Advanced Search
Article Contents
Article Contents

Finite element error analysis for measure-valued optimal control problems governed by a 1D wave equation with variable coefficients

The first and the second author were supported by FWF and DFG through the International Research Training Group IGDK 1754 'Optimization and Numerical Analysis for Partial Differential Equations with Nonsmooth Structures'. The third has been funded within the framework of the Academic Fund Program at the National Research University Higher School of Economics in 2016-2017 (grant no. 16-01-0054) and by the Russian Academic Excellence Project '5-100'. He also thanks the Technical University of Munich for its hospitality in 2014-2015 years.
Abstract Full Text(HTML) Figure(6) Related Papers Cited by
  • This work is concerned with the optimal control problems governed by a 1D wave equation with variable coefficients and the control spaces $\mathcal M_T$ of either measure-valued functions $L_{{{w}^{*}}}^{2}\left( I, \mathcal M\left( {\mathit \Omega } \right) \right)$ or vector measures $\mathcal M({\mathit \Omega }, L^2(I))$. The cost functional involves the standard quadratic tracking terms and the regularization term $α\|u\|_{\mathcal M_T}$ with $α>0$. We construct and study three-level in time bilinear finite element discretizations for this class of problems. The main focus lies on the derivation of error estimates for the optimal state variable and the error measured in the cost functional. The analysis is mainly based on some previous results of the authors. The numerical results are included.

    Mathematics Subject Classification: Primary: 65M60, 49K20, 49M05, 49M25, 49M29; Secondary: 35L05.


    \begin{equation} \\ \end{equation}
  • 加载中
  • Figure 1.  Example 1: the reference solution $(\hat u, \hat y)$

    Figure 2.  Example 1: errors as $h$ refines and $M = 2^{10}$

    Figure 3.  Example 1: errors as $\tau$ refines and $N = 2^{10}$

    Figure 4.  Example 2: the reference solution $(\hat u, \hat y)$

    Figure 5.  Example 2: errors as $h$ refines and $M = 2^{10}$

    Figure 6.  Example 2: errors as $\tau$ refines and $N = 2^{10}$

  • [1] L. Bales and I. Lasiecka, Continuous finite elements in space and time for the nonhomogeneous wave equation, Computers. Mathematics with Applications, 27 (1994), 91-102.  doi: 10.1016/0898-1221(94)90048-5.
    [2] W. BangerthM. Geiger and R. Rannacher, Adaptive Galerkin finite element methods for the wave equation, Comput. Methods Appl. Math., 10 (2010), 3-48. 
    [3] J. Bergh and J. Löfström, Interpolation Spaces. An Introduction, Springer, Berlin-New York, 1976.
    [4] A. BermúdezP. Gamallo and R. Rodríguez, Finite element methods in local active control of sound, SIAM J. Control Optim., 43 (2004), 437-465.  doi: 10.1137/S0363012903431785.
    [5] V. I. Bogachev, Measure Theory. Vol. I, II, Springer, Berlin, 2007.
    [6] K. Bredies and H. K. Pikkarainen, Inverse problems in spaces of measures, ESAIM Control Optim. Calc. Var., 19 (2013), 190-218.  doi: 10.1051/cocv/2011205.
    [7] S. C. Brenner and L. R. Scott, The Mathematical Theory of Finite Element Methods, vol. 15 of Texts in Applied Mathematics, Springer, New York, 3 ed., 2008.
    [8] H. Brezis, Functional Analysis, Sobolev Spaces and Partial Differential Equations, Springer, New York, 2011.
    [9] P. BrunnerC. ClasonM. Freiberger and H. Scharfetter, A deterministic approach to the adapted optode placement for illumination of highly scattering tissue, Biomed. Opt. Express, 3 (2012), 1732-1743.  doi: 10.1364/BOE.3.001732.
    [10] G. Butazzo, M. Giaqinta and S. Hildebrandt, One-dimensional Variational Problems. An Introduction, Clarendon Press, Oxford, 1998.
    [11] E. CasasC. Clason and K. Kunisch, Approximation of elliptic control problems in measure spaces with sparse solutions, SIAM J. Control Optim., 50 (2012), 1735-1752.  doi: 10.1137/110843216.
    [12] _____, Parabolic control problems in measure spaces with sparse solutions, SIAM J. Control Optim., 51 (2013), 28–63. doi: 10.1137/120872395.
    [13] E. Casas and K. Kunisch, Optimal control of semilinear elliptic equations in measure spaces, SIAM J. Control Optim., 52 (2014), 339-364.  doi: 10.1137/13092188X.
    [14] _____, Parabolic control problems in space-time measure spaces, ESAIM Control Optim. Calc. Var., 22 (2016), 355–376.
    [15] E. CasasB. Vexler and E. Zuazua, Sparse initial data indentification for parabolic pde and its finite element approximations, Math. Control Relat. Fields, 5 (2015), 377-399.  doi: 10.3934/mcrf.2015.5.377.
    [16] E. Casas and E. Zuazua, Spike controls for elliptic and parabolic PDEs, Systems Control Lett., 62 (2013), 311-318.  doi: 10.1016/j.sysconle.2013.01.001.
    [17] P. Cembranos and J. Mendoza, Banach Spaces of Vector-Valued Functions, Lect. Notes in Math., 1676, Springer, Berlin, 1997.
    [18] C. Clason and K. Kunisch, A duality-based approach to elliptic control problems in non-reflexive Banach spaces, ESAIM Control Optim. Calc. Var., 17 (2011), 243-266.  doi: 10.1051/cocv/2010003.
    [19] _____, A measure space approach to optimal source placement, Comp. Optim. Appl. , 53 (2011), 155–171.
    [20] R. E. Edwards, Functional Analysis: Theory and Applications, Holt, Rinehart and Winston, New York, 1965.
    [21] C. Fabre and J.-P. Puel, Pointwise controllability as limit of internal controllability for the wave equation in one space dimension, Portugaliae Mathematica, 51 (1994), 335-350. 
    [22] M. Fornasier and H. Rauhut, Recovery algorithms for vector-valued data with joint sparsity constraints, SIAM J. Numer. Anal., 46 (2008), 577-613.  doi: 10.1137/0606668909.
    [23] D. A. French and T.E. Peterson, A continuous space-time finite element method for the wave equation, Math. Comp., 65 (1996), 491-506.  doi: 10.1090/S0025-5718-96-00685-0.
    [24] M. GugatA. Keimer and G. Leugering, Optimal distributed control of the wave equation subject to state constraints, ZAMM Z. Angew. Math. Mech., 89 (2009), 420-444.  doi: 10.1002/zamm.200800196.
    [25] M. GugatE. Trélat and E. Zuazua, Optimal Neumann control for the 1D wave equation: Finite horizon, infinite horizon, boundary tracking terms and the turnpike property, Systems Control Lett., 90 (2016), 61-70.  doi: 10.1016/j.sysconle.2016.02.001.
    [26] R. HerzogG. Stadler and G. Wachsmuth, Directional sparsity in optimal control of partial differential equations, SIAM J. Control Optim., 50 (2012), 943-963.  doi: 10.1137/100815037.
    [27] M. Hinze, A variational discretization concept in control constrained optimization: The linear quadratic case, Comput. Optim. Appl., 30 (2005), 45-61.  doi: 10.1007/s10589-005-4559-5.
    [28] L. V. Kantorovich and G. P. Akilov, Functional Analysis, Pergamon Press, Oxford, 1982.
    [29] A. Kröner, Adaptive finite element methods for optimal control of second order hyperbolic equations, Comput. Methods Appl. Math., 11 (2011), 214-240. 
    [30] _____, Semi-smooth Newton methods for optimal control of the dynamical Lamé system with control constraints, Numer. Funct. Anal. Optim., 34 (2013), 741–769. doi: 10.1080/01630563.2013.772423.
    [31] A. Kröner and K. Kunisch, A minimum effort optimal control problem for the wave equation, Comput. Optim. Appl., 57 (2014), 241-270.  doi: 10.1007/s10589-013-9587-y.
    [32] A. KrönerK. Kunisch and B. Vexler, Semismooth Newton methods for optimal control of the wave equation with control constraints, SIAM J. Control Optim., 49 (2011), 830-858.  doi: 10.1137/090766541.
    [33] K. KunischK. Pieper and B. Vexler, Measure valued directional sparsity for parabolic optimal control problems, SIAM J. Control Optim., 52 (2014), 3078-3108.  doi: 10.1137/140959055.
    [34] K. KunischP. Trautmann and B. Vexler, Optimal control of the undamped linear wave equation with measure valued controls, SIAM J. Control Optim., 54 (2016), 1212-1244.  doi: 10.1137/141001366.
    [35] K. Kunisch and D. Wachsmuth, On time optimal control of the wave equation and its numerical realization as parametric optimization problem, SIAM J. Control Optim., 51 (2013), 1232-1262.  doi: 10.1137/120877520.
    [36] I. Lasiecka and J. Sokolowski, Sensitivity analysis of optimal control problems for wave equations, SIAM J. Control Optim., 29 (1991), 1128-1149.  doi: 10.1137/0329060.
    [37] J. Lions, Control of Distributed Singular Systems, 13. Gauthier-Villars, Montrouge, 1983.
    [38] J. L. Lions and E. Magenes, Non-homogeneous Boundary Value Problems and Applications, vol. 1, Springer Berlin, 1972.
    [39] A. Milzarek and M. Ulbrich, A semismooth Newton method with multidimensional filter globalization for l1-optimization, SIAM J. Optim., 24 (2014), 298-333.  doi: 10.1137/120892167.
    [40] B.S. Mordukhovich and J.-P. Raymond, Dirichlet boundary control of hyperbolic equations in the presence of state constraints, Appl. Math. Optim., 49 (2004), 145-157.  doi: 10.1007/BF02638149.
    [41] _____, Neumann boundary control of hyperbolic equations with pointwise state constraints, SIAM J. Control Optim. , 43 (2004/05), 1354–1372. doi: 10.1137/S0363012903431177.
    [42] S. M. Nikolskii, Approximation of Functions of Several Variables and Imbedding Theorems, Springer, Berlin, 1975.
    [43] K. Pieper, Finite Element Discretization and Efficient Numerical Solution of Elliptic and Parabolic Sparse Control Problems, PhD thesis, TU Munich, 2015.
    [44] K. Pieper, P. Trautmann, B. Tang Quoc and D. Walter, Inverse point source location for the helmholtz equation, Submitted.
    [45] K. Pieper and B. Vexler, A priori error analysis for discretization of sparse elliptic optimal control problems in measure space, SIAM J. Control Optim., 51 (2013), 2788-2808.  doi: 10.1137/120889137.
    [46] A. R. Raymond, Introduction to Tensor Products of Banach Spaces, Springer, New York, 2002.
    [47] A. A. Samarskii, The Theory of Difference Schemes, Marcel Dekker, New York-Basel, 2001.
    [48] H. Triebel, Interpolation Theory, Function Spaces, Differential Operators, vol. 18 of NorthHolland Mathematical Library, North-Holland Publishing Co., Amsterdam-New York, 1978.
    [49] A. A. Zlotnik, Projective-difference Schemes for Nonstationary Problems with Nonsmooth Data, PhD thesis, Lomonosov Moscow State University, 1979 (in Russian).
    [50] _____, Lower error estimates for three-layer difference methods of solving the wave equation with data from hölder spaces, Math. Notes, 51 (1992), 321–323.
    [51] _____, Convergence Rate Estimates of Finite-Element Methods for Second Order Hyperbolic Equations, in Numerical methods and applications, G. I. Marchuk, ed., CRC Press, Boca Raton, FL, 1994,155–220.
    [52] E. Zuazua, Optimal and approximate control of finite-difference approximation schemes for the 1D wave equation, Rend. Mat. Appl., 24 (2004), 201-237. 
  • 加载中



Article Metrics

HTML views(912) PDF downloads(267) Cited by(0)

Access History

Other Articles By Authors



    DownLoad:  Full-Size Img  PowerPoint