & Juan M. Enrique & Antonio J. Calderón & José M. Andújar, 2018. "Discovering the dynamic behavior of unknown systems using fuzzy logic," Fuzzy Optimization and Decision Making, Springer, vol. 17(4), pages 421-445, December.
    • Handle: RePEc:spr:fuzodm:v:17:y:2018:i:4:d:10.1007_s10700-018-9285-4
    DOI: 10.1007/s10700-018-9285-4
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    References listed on IDEAS

    as
    1. J. Grande & Jose Andújar & Javier Aroba & Rafael Beltrán & Maria de la Torre & Juan Cerón & T. Gómez, 2010. "Fuzzy Modeling of the Spatial Evolution of the Chemistry in the Tinto River (SW Spain)," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 24(12), pages 3219-3235, September.
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    Cited by:

    1. Hadi Vatankhah Ghadim & Mehrdad Tarafdar Hagh & Saeid Ghassem Zadeh, 2023. "Fermat-curve based fuzzy inference system for the fuzzy logic controller performance optimization in load frequency control application," Fuzzy Optimization and Decision Making, Springer, vol. 22(4), pages 555-586, December.

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