This paper is motivated by the filtering estimation for a class of nonlinear stochastic systems
in the case that the measurements are randomly delayed by one sampling time. Through …

This paper proposes a Gaussian approximation recursive filter (GASF) for a class of
nonlinear stochastic systems in the case that the process and measurement noises are …

Adaptive and robust methods are two opposite strategies to be adopted in the Kalman filter
when the difference between the predictive observation and the actual observation, ie the …

Performance of the Kalman filter (KF) is degraded when dealing with nonlinear dynamic
systems. For a kind of nonlinear biomechatronics system, a fifth-degree ensemble iterated …

Nonlinear Estimation: Methods and Applications with Deterministic Sample Points focusses
on a comprehensive treatment of deterministic sample point filters (also called Gaussian …

An adaptive Kalman filter with fading factor is derived to address the modeling errors. In any
recursion of the proposed filter, a judging index is defined as the square of the Mahalanobis …

An adaptive robust Kalman filter algorithm is derived to account for both process noise and
measurement noise uncertainty. The adaptive algorithm estimates process noise covariance …

Friction stir welding (FSW) is a relatively new and promising joining process that is the
subject of much current research. When welding with constant parameters, the axial force …

This paper develops a robust divided difference filtering approach based on the concept of
Desensitized Kalman Filtering. The filters are formulated using a minimum variance cost …

Power Systems Dynamic State Estimation (PSDSE) using hybrid measurements from
Phasor Measurement Units (PMUs) and Remote Terminal Units (RTUs) in the presence of …