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

Hayato Maki, Seiichiro Katsura

研究成果: Conference contribution

抄録

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.

本文言語English
ホスト出版物のタイトルProceedings - 2019 IEEE International Conference on Industrial Technology, ICIT 2019
出版社Institute of Electrical and Electronics Engineers Inc.
ページ744-749
ページ数6
ISBN(電子版)9781538663769
DOI
出版ステータスPublished - 2019 2 1
イベント2019 IEEE International Conference on Industrial Technology, ICIT 2019 - Melbourne, Australia
継続期間: 2019 2 132019 2 15

出版物シリーズ

名前Proceedings of the IEEE International Conference on Industrial Technology
2019-February

Conference

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

ASJC Scopus subject areas

  • Computer Science Applications
  • Electrical and Electronic Engineering

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