On the Identification of Hysteretic Systems, Part II: Bayesian Sensitivity Analysis

Abstract

This paper forms the second in a short sequence considering the system identification problem for hysteretic systems. The basic model for parameter estimation is assumed to be the Bouc-Wen model, as this has proved particularly versatile in the past. Previous work on the Bouc-Wen system has shown that the system response is more sensitive to some parameters than others and that the errors in the associated parameter estimates vary as a consequence. The objective of the current paper is to demonstrate the use of a principled Bayesian approach to parameter sensitivity analysis for the Bouc-Wen system. The approach is based on Gaussian process emulation and is encoded in the software package Gem-SA. The paper considers a fiveparameter Bouc-Wen model, and the sensitivity analysis is based on data generated by computer simulation of a single-degree-of-freedom system.KeywordsHysteresisthe Bouc-Wen modelsystem identificationuncertainty analysisBayesian sensitivity analysis