Time-domain harmonic state estimation of nonlinear load power systems with under-determined condition based on the extended Kalman filter

Rotated Unscented Kalman Filter for Two State Nonlinear Systems

In the several past years, Extended Kalman Filter (EKF) and Unscented Kalman Filter (UKF) havebecame basic algorithm for state-variables and parameters estimation of discrete nonlinear systems.The UKF has consistently outperformed for estimation. Sometimes least estimation error doesn't yieldwith UKF for the most nonlinear systems. In this paper, we use a new approach for a two variablestate no...

Nonlinear state estimation , indistinguishable states , and the extended Kalman filter

It has been shown by Judd and Smith that it is impossible to determine the state of a nonlinear dynamical system from noisy observations of the system, even with perfect knowledge of the system dynamics and unlimited prior observation. There is always a set of states indistinguishable from the true state. However, a new, simple method to assimilate data into a model and estimate the state is su...

Tuning of Extended Kalman Filter for nonlinear State Estimation

Kalman Filter is the most popular method for state estimation when the system is linear. State estimation is the typical issue in every part of engineering and science. But, for non linear systems, different extensions of Kalman Filter are used. Extended Kalman Filter is famous to discard the non linearity which uses First order Taylor series expansion. But for these estimation techniques, the ...

State Reconstruction In Nonlinear Stochastic Systems By Extended Kalman Filter

A New Adaptive Extended Kalman Filter for a Class of Nonlinear Systems

This paper proposes a new adaptive extended Kalman filter (AEKF) for a class of nonlinear systems perturbed by noise which is not necessarily additive. The proposed filter is adaptive against the uncertainty in the process and measurement noise covariances. This is accomplished by deriving two recursive updating rules for the noise covariances, these rules are easy to implement and reduce the n...