Highly nonlinear systems estimation using extended and unscented kalman filters

Citation:

Laamari Y, Allaoui S, Chafaa K, Bendaikha A. Highly nonlinear systems estimation using extended and unscented kalman filters. [Internet]. 2021.

Date Published:

1978

Abstract:

The main idea of this study is to evaluate the estimation performance of extended and unscented Kalman filters (EKF and UKF). So, these latter are introduced to estimate the dynamic states of a similar model operating with identical covariance matrices in the same situation. The mean square error (MSE) criterion is used to quantify the estimation error between the actual and the estimated values. The simulation results obtained with Matlab/ Simulink software confirm the superiority and efficiency of UKF over EKF, especially when the system is highly non-linear under process and measurement noises, such is the case of the inverted double pendulum mounted on a cart (DIPC).

Publisher's Version

Last updated on 03/28/2022