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 …

A novel maximum likelihood solution to the problem of identifying parameters of a nonlinear
model under missing observations is presented. If the observations are missing, then it is …

State estimation is a major problem in industrial systems, particularly in industrial robotics.
To this end, Gaussian and nonparametric filters have been developed. In this paper, the …

State estimation is a major problem in industrial systems. To this end, Gaussian and
nonparametric filters have been developed. In this paper the Kalman Filter, which assumes …

Filtering-based indoor positioning using ultra wideband (UWB) requires known velocity to
predict prior position in the prediction stage. Velocity can be obtained from an inertial …

In this paper, we propose a method for vehicle tracking on roadways using measurements of
magnetometers and accelerometers. The measurements are used to build a low-cost, low …

In this paper, we compare Kalman update based filters with particle filters using simulations
on polymerization processes. In particular, we compare the unscented Kalman filter (UKF) …

In the machining industry, maximising profit is intuitively a primary goal; therefore
continuously increasing machining process uptime and consequently productivity and …

This paper presents a dynamic risk assessment using a comprehensive economic
consequence methodology in combination with a multivariate model‐based fault detection …

Drilling in the offshore environment involves high risk, mainly caused by uncertainties in the
reservoir conditions. Unplanned events such as the influx of reservoir fluids (ie, kick) can …