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SIAM Journal on Scientific Computing
The Primal-Dual Active Set Method for Nonlinear Optimal Control Problems with Bilateral Constraints
SIAM Journal on Control and Optimization
Semismooth Newton and Augmented Lagrangian Methods for a Simplified Friction Problem
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Interior Point Methods in Function Space
SIAM Journal on Control and Optimization
On Effective Methods for Implicit Piecewise Smooth Surface Recovery
SIAM Journal on Scientific Computing
Modeling and numerical study of actuator and sensor effects for a laminated piezoelectric plate
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Feasible and Noninterior Path-Following in Constrained Minimization with Low Multiplier Regularity
SIAM Journal on Control and Optimization
A sparse proximal implementation of the LP dual active set algorithm
Mathematical Programming: Series A and B
Computational Optimization and Applications
SIAM Journal on Matrix Analysis and Applications
Karush-Kuhn-Tucker Conditions for Nonsmooth Mathematical Programming Problems in Function Spaces
SIAM Journal on Control and Optimization
Directional Sparsity in Optimal Control of Partial Differential Equations
SIAM Journal on Control and Optimization
Approximation of sparse controls in semilinear elliptic equations
LSSC'11 Proceedings of the 8th international conference on Large-Scale Scientific Computing
A measure space approach to optimal source placement
Computational Optimization and Applications
Computational Optimization and Applications
Computational Optimization and Applications
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Elliptic optimal control problems with L 1-control cost are analyzed. Due to the nonsmooth objective functional the optimal controls are identically zero on large parts of the control domain. For applications, in which one cannot put control devices (or actuators) all over the control domain, this provides information about where it is most efficient to put them. We analyze structural properties of L 1-control cost solutions. For solving the non-differentiable optimal control problem we propose a semismooth Newton method that can be stated and analyzed in function space and converges locally with a superlinear rate. Numerical tests on model problems show the usefulness of the approach for the location of control devices and the efficiency of our algorithm.