Applying the unscented Kalman filter for nonlinear state estimation

被引：372
|
作者：
Kandepu, Rambabu [1 ]
Foss, Bjarne [1 ]
Imsland, Lars [2 ]
机构：
[1] Norwegian Univ Sci & Technol, Dept Engn Cybernet, N-7491 Trondheim, Norway
[2] SINTEF ICT, N-7465 Trondheim, Norway
来源：
JOURNAL OF PROCESS CONTROL | 2008年 / 18卷 / 7-8期
关键词：
nonlinear state estimation; Kalman filter; constraint handling;
D O I：
10.1016/j.jprocont.2007.11.004
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Based on presentation of the principles of the EKF and UKF for state estimation, we discuss the differences of the two approaches. Four rather different simulation cases are considered to compare the performance. A simple procedure to include state constraints in the UKF is proposed and tested. The overall impression is that the performance of the UKF is better than the EKF in terms of robustness. and speed of convergence. The computational load in applying the UKF is comparable to the EKF. (c) 2007 Elsevier Ltd. All rights reserved.
引用
收藏
页码：753 / 768
页数：16
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