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Sensor scheduling in variance based event triggered estimation with packet drops
Paderborn Univ, Dept Elect Engn EIM E, D-33098 Paderborn, Germany.
Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
Paderborn Univ, Dept Elect Engn EIM E, D-33098 Paderborn, Germany.
2017 (English)In: IEEE Transactions on Automatic Control, ISSN 0018-9286, E-ISSN 1558-2523, Vol. 62, no 4, 1880-1895 p.Article in journal (Refereed) Published
Abstract [en]

This paper considers a remote state estimation problem with multiple sensors observing a dynamical process, where sensors transmit local state estimates over an independent and identically distributed (i.i.d.) packet dropping channel to a remote estimator. At every discrete time instant, the remote estimator decides whether each sensor should transmit or not, with each sensor transmission incurring a fixed energy cost. The channel is shared such that collisions will occur if more than one sensor transmits at a time. Performance is quantified via an optimization problem that minimizes a convex combination of the expected estimation error covariance at the remote estimator and expected energy usage across the sensors. For transmission schedules dependent only on the estimation error covariance at the remote estimator, this work establishes structural results on the optimal scheduling which show that: 1) for unstable systems, if the error covariance is large then a sensor will always be scheduled to transmit and 2) there is a threshold-type behavior in switching from one sensor transmitting to another. Specializing to the single sensor case, these structural results demonstrate that a threshold policy (i.e., transmit if the error covariance exceeds a certain threshold and don't transmit otherwise) is optimal. We also consider the situation where sensors transmit measurements instead of state estimates, and establish structural results including the optimality of threshold policies for the single sensor, scalar case. These results provide a theoretical justification for the use of such threshold policies in variance based event triggered estimation. Numerical studies confirm the qualitative behavior predicted by our structural results.

Place, publisher, year, edition, pages
2017. Vol. 62, no 4, 1880-1895 p.
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:uu:diva-306981DOI: 10.1109/TAC.2016.2602499ISI: 000399033000024OAI: oai:DiVA.org:uu-306981DiVA: diva2:1045031
Funder
Australian Research Council, DE120102012, DP120101122
Available from: 2016-11-08 Created: 2016-11-08 Last updated: 2017-05-18Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
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  • de-DE
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