Scheduling kalman filters in continuous time

Jerome Le Ny, Eric Feron, Munther A. Dahleh

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

9 Scopus citations

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. © 2009 AACC.
Original languageEnglish (US)
Title of host publicationProceedings of the American Control Conference
Pages3799-3805
Number of pages7
DOIs
StatePublished - Nov 23 2009
Externally publishedYes

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