Identification of Bouc-Wen type models using the Transitional Markov Chain Monte Carlo method

@inproceedings{Ortiz2015IdentificationOB,
  title={Identification of Bouc-Wen type models using the Transitional Markov Chain Monte Carlo method},
  author={Gilberto A. Ortiz and Diego {\'A}lvarez and Daniel Bedoya-Ru{\'i}z},
  year={2015}
}
  • Gilberto A. Ortiz, Diego Álvarez, Daniel Bedoya-Ruíz
  • Published 2015
  • Computer Science
  • The Transitional Markov Chain Monte Carlo method is applied.Identification of the distribution of the parameters are found.The methodology is evaluated with simulated and experimental data with good results.The method provides a very accurate estimation of the response of the system.The method reveals the multi-modality of the Bouc-Wen-Baber-Noori hysteresis model. Bayesian model updating techniques are becoming the standard tool for the identification of nonlinear dynamical systems, because… CONTINUE READING

    Create an AI-powered research feed to stay up to date with new papers like this posted to ArXiv

    Citations

    Publications citing this paper.
    SHOWING 1-10 OF 12 CITATIONS

    Bayesian Frameworks for Probabilistic System Identification of Structural Parameters

    VIEW 2 EXCERPTS
    CITES METHODS
    HIGHLY INFLUENCED

    Identification for Bouc-Wen hysteresis system with hopfield neural network

    • Gao Xuehui, Sun Bo
    • Computer Science
    • 2017 9th International Conference on Modelling, Identification and Control (ICMIC)
    • 2017
    VIEW 3 EXCERPTS
    CITES METHODS