Self-Recovering Extended Kalman Filter for Frequency Tracking

被引：0

作者：

Pak, Jung Min ^{[1
]}

Ahn, Choon Ki ^{[1
]}

Lim, Myo Taeg ^{[1
]}

机构：

[1] Korea Univ, Sch Elect Engn, 145 Anam Ro, Seoul, South Korea

来源：

2015 15TH INTERNATIONAL CONFERENCE ON CONTROL, AUTOMATION AND SYSTEMS (ICCAS) | 2015年

关键词：

Self-recovering extended Kalman filter (SREKF); extended Kalman filter (EKF); finite impulse response (FIR) filter; frequency tracking;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper proposes a new nonlinear filtering algorithm called the self-recovering extended Kalman filter ( SREKF). In the SREKF algorithm, the EKF's failure or abnormal operation is automatically diagnosed. When the failure is diagnosed, an assisting filter, a nonlinear finite impulse response ( FIR) filter, is operated. Using the output of the nonlinear FIR filter, the EKF is reset and rebooted. In this way, the SREKF can self-recover from failures. The SREKF is applied to a frequency tracking problem for demonstration of its effectiveness.

引用

页码：389 / 392

页数：4

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