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
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;
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
DOI :
10.1109/ISIE.2007.4374766