Parameter identification in explicit structural dynamics: performance of the extended Kalman filter Original Research Article

An extended Kalman filter (EKF) approach is adopted in this paper for structural systems subject to dynamic loadings to simultaneously estimate the state and calibrate constitutive parameters. To pursue this aim, after space and time discretizations a joint system state vector is introduced, gathering nodal displacements and constitutive parameters to be identified. Because of the linearization of the discretized equations governing filter updates, the EKF can lead to inaccurate model calibration. It is shown that, even though the state of the system is always followed with a high level of accuracy, unsatisfactory parameter estimations can be obtained in the case of degrading strength of the structure, that is in the case of softening. Both single degree-of-freedom (DOF) and multi-DOF dynamic systems are analyzed to detect the possible sources of this inaccuracy.