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Structural system identification via synchronization technique and fuzzy logic

Author

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  • Zand, Behnam
  • Ghaderi, Pedram
  • Amini, Fereidoun

Abstract

In this paper, a new approach is proposed for parameter identification in seismically excited structures based on synchronization method and fuzzy logic. The main contribution of this paper is providing a general solution for the estimation of the identifier coefficients using fuzzy logic. These identifier coefficients adjust the convergence rate and accuracy of the identification. The fuzzy controller uses triangular membership functions as input and output. The input parameters to the fuzzy controller are functions of displacement and velocity of the top story subjected to earthquake excitation. By using appropriate fuzzy rules the results are obtained for identifier coefficients. Additionally, a novel and simple formulation to identify structural unknown parameters based on synchronization is presented. The performance of the proposed approach is investigated using different shear frames under various excitations. The sensitivity of the proposed method to different noise levels and modeling uncertainties is analyzed. Numerical examples indicate that the presented method can identify the unknown parameters of the structure with high accuracy and reasonable computational time.

Suggested Citation

  • Zand, Behnam & Ghaderi, Pedram & Amini, Fereidoun, 2023. "Structural system identification via synchronization technique and fuzzy logic," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 203(C), pages 174-188.
    • Handle: RePEc:eee:matcom:v:203:y:2023:i:c:p:174-188
    DOI: 10.1016/j.matcom.2022.06.009
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    References listed on IDEAS

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    1. Chou, Jyh-Horng & Sun, Jung-Hung & Shieh, Jyh-Nan, 2003. "On-line identification and optimal control of continuous-time systems," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 63(6), pages 493-503.
    2. Chassiakos, Anastassios G. & Masri, Sami F., 1996. "Identification of structural systems by neural networks," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 40(5), pages 637-656.
    3. Hassan A. Yousef & Mohamed Hamdy & Kyrillos Nashed, 2017. "Adaptive fuzzy controller for a class of nonlinear systems with unknown backlash-like hysteresis," International Journal of Systems Science, Taylor & Francis Journals, vol. 48(12), pages 2522-2533, September.
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    Cited by:

    1. Juan J. Font & Sergio Macario & Manuel Sanchis, 2023. "Endograph Metric and a Version of the Arzelà–Ascoli Theorem for Fuzzy Sets," Mathematics, MDPI, vol. 11(2), pages 1-8, January.

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