DocumentCode :
3278721
Title :
Linear and quadratic programming formulations of data assimilation or data reconciliation problems for a class of Hamilton-Jacobi equations
Author :
Claudel, C.G. ; Bayen, A.M.
Author_Institution :
Dept. of Electr. Eng. & Comput. Sci., Univ. of California, Berkeley, CA, USA
fYear :
2010
fDate :
June 30 2010-July 2 2010
Firstpage :
4115
Lastpage :
4120
Abstract :
This article proposes a new method for data assimilation and data reconciliation applicable to systems modeled by conservation laws. The state of the system is written in the form of a scalar Hamilton-Jacobi (HJ) partial differential equation (PDE), for which the solution is fully characterized by a LaxHopf formula. Using the properties of the solution, we prove that when the data of the problem is prescribed in piecewise affine form, the constraints of the model are in standard convex form, and can be computed explicitly. This property enables us to identify a class of data assimilation and data reconciliation problems that can be formulated using convex programs in standard form.
Keywords :
convex programming; data assimilation; linear programming; partial differential equations; quadratic programming; Hamilton-Jacobi partial differential equation; Lax-Hopf formula; convex program; data assimilation; data reconciliation; linear programming; quadratic programming; Control systems; Data assimilation; Distributed parameter systems; Filtering; Kalman filters; Parameter estimation; Partial differential equations; Quadratic programming; Road vehicles; State estimation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
American Control Conference (ACC), 2010
Conference_Location :
Baltimore, MD
ISSN :
0743-1619
Print_ISBN :
978-1-4244-7426-4
Type :
conf
DOI :
10.1109/ACC.2010.5530615
Filename :
5530615
Link To Document :
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