Abstract
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.
| Original language | English |
|---|---|
| Title of host publication | ICCAS 2015 - 2015 15th International Conference on Control, Automation and Systems, Proceedings |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 389-392 |
| Number of pages | 4 |
| ISBN (Print) | 9788993215090 |
| DOIs | |
| Publication status | Published - 2015 Dec 23 |
| Event | 15th International Conference on Control, Automation and Systems, ICCAS 2015 - Busan, Korea, Republic of Duration: 2015 Oct 13 → 2015 Oct 16 |
Other
| Other | 15th International Conference on Control, Automation and Systems, ICCAS 2015 |
|---|---|
| Country | Korea, Republic of |
| City | Busan |
| Period | 15/10/13 → 15/10/16 |
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Keywords
- extended Kalman filter (EKF)
- finite impulse response (FIR) filter
- frequency tracking
- Self-recovering extended Kalman filter (SREKF)
ASJC Scopus subject areas
- Control and Systems Engineering
Cite this
Pak, J. M., Ahn, C. K., & Lim, M. T. (2015). Self-recovering extended Kalman filter for frequency tracking. In ICCAS 2015 - 2015 15th International Conference on Control, Automation and Systems, Proceedings (pp. 389-392). [7364945] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICCAS.2015.7364945