'Stealth' filtering with reduced order observations

C. Olivier, O. Dessoude, E. Feron

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

1 Scopus citations

Abstract

Communications resources in modern automated systems have to be shared between different users and purposes. A process filtering task performed by a dedicated processor and integrating measurements delivered by a remote information source may in particular be subject to data flow limitations. The authors examine some problems related to these measurement data reductions in a linear filtering algorithm, focusing on linear observation compression schemes. A global approach gives a sufficient algebraic condition to admit reduced-order measurement vectors. Compression policies, dynamically optimized under specific criteria, are proposed. Remaining generic problems and possible extensions of such an approach are also discussed.
Original languageEnglish (US)
Title of host publicationProceedings of the IEEE Conference on Decision and Control
PublisherPubl by IEEEPiscataway, NJ, United States
Pages3060-3065
Number of pages6
ISBN (Print)0780304500
StatePublished - Dec 1 1991

Bibliographical note

Generated from Scopus record by KAUST IRTS on 2021-02-18

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