Constrained Kalman Filter for Nonlinear Structural Identification

Abstract

It is well known that hysteresis is a principal source of internal energy dissipation in structural systems. One of the widely accepted hysteretic models for structures is a differential model, called the modified Bouc-Wen model. In this paper, a constrained Kalman filter with a global weighted iteration strategy has been used to estimate the parameters in the modified Bouc-Wen model. An actual seismic signal was used to excite a nonlinear structural system described by the modified Bouc-Wen model that has both degradation and pinching characteristics. The convergence results show that, for both clean and noise-corrupted data, this algorithm is effective in estimating all the 11 parameters with satisfactory precision and fast convergence. As this algorithm has modest computing requirements, it should be acceptable as a basic tool for estimating hysteretic parameters in engineering design.