Abstract
In this work we develop an adaptive algorithm for solving elliptic optimal control problems with simultaneously appearing state and control constraints. Building upon the concept proposed in [9] the algorithm applies a Moreau-Yosida regularization technique for handling state constraints. The state and co-state variables are discretized using continuous piecewise linear finite elements while a variational discretization concept is applied for the control. To perform the adaptive mesh refinement cycle we derive local error representations which extend the goal-oriented error approach to our setting. The performance of the overall adaptive solver is demonstrated by a numerical example.
Mathematics Subject Classification (2000). 49J20; 65N30; 65N50.
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References
R. Becker and R. Rannacher, An optimal control approach to a posteriori error estimation in finite element methods. Acta Numerica 10 (2001), 1–102.
O. Benedix and B. Vexler, A posteriori error estimation and adaptivity for elliptic optimal control problems with state constraints. Comput. Optim. Appl. 44 (2009), 3–25.
M. Bergounioux, M. Haddou, M. Hintermüller, and K. Kunisch, A comparison of a Moreau-Yosida based active strategy and interior point methods for constrained optimal control problems. SIAM J. Optim. 11 (2000), 495–521.
M. Bergounioux and K. Kunisch, On the structure of the Lagrange multiplier for state-constrained optimal control problems. Syst. Control Lett. 48 (2002), 169–176.
M. Bergounioux and K. Kunisch, Primal-dual strategy for state-constrained optimal control problems. Comput. Optim. Appl. 22 (2002), 193–224.
E. Casas, Boundary control of semilinear elliptic equations with pointwise state constraints. SIAM J. Control Optim. 31 (1993), 993–1006.
E. Casas, Control of an elliptic problem with pointwise state constraints. SIAM J. Control Optim. 24 (1986), 1309–1318.
K. Deckelnick and M. Hinze, A finite element approximation to elliptic control problems in the presence of control and state constraints. Hamburger Beiträge zur Angewandten Mathematik, Universität Hamburg, preprint No. HBAM2007-01 (2007).
A. Günther and M. Hinze, A posteriori error control of a state constrained elliptic control problem. J. Numer. Math. 16 (2008), 307–322.
A. Günther and M.H. Tber, A goal-oriented adaptive Moreau-Yosida algorithm for control- and state-constrained elliptic control problems. DFG Schwerpunktprogramm 1253, preprint No. SPP1253-089 (2009).
Michael Hintermüller and Michael Hinze. Moreau-yosida regularization in state constrained elliptic control problems: error estimates and parameter adjustment. SIAM J. Numerical Analysis, 47:1666–1683, 2009.
M. Hintermüller and R.H.W. Hoppe, Goal-oriented adaptivity in control constrained optimal control of partial differential equations. SIAM J. Control Optim. 47 (2008), 1721–1743.
M. Hintermüller and R.H.W. Hoppe, Goal-oriented adaptivity in pointwise state constrained optimal control of partial differential equations. SIAM J. Control Optim. 48 (2010), 5468–5487.
M. Hintermüller, K. Ito and K. Kunisch, The primal-dual active set strategy as a semismooth Newton method. SIAM J. Optim. 13 (2003), 865–888.
M. Hintermüller and K. Kunisch, Feasible and noninterior path-following in constrained minimization with low multiplier regularity. SIAM J. Control Optim. 45 (2006), 1198–1221.
M. Hintermüller and K. Kunisch, Pde-constrained optimization subject to pointwise constraints on the control, the state and its derivative. SIAM J. Optim. 20 (2009), 1133–1156.
M. Hinze, A variational discretization concept in control constrained optimization: the linear-quadratic case. Comput. Optim. Appl. 30 (2005), 45–63.
R.H. Hoppe and M. Kieweg, Adaptive finite element methods for mixed control-state constrained optimal control problems for elliptic boundary value problems. Comput. Optim. Appl. 46 (2010), 511–533.
C. Meyer, A. Rösch and F. Tröltzsch, Optimal control of PDEs with regularized pointwise state constraints. Comput. Optim. Appl. 33 (2006), 209–228.
A. Schiela, State constrained optimal control problems with states of low regularity. SIAM J. Control Optim. 48 (2009), 2407–2432.
A. Schiela and A. Günther, An interior point algorithm with inexact step computation in function space for state constrained optimal control. 35 pp. To appear in Numerische Mathematik, doi:10.1007/s00211-011-0381-4, 2011.
A. Shapiro, On uniqueness of Lagrange multipliers in optimization problems subject to cone constraints. SIAM J. Optim. 7 (1997), 508–518.
F. Tröltzsch, Regular Lagrange multipliers for control problems with mixed pointwise control-state constraints. SIAM J. Optim. 15 (2005), 616–634.
B. Vexler and W. Wollner, Adaptive finite elements for elliptic optimization problems with control constraints. SIAM J. Control Optim. 47 (2008), 509–534.
W. Vogt, Adaptive Verfahren zur numerischen Quadratur und Kubatur. IfMath TU Ilmenau, preprint No. M 1/06 (2006).
M. Weiser, Interior point methods in function space. SIAM J. Control Optim. 44 (2005), 1766–1786.
W. Wollner, A posteriori error estimates for a finite element discretization of interior point methods for an elliptic optimization problem with state constraints. Comput. Optim. Appl. 47 (2010), 133–159.
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Günther, A., Hinze, M., Tber, M.H. (2012). A Posteriori Error Representations for Elliptic Optimal Control Problems with Control and State Constraints. In: Leugering, G., et al. Constrained Optimization and Optimal Control for Partial Differential Equations. International Series of Numerical Mathematics, vol 160. Birkhäuser, Basel. https://doi.org/10.1007/978-3-0348-0133-1_17
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DOI: https://doi.org/10.1007/978-3-0348-0133-1_17
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