To comply with the increasing complexity of new mechatronic systems and stricter safety
regulations, advanced estimation algorithms are currently undergoing a transformation …

A convergence analysis of the modified unscented Kalman filter (UKF), used as an observer
for a class of nonlinear deterministic continuous time systems, is presented. Under certain …

This article is concerned with Gaussian filtering in nonlinear continuous-discrete state-space
models. We propose a novel Taylor moment expansion (TME) Gaussian filter, which …

We present a continuous-time probabilistic approach for estimating the chirp signal and its
instantaneous frequency function when the true forms of these functions are not accessible …

This paper investigates managing the comfort-handling trade-off of a quarter car suspension
system using a Kalman filter. Using the unscented Kalman filter, the adapted feedback input …

The sigma-point filters, such as the unscented Kalman filter, are popular alternatives to the
ubiquitous extended Kalman filter. The classical quadrature rules used in the sigma-point …

This paper is aimed at characterizing the mean square error and probabilistic uncertainty of
a popular class of filtering algorithms in nonlinear systems. The state estimation error of the …

We present a new method of calculating approximate probabilistic bounds for the state
estimation error of a constant-gain Kalman filter in nonlinear multivariate systems. A critical …

This letter is concerned with solvingcontinuous-discrete Gaussian smoothing problems by
using the Taylor moment expansion (TME) scheme. In the proposed smoothing method, we …

This work proposes a detectability condition for linear time-varying systems based on the
exponential dichotomy spectrum. The condition guarantees the existence of an observer …