A Frequency-Domain Characterization of Optimal Error Covariance for the Kalman-Bucy Filter

Song Fang, Hideaki Ishii, Jie Chen, Karl Henrik Johansson

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

2 Citations (Scopus)

Abstract

In this paper, we discover that the trace of the division of the optimal output estimation error covariance over the noise covariance attained by the Kalman-Bucy filter can be explicitly expressed in terms of the plant dynamics and noise statistics in a frequency-domain integral characterization. Towards this end, we examine the algebraic Riccati equation associated with Kalman-Bucy filtering using analytic function theory and relate it to the Bode integral. Our approach features an alternative, frequency-domain framework for analyzing algebraic Riccati equations and reduces to various existing related results.
Original languageEnglish
Title of host publication2018 IEEE Conference on Decision and Control (CDC)
PublisherIEEE
Pages6366-6371
ISBN (Print)9781538613955
DOIs
Publication statusPublished - Dec 2018
Event57th IEEE Conference on Decision and Control (CDC 2018) - Miami, United States
Duration: 17 Dec 201819 Dec 2018

Publication series

NameProceedings of the IEEE Conference on Decision and Control
Volume2018-December
ISSN (Print)0743-1546

Conference

Conference57th IEEE Conference on Decision and Control (CDC 2018)
Country/TerritoryUnited States
CityMiami
Period17/12/1819/12/18

Research Keywords

  • NETWORKED FEEDBACK
  • TRADE-OFFS
  • INFORMATION
  • BODE
  • STABILIZATION
  • PERFORMANCE
  • LIMITATIONS
  • CHANNELS
  • RICCATI
  • SYSTEMS

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