Scheduling Kalman filters in continuous time Export

@inproceedings{JNy09, 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.}, author = {Le Ny, J. and Feron, E. and Dahleh, M. A.}, booktitle = {American Control Conference, 2009}, citeulike-article-id = {6070207}, citeulike-linkout-0 = {http://dx.doi.org/10.1109/ACC.2009.5160141}, citeulike-linkout-1 = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5160141}, day = {10}, doi = {10.1109/ACC.2009.5160141}, journal = {American Control Conference, 2009. ACC '09.}, keywords = {1451, continuous, filter, kalman, scheduling, time}, month = {July}, pages = {3799--3805}, posted-at = {2009-11-04 16:45:01}, priority = {3}, title = {Scheduling Kalman filters in continuous time}, url = {http://dx.doi.org/10.1109/ACC.2009.5160141}, year = {2009} }

TY - CONF ID - JNy09 L3 - citeulike-article-id:6070207 N2 - 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. JF - American Control Conference, 2009. ACC '09. EP - 3805 TI - Scheduling Kalman filters in continuous time T2 - American Control Conference, 2009 SP - 3799 KW - 1451 KW - continuous KW - filter KW - kalman KW - scheduling KW - time AU - Le Ny, J AU - Feron, E AU - Dahleh, MA PY - 2009/07/10/ UR - http://dx.doi.org/10.1109/ACC.2009.5160141 ER -