Modified state estimation with fixed point update based on maximum correntropy criterion

Hayato Maki, Seiichiro Katsura

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

Abstract

It is well known that Kalman Filter is good for a state estimation on a linear system. The criterion is a square error function, which is efficient and sufficient for most systems. However, the square error evaluation function is often not sufficient in the systems under non-Gaussian noise. In recent years, an entropy has been attracting attention as an evaluation function changing to the square error criterion. Beginning with entropy of Shannon, its characteristics are related to higher-order statistics. When the entropy is set as criterion, all moments or all even moments of the state estimation error can be constrained. These characteristics have been utilized for learning system, adaptive filtering, and neuro-control. In this research, we focus on a correntropy, which has expanded Renyi 's entropy more generally, and the correntropy is utilized in order to estimate states of systems. This method uses multi-step ahead predictions, and aims to better state estimation. The method of multi-step ahead predictions is effective for the case that the system has not only statistic process noise but also other disturbances. Previous methods using the correntropy as a criterion are introduced here, and compared with modified method through experimental data.

Original languageEnglish
Title of host publicationProceedings - 2019 IEEE International Conference on Industrial Technology, ICIT 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages744-749
Number of pages6
ISBN (Electronic)9781538663769
DOIs
Publication statusPublished - 2019 Feb 1
Event2019 IEEE International Conference on Industrial Technology, ICIT 2019 - Melbourne, Australia
Duration: 2019 Feb 132019 Feb 15

Publication series

NameProceedings of the IEEE International Conference on Industrial Technology
Volume2019-February

Conference

Conference2019 IEEE International Conference on Industrial Technology, ICIT 2019
CountryAustralia
CityMelbourne
Period19/2/1319/2/15

Keywords

  • Correntropy
  • Fixed point algorithm
  • Optimization
  • State estimation

ASJC Scopus subject areas

  • Computer Science Applications
  • Electrical and Electronic Engineering

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  • Cite this

    Maki, H., & Katsura, S. (2019). Modified state estimation with fixed point update based on maximum correntropy criterion. In Proceedings - 2019 IEEE International Conference on Industrial Technology, ICIT 2019 (pp. 744-749). [8755221] (Proceedings of the IEEE International Conference on Industrial Technology; Vol. 2019-February). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICIT.2019.8755221