Online estimation of the internal states is a perquisite for monitoring, control, and fault
diagnosis of many engineering processes. A cost effective approach to monitor these …

This paper provides an overview of nonlinear state estimation techniques along with a
discussion on the challenges and opportunities for future work in the field. Emphasis is given …

The Kalman filter is the minimum-variance state estimator for linear dynamic systems with
Gaussian noise. Even if the noise is non-Gaussian, the Kalman filter is the best linear …

In this paper, the unscented Kalman filtering (UKF) problem is investigated for a class of
general nonlinear systems with stochastic uncertainties under communication protocols. A …

Dynamical systems modeling, particularly via systems of ordinary differential equations, has
been used to effectively capture the temporal behavior of different biochemical components …

In this paper we investigate the use of an alternative to the extended Kalman filter (EKF), the
unscented Kalman filter (UKF). First we give a broad overview of different UKF algorithms …

Uranium in situ recovery (ISR) is the most widely used uranium mining technique worldwide.
It consists of the dissolution of the ore by a mining solution, directly within the deposit. By …

This paper investigates constrained Bayesian state estimation problems by using a Particle
Filter (PF) approach. Constrained systems with nonlinear model and non-Gaussian …

Ensemble Kalman methods constitute an increasingly important tool in both state and
parameter estimation problems. Their popularity stems from the derivative-free nature of the …

Recent results in the development of efficient large-scale nonlinear programming (NLP)
algorithms have led to fast, on-line realizations of optimization-based methods for nonlinear …