• 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