Since the landmark work of RE Kalman in the 1960s, considerable efforts have been
devoted to time series state space models for a large variety of dynamic estimation …

Availability of the synchronous machine angle and speed variables give us an accurate
picture of the overall condition of power networks leading therefore to an improved …

Accurate measurement of the rotor angle and speed of synchronous generators is
instrumental in developing powerful local or wide-area control and monitoring systems to …

For the nonlinear system with partially unknown dynamic, the problems of fault estimation
and fault-tolerant control are considered. A novel adaptive observer is designed to …

The classical recursive three‐step filter can be used to estimate the state and unknown input
when the system is affected by unknown input, but the recursive three‐step filter cannot be …

In this paper, we present a unified optimal and exponentially stable filter for linear discrete-
time stochastic systems that simultaneously estimates the states and unknown inputs in an …

In this work, an event-based optimal state estimation problem for linear-time varying systems
with unknown inputs is investigated. By treating the unknown input as a process with a non …

Due to its potential applications in robotics and navigation, recent years have witnessed
some progress in Kalman filter (KF) with norm constraints on the state. A noticeable …

In this article, a novel robust Gaussian approximation smoother based on expectation–
maximization (EM) algorithm is proposed for cooperative localization (CL) with faulty …

This paper presents a novel algorithm that reconstructs structural responses under unknown
inputs and rank-deficient feedthrough matrix conditions. The algorithm eliminates one of the …