A novel extended Kalman filter for a class of nonlinear systems

被引：6
|
作者：
DONG Zhe and YOU Zheng (Department of Precision Instrument and Mechanology
机构：
来源：
ProgressinNaturalScience | 2006年 / 09期
关键词：
nonlinear systems; state estimation; Kalman filtering;
D O I：
暂无
中图分类号：
TN713 [滤波技术、滤波器];
学科分类号：
080902 ;
摘要：
Estimation of the state variables of nonlinear systems is one of the fundamental and significant problems in control and signal processing. A new extended Kalman filtering approach for a class of nonlinear discrete-time systems in engineering is presented in this paper. In contrast to the celebrated extended Kalman filter (EKF), there is no linearization operation in the design procedure of the filter, and the parameters of the filter are obtained through minimizing a proper upper bound of the mean-square estimation error. Simulation results show that this filter can provide higher estimation precision than that provided by the EKF.
引用
收藏
页码：912 / 918
页数：7
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