Title :
Estimation of spatial fields using asymptotic embedding methods and Lagrangian sensing
Author :
Demetriou, Michael A. ; Fahroo, Fariba
Author_Institution :
Dept. of Mech. Eng., Worcester Polytech. Inst., Worcester, MA, USA
Abstract :
This paper proposes a new method for estimating spatial fields using moving and fixed-in-space sensing devices. It is assumed that the spatial field can be generated as the state of an elliptic partial differential equation and an on-line state estimator is proposed that takes partial state estimates in order to reconstruct the spatial field. The proposed estimation scheme is based on asymptotic embedding methods which essentially embed the elliptic PDE into a parabolic PDE that describes the state estimate in each time instance. To further enhance the performance of the state estimator, a guidance scheme provides the spatial relocation of the sensing devices within the spatial domain.
Keywords :
elliptic equations; parabolic equations; partial differential equations; sensors; state estimation; Lagrangian sensing; asymptotic embedding methods; elliptic PDE; elliptic partial differential equation; fixed-in-space sensing devices; online state estimator; parabolic PDE; spatial fields estimation; Convergence; Distribution functions; Equations; Estimation; Graphical models; Mathematical model; Sensors; Infinite dimensional systems; asymptotic embedding; elliptic PDEs; mobile sensors; parabolic PDEs;
Conference_Titel :
Decision and Control (CDC), 2012 IEEE 51st Annual Conference on
Conference_Location :
Maui, HI
Print_ISBN :
978-1-4673-2065-8
Electronic_ISBN :
0743-1546
DOI :
10.1109/CDC.2012.6426741