State estimation (SE) is an important element of power network analysis applications
implemented at control centres, being instrumental in providing reliable data on the system …

In this paper, a distributed set-membership estimator for linear full-coupled systems affected
by bounded disturbances is presented. The estimator uses a multi-hop staircase …

The distribution of measurement noise is commonly considered as an assumed Gaussian
model in power systems, but this assumption is not always true in reality. This article …

This work is concerned with the design of a two-step distributed state estimation scheme for
large-scale systems in the presence of unknown-but-bounded disturbances and noise. The …

This paper presents a distributed unscented information filtering (UIF) method for state
estimation of interconnected nonlinear dynamic systems. The UIF method is an information …

In practical power system applications, the distribution of the measurement noise is
sometimes unknown and deviates from the assumed Gaussian noise model due to …

State estimators based on load flows and applied in electrical power systems (EPS) are a
basic and crucial function in energy management systems (EMS), since they must guarantee …

The cubature Kalman filter (CKF) has poor performance in strongly nonlinear systems while
the cubature particle filter has high computational complexity induced by stochastic …

Accurate state estimations are perquisites of autonomous navigation and orbit maintenance
missions. The extended Kalman filter (EKF) and the unscented Kalman filter (UKF), are the …

This paper investigates the distributed state estimation problem for spacecraft thermal
experiments over sensor networks. The state estimators are designed in a distributed …