Highly Nonlinear Systems Estimation using Extended and Unscented Kalman Filters

被引：1
|
作者：
Laamari, Yahia [1 ]
Allaoui, Samia [2 ]
Chafaa, Kheireddine [2 ]
Bendaikhal, Abdelmalik [1 ]
机构：
[1] Univ MSila, Fac Technol, Res Lab Elect Engn, BP 166, Msila 28000, Algeria
[2] Batna 2 Univ, Elect Dept, Fac Technol, Fesdis 05078, Batna, Algeria
来源：
PRZEGLAD ELEKTROTECHNICZNY | 2021年 / 97卷 / 05期
关键词：
Nonlinear Systems; Double Inverted Pendulum; Extended and Unscented Kalman filters; State Estimation;
D O I：
10.15199/48.2021.05.20
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
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).
引用
收藏
页码：111 / 115
页数：5
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