Extended State based Kalman Filter for Uncertain Systems with Bias

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...

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...

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 variablesta...

State Reconstruction In Nonlinear Stochastic Systems By Extended Kalman Filter

Nonlinear H Control for Uncertain Flexible Joint Robots with Unscented Kalman Filter

Todays, use of combination of two or more methods was considered to control of systems. In this paper ispresented how to design of a nonlinear H∞ (NL-H∞) controller for flexible joint robot (FJR) based on boundedUKF state estimator. The UKF has more advantages to standard EKF such as low bios and no need toderivations. In this research, based on spong primary model for FJRs, same as rigid robot...