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The quadratic loss penalty is a well known technique for optimization and control problems to treat constraints. In the present paper they are applied to handle control bounds in a boundary control problems with semilinear elliptic state equations. Unlike in the case of finite dimensional optimization for infinite dimensional problems the order of convergence could only be roughly estimated, but numerical experiments revealed a clearly better convergence behavior with constants independent of the dimension of the used discretization. The main result in the present paper is the proof of sharp convergence bounds for both, the finite und infinite dimensional problem with a mesh-independence in case of the discretization. Further, to achieve an efficient realization of penalty methods the principle of control reduction is applied, i.e. the control variable is represented by the adjoint state variable by means of some nonlinear function. The resulting optimality system this way depends only on the state and adjoint state. This system is discretized by conforming linear finite elements. Numerical experiments show exactly the theoretically predicted behavior of the studied penalty technique.
Czasopismo
Rocznik
Tom
Strony
9--26
Opis fizyczny
Bibliogr. 20 poz, rys.
Twórcy
autor
- Institut fur Numerische Mathematik, Technische Universität Dresden, 01062 Dresden, Germany
autor
- Institut fur Mathematik und Bauinformatik, Universität der Bundeswehr München, 81549 Neubiberg, Germany
Bibliografia
- [1] Apel T., Pfefferer J., Rösch A.; Finite element error estimates on the boundary with application to optimal control, submitted.
- [2] Carl S., Le V.K., Motreanu D.; Nonsmooth Variational Problems and Their Inequalities, Springer 2007.
- [3] Casas E.; Boundary control of semilinear elliptic equations with pointwise state constraints, SIAM J. Control Optim. 31, 1993.
- [4] Casas E., Mateos M.; Error estimates for the numerical approximation of Neumann control problems, Comp. Optim. Appl. 39, 2008, pp. 265-295.
- [5] Casas E., Mateos M.; Uniform convergence of FEM. applications to state constrained problems, Comp. Appl Math. 21, 2002, pp. 67–100.
- [6] Ciarlet P.; The Finite Element Method for Elliptic Problems, North-Holland Publ. Co. 1978.
- [7] Fiacco A.V., McCormick G.P.; Nonlinear programming: Sequential unconstrained minimization techniques, Wiley 1968.
- [8] Grossmann C., Kunz H., Meischner R.; Elliptic control by penalty techniques with control reduction, System modeling and optimization, IFIP Adv. Inf. Commun. Technol. 312, 2009, Springer, Berlin, pp. 251–267.
- [9] Grossmann C., Roos H.-G., Stynes M.; Numerical Treatment of Partial Differential Equations, Springer, Berlin 2007.
- [10] Grossmann C., Terno J.; Numerik der Optimierung, Teubner 1993.
- [11] Grossmann C., Winkler M.; Mesh-Independent Convergence of Penalty Methods Applied to Optimal Control with Partial Differential Equations (to appear in Optimization 2012).
- [12] Grossmann C., Zadlo M.; A general class of penalty/barrier path-following Newton methods for nonlinear programming, Optimization 54, 2005, pp. 161–190.
- [13] Grossmann C., Zadlo M.; General primal-dual penalty/barrier path-following Newton methods for nonlinear programming, Optimization 54, 2005, pp. 641–663.
- [14] Hinze M.; A variational discretization concept in control constrained optimization:The linear-quadratic case, Comput. Optim. Appl. 30, 2005, pp. 45–61.
- [15] Krumbiegel K., Neitzel I., Rösch A.; Regularization for semilinear elliptic optimal control problems with pointwise state and control constraints, Comput. Optim.Appl. 2010, pp. 1–27
- [16] Schiela A.; The Control Reduced Interior Point Method. A Function Space Oriented Algorithmic Approach, Verlag Dr. Hut, München 2006.
- [17] Schiela A.; A continuity result for Nemyckii Operators and some applications in PDE constrained optimal control, ZIB, Berlin 2006.
- [18] Tröltzsch F.; Optimal Control of Partial Differential Equations. Theory, Methods and Applications, Amer. Math. Soc. (AMS), Providence, RI, 2010.
- [19] Ulbrich M.; Semismooth Newton methods for operator equations in function spaces, SIAM J. Optimization 13, 2002, pp. 805–841.
- [20] Zeidler E.; Nonlinear Functional Analysis and its Applications, II – Nonlinear Monotone Operators, Springer-Verlag, New York 1985.
Typ dokumentu
Bibliografia
Identyfikator YADDA
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