Self-recovering extended Kalman filter for frequency tracking

Jung Min Pak, Choon Ki Ahn, Myo Taeg Lim

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

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 languageEnglish
Title of host publicationICCAS 2015 - 2015 15th International Conference on Control, Automation and Systems, Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages389-392
Number of pages4
ISBN (Print)9788993215090
DOIs
Publication statusPublished - 2015 Dec 23
Event15th International Conference on Control, Automation and Systems, ICCAS 2015 - Busan, Korea, Republic of
Duration: 2015 Oct 132015 Oct 16

Other

Other15th International Conference on Control, Automation and Systems, ICCAS 2015
CountryKorea, Republic of
CityBusan
Period15/10/1315/10/16

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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