• DocumentCode
    650008
  • Title

    A posteriori error estimates of variational discretization mixed finite element methods for integro-differential optimal control problem

  • Author

    Zuliang Lu ; Dayong Liu

  • Author_Institution
    Sch. of Math. & Stat., Chongqing Three Gorges Univ., Chongqing, China
  • fYear
    2013
  • fDate
    Sept. 30 2013-Oct. 4 2013
  • Firstpage
    37
  • Lastpage
    41
  • Abstract
    In this paper we study a posteriori error estimates of all discretization parameters for quadratic convex optimal control problems governed by integro-differential equations by using the variational discretization mixed finite element methods. The state and co-state are approximated by the lowest order Raviart-Thomas mixed finite element spaces and the control is not approximated. By applying some error estimates results of mixed finite element methods for integro-differential equations, we derive a posteriori error estimates both for the coupled state and the control approximation of the optimal control problem.
  • Keywords
    convex programming; estimation theory; finite element analysis; integro-differential equations; optimal control; quadratic programming; variational techniques; control approximation; costate approximation; coupled state; discretization parameters; integro-differential equations; integro-differential optimal control problem; lowest order Raviart-Thomas mixed finite element spaces; posteriori error estimates; quadratic convex optimal control problems; variational discretization mixed finite element methods; a posteriori error estimates; integro-differential optimal control; variational discretization mixed finite element method;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electrical Engineering, Computing Science and Automatic Control (CCE), 2013 10th International Conference on
  • Conference_Location
    Mexico City
  • Print_ISBN
    978-1-4799-1460-9
  • Type

    conf

  • DOI
    10.1109/ICEEE.2013.6676039
  • Filename
    6676039