In many practical structural applications, unknown states, inputs and parameters are
present. However, most methods require one or more of these variables to be known in …

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 …

This paper presents a novel algorithm for joint input-state-parameter estimation in structural
dynamics. The algorithm is derived from an existing smoothing algorithm. In each time step …

A successive Bayesian filtering framework for addressing the joint input-state-parameter
estimation problem is proposed in this study. Following the notion of analytical, rather than …

The classical Kalman filter (KF) provides a practical and efficient state estimation approach
for structural identification and vibration control. However, the classical KF approach is …

Abstract The traditional Extended Kalman filter (EKF) is a useful tool for structural parameter
identification with limited observations. It is, however, not applicable when the excitations on …

The problem of identification of stiffness, mass and damping properties of linear structural
systems, based on multiple sets of measurement data originating from static and dynamic …

A dual implementation of the Kalman filter is proposed for estimating the unknown input and
states of a linear state-space model by using sparse noisy acceleration measurements. The …

An algorithm is presented for jointly estimating the input and state of a structure from a
limited number of acceleration measurements. The algorithm extends an existing joint input …

This paper presents a joint input-state estimation algorithm that can be used for the
identification of forces applied to a structure and for the extrapolation of the measured data …