This article presents an up-to-date tutorial review of nonlinear Bayesian estimation. State
estimation for nonlinear systems has been a challenge encountered in a wide range of …

In this paper, we present a unified optimal and exponentially stable filter for linear discrete-
time stochastic systems that simultaneously estimates the states and unknown inputs in an …

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 …

According to the iterative identification technique and the hierarchical identification principle,
this paper presents a two-stage gradient based and a least squares based iterative …

In this work, an event-based optimal state estimation problem for linear-time varying systems
with unknown inputs is investigated. By treating the unknown input as a process with a non …

In the paper, for systems described by ordinary differential equations a review of algorithms
of dynamical input reconstruction by results of inaccurate observations of its solutions is …

Simultaneous real-time input and state estimation and optimal sensor placements are
investigated in this paper, focusing on systems without direct feedthrough, such as …

Estimation of systems with arbitrary unknown inputs, for which no models or statistical
properties are assumed to be known, has received much attention. Given that no prior …

In this paper, the problem of the robust unknown input observer for a class of linear multi-
agent systems and its application to fault estimation are considered. First, an undirected …

Outliers can be caused by sensor errors, model uncertainties, changes in the ambient
environment, data loss, or malicious cyberattacks to contaminate the measurement process …