• DocumentCode
    1976701
  • Title

    Markov Chain Monte Carlo Bayesian Analysis of the Nonlinear Characteristic of a Three-Phase Alternator

  • Author

    Aguirre, G. ; Uriondo, F. ; Hernández, J.R.

  • Author_Institution
    Univ. of Basque Country, Bilbao
  • fYear
    2007
  • fDate
    4-7 June 2007
  • Firstpage
    1183
  • Lastpage
    1188
  • Abstract
    We have applied the methods of the Bayesian probability theory as an alternative to the Potier´s triangle construction to rigorously analyze the nonlinear characteristics of a saturated alternator. This analysis comprises the choice of the prior probabilities, the setting up of the models, the calculation of multidimensional integrals with MCMC sampling methods as implemented in the winBUGS software and the discussion of the results. Our objectives have been to clearly illustrate the main advantages of the method: first, its ability to take into account all the cogent information previously available about a given problem; second, the parameter estimation feature and, third, the possibility of performing a true model comparison.
  • Keywords
    Bayes methods; Markov processes; Monte Carlo methods; alternators; parameter estimation; probability; Bayesian probability theory; Markov chain Monte Carlo Bayesian analysis; Potier´s triangle construction; multidimensional integrals; nonlinear characteristic; parameter estimation; three-phase alternator; winBUGS software; Alternators; Bayesian methods; Circuit simulation; Equivalent circuits; Monte Carlo methods; Multidimensional systems; Parameter estimation; Power electronics; Probability; Sampling methods;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Electronics, 2007. ISIE 2007. IEEE International Symposium on
  • Conference_Location
    Vigo
  • Print_ISBN
    978-1-4244-0754-5
  • Electronic_ISBN
    978-1-4244-0755-2
  • Type

    conf

  • DOI
    10.1109/ISIE.2007.4374766
  • Filename
    4374766