Robust strong tracking unscented Kalman filter for non‐linear systems with unknown inputs
Abstract This paper proposes a state estimation approach ‘robust strong tracking unscented Kalman filter with unknown inputs’ that can be applied to non‐linear systems with unknown inputs. Specifically, the non‐linear state and measurement equations are linearised by statistical linearisation. Then,...
Saved in:
Main Authors: | Xinghua Liu, Jianwei Guan, Rui Jiang, Xiang Gao, Badong Chen, Shuzhi Sam Ge |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2022-05-01
|
Series: | IET Signal Processing |
Subjects: | |
Online Access: | https://doi.org/10.1049/sil2.12098 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Optimization of Covariance Matrices of Kalman Filter with Unknown Input Using Modified Directional Bat Algorithm
by: Lijun Liu, et al.
Published: (2025-01-01) -
An Improved Unscented Kalman Filter Applied to Positioning and Navigation of Autonomous Underwater Vehicles
by: Jinchao Zhao, et al.
Published: (2025-01-01) -
A State Estimation of Dynamic Parameters of Electric Drive Articulated Vehicles Based on the Forgetting Factor of Unscented Kalman Filter with Singular Value Decomposition
by: Tianlong Lei, et al.
Published: (2025-01-01) -
A comparison of nonlinear filtering approaches in the context of anHIV model
by: H. Thomas Banks, et al.
Published: (2010-03-01) -
An Augmented Estimation of the State of Charge and Measurement Fault for Lithium-ion Batteries for Off-Grid Stationary Applications
by: Mehrdad Yousefi Faal
Published: (2023-12-01)