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A Frequency-Domain Characterization of Optimal Error Covariance for the Kalman-Bucy Filter
KTH, School of Electrical Engineering and Computer Science (EECS).
Tokyo Inst Technol, Dept Comp Sci, Tokyo, Japan..
City Univ Hong Kong, Dept Elect Engn, Hong Kong, Peoples R China..
KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control.ORCID iD: 0000-0001-9940-5929
2018 (English)In: 2018 IEEE CONFERENCE ON DECISION AND CONTROL (CDC), IEEE , 2018, p. 6366-6371Conference paper, Published paper (Refereed)
Abstract [en]

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.

Place, publisher, year, edition, pages
IEEE , 2018. p. 6366-6371
Series
IEEE Conference on Decision and Control, ISSN 0743-1546
National Category
Computer and Information Sciences
Identifiers
URN: urn:nbn:se:kth:diva-245013DOI: 10.1109/CDC.2018.8619084ISI: 000458114805140Scopus ID: 2-s2.0-85062165780ISBN: 978-1-5386-1395-5 (print)OAI: oai:DiVA.org:kth-245013DiVA, id: diva2:1293690
Conference
57th IEEE Conference on Decision and Control (CDC), DEC 17-19, 2018, Miami Beach, FL
Note

QC 20190305

Available from: 2019-03-05 Created: 2019-03-05 Last updated: 2019-04-11Bibliographically approved

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Johansson, Karl H.

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CiteExportLink to record
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Citation style
  • apa
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Language
  • de-DE
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  • nn-NO
  • nn-NB
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  • Other locale
More languages
Output format
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