Motivated by challenges in state estimation with event-based measurement updates, the
properties of the exact and approximate set-valued Kalman filters with multiple sensor …

This paper presents an optimal discrete time reduced order Kalman filter. The reduced order
filter is used to estimate a linear combination of a subset of the state vector. Most previous …

This paper proposes a general method for dealing with state estimation under nonlinear
state soft inequality constraints. This method is based on the projection approach, and then …

This paper presents a new algorithm which yields a nonlinear state estimator called iterated
unscented Kalman filter. This state estimator makes use of both statistical and analytical …

Due to its potential applications in robotics and navigation, recent years have witnessed
some progress in Kalman filter (KF) with norm constraints on the state. A noticeable …

As a recursive state estimation algorithm, the Kalman filter (KF) assumes initial state
distribution is known a priori, while in practice the initial distribution is commonly treated as …

The time and measurement update for the discrete time Kalman filter can be formulated in
terms of conditional means and covariances. The unscented Kalman filter can be interpreted …

A significant shortcoming of the state space control theory that emerged in the 1960s was its
lack of concern for the issue of robustness. However, in the design of feedback control …

Recursive estimation of constrained nonlinear dynamical systems has attracted the attention
of many researchers in recent years. In this work, we propose a constrained recursive …

This brief focuses on the development of a linear Kalman filtering algorithm when the control
input variable is corrupted by noises. The noisy input is considered in the derivation process …