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 …

The problem of combined state and input estimation of linear structural systems based on
measured responses and a priori knowledge of structural model is considered. A novel …

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 …

In this study, a novel dual implementation of the Kalman filter proposed by Eftekhar Azam et
al.(2014, 2015) is experimentally validated for simultaneous estimation of the states and …

A methodology is proposed to update mechanics-based nonlinear finite element (FE)
models of civil structures subjected to unknown input excitation. The approach allows to …

This work proposes an augmented extended Kalman filter based state-input estimator for
mechanical systems defined by implicit equations of motion which is then applied to …

The need to perform dynamic response reconstruction always arises as the measurement of
structural response is often limited to a few locations, especially for a large civil structure …

The direct measurement of the external loads acting on a mechanical component represents
often a challenge in many engineering applications. In this context, the attention of many …

This paper presents a general framework for estimating the state and unknown inputs at the
level of a system subdomain using a limited number of output measurements, enabling thus …

This paper presents a verification of a joint input-state estimation algorithm using data
obtained from in situ experiments on a footbridge. The estimation of the input and the system …