Scheduling Kalman filters in continuous time
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Dahleh_Scheduling Kalman.pdf
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484.92 KB
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Author(s)
Ny, Jerome Le
Feron, Eric
Dahleh, Munther A.
Date Issued
June 2009
Journal
American Control Conference
Publisher
Institute of Electrical and Electronics Engineers
Citation
Le Ny, J., E. Feron, and M.A. Dahleh. “Scheduling Kalman Filters in Continuous Time.” American Control Conference, 2009. ACC ’09. 2009. 3799-3805. Copyright © 2009, IEEE
Version
Final published version
Abstract
A set of N independent Gaussian linear time invariant systems is observed by M sensors whose task is to provide the best possible steady-state causal minimum mean square estimate of the state of the systems, in addition to minimizing a steady-state measurement cost. The sensors can switch between systems instantaneously, and there are additional resource constraints, for example on the number of sensors which can observe a given system simultaneously. We first derive a tractable relaxation of the problem, which provides a bound on the achievable performance. This bound can be computed by solving a convex program involving linear matrix inequalities. Exploiting the additional structure of the sites evolving independently, we can decompose this program into coupled smaller dimensional problems. In the scalar case with identical sensors, we give an analytical expression for an index policy proposed in a more general context by Whittle. In the general case, we develop open-loop periodic switching policies whose performance matches the bound arbitrarily closely.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Massachusetts Institute of Technology. Laboratory for Information and Decision Systems
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Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1109/ACC.2009.5160141
