Fusion Kalman/UFIR Filter for State Estimation With Uncertain Parameters and Noise Statistics

Shunyi Zhao, Yuriy S. Shmaliy, Peng Shi, Choon Ki Ahn

Research output: Contribution to journalArticle

38 Citations (Scopus)

Abstract

In this paper, we fuse the Kalman filter (KF) that is optimal but not robust with the unbiased finite-impulse response (UFIR) filter which is more robust than KF but not optimal. The fusion filter employs the KF and UFIR filter as subfilters and produces smaller errors under the industrial conditions. In order to provide the best fusion effect, the operation point where UFIR meets Kalman is determined by applying probabilistic weights to each subfilter. Extensive simulations of the three degree of freedom (3-DOF) hover system have shown that the fusion filter output tends to range close to that by the best subfilter. Experimental verification provided for a 1-DOF torsion system has confirmed validity of simulation.

Original languageEnglish
Article number7778185
Pages (from-to)3075-3083
Number of pages9
JournalIEEE Transactions on Industrial Electronics
Volume64
Issue number4
DOIs
Publication statusPublished - 2017 Apr 1

Fingerprint

FIR filters
State estimation
Kalman filters
Fusion reactions
Statistics
Electric fuses
Impulse response
Torsional stress

Keywords

  • Fusion filter (FF)
  • industrial conditions
  • Kalman filter (KF)
  • state estimation
  • unbiased finite-impulse response (UFIR) filter

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science Applications
  • Electrical and Electronic Engineering

Cite this

Fusion Kalman/UFIR Filter for State Estimation With Uncertain Parameters and Noise Statistics. / Zhao, Shunyi; Shmaliy, Yuriy S.; Shi, Peng; Ahn, Choon Ki.

In: IEEE Transactions on Industrial Electronics, Vol. 64, No. 4, 7778185, 01.04.2017, p. 3075-3083.

Research output: Contribution to journalArticle

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