Name
Abstract | ||
|---|---|---|
This paper considers the sensor scheduling problem which consists of estimating the state of an uncertain process based on measurements obtained by switching a given set of noisy sensors. The noise and uncertainty models considered in this paper are assumed to be unknown deterministic functions which satisfy an energy type constraint known as an integral quadratic constraint. The problem of optimal robust sensor scheduling is formulated and solution to this problem is given in terms of the existence of suitable solutions to a Riccati differential equation of the game type and a dynamic programming equation. Furthermore, a real time implementable method for sensor scheduling is also presented. |
Year | DOI | Venue |
|---|---|---|
2001 | 10.1016/S0167-6911(01)00086-X | Decision and Control, 2000. Proceedings of the 39th IEEE Conference |
Keywords | Field | DocType |
Robust filtering,Sensor scheduling,Uncertain system,Hybrid systems,Riccati equations | Dynamic programming,Differential equation,Mathematical optimization,Job shop scheduling,Control theory,Computer science,Scheduling (computing),Quadratic equation,Nurse scheduling problem,Bellman equation,Game theory | Journal |
Volume | Issue | ISSN |
43 | 2 | Systems & Control Letters |
ISBN | Citations | PageRank |
0-7803-6638-7 | 25 | 3.00 |
References | Authors | |
2 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Andrey V. Savkin | 1 | 1431 | 178.60 |
| Robin J. Evans | 2 | 1333 | 168.58 |
| Efstratios Skafidas | 3 | 200 | 32.11 |