Two-stage Unscented Kalman Filter for nonlinear systems in the presence of unknown random bias

被引：31
|
作者：
Xu, Jiahe [1 ]
Jing, Yuanwei [1 ]
Dimirovski, Georgi M. [2 ]
Ban, Ying [1 ]
机构：
[1] Northeastern Univ, Fac Informat Sci & Engn, Shenyang 110004, Peoples R China
[2] Dogus Univ Istanbul, Fac Engn, Dept Comp Engn, TR-347222 Istanbul, Turkey
来源：
2008 AMERICAN CONTROL CONFERENCE, VOLS 1-12 | 2008年
基金：
中国国家自然科学基金;
关键词：
D O I：
10.1109/ACC.2008.4587040
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The two-stage Unscented Kalman Filter (TUKF) is proposed to consider the nonlinear system in the presence of unknown random bias in a number of practical situations. The adaptive fading UKF is designed by using the forgetting factor to compensate the effects of incomplete information. The TUKF to estimate unknown random bias is designed by using the adaptive fading UKF. This filter can be used for nonlinear systems with unknown random bias on the assumption that the stochastic information of a random bias is incomplete. The stability of the TURF is analyzed and ensured under certain conditions. The performance of the TUKF is verified by using MATLAB simulation on the high-update rate Wheel Mobile Robot (WMR).
引用
收藏
页码：3530 / +
页数：2
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