IDENTIFICATION OF STRUCTURAL PARAMETERS AND UNKNOWN EXCITATIONS BASED ON THE EXTENDED KALMAN FILTER

Abstract

The classical extended Kalman filter (EKF) method is capable of accurately identifying structural parameters with known external excitations. However, in some practical situations, the excitations are difficult or impossible to measure. A time-domain approach based on EKF is proposed in this paper for the simultaneous identification of structural parameters and unknown inputs. A projection matrix is introduced in the observation equation, based on which the structural parameters are identified. The unknown inputs are determined by means of least squares estimation using the estimated parameters. The effectiveness and robustness of the proposed approach is verified through three numerical examples including a four-story benchmark model, a piecewise linear structure and a Duffing hysteretic structure. The numerical results show that the proposed approach can not only accurately identify the parameters of linear and nonlinear structures, but also satisfactorily estimate the unknown external excitations.