Control of an elliptic problem with pointwise state constraints
SIAM Journal on Control and Optimization
SIAM Journal on Control and Optimization
On Moment Theory and Controllability of One-Dimensional Vibrating Systems and Heating Processes
On Moment Theory and Controllability of One-Dimensional Vibrating Systems and Heating Processes
On the Boundary Control of Systems of Conservation Laws
SIAM Journal on Control and Optimization
Regularization of L∞-Optimal Control Problems for Distributed Parameter Systems
Computational Optimization and Applications
Regular Lagrange Multipliers for Control Problems with Mixed Pointwise Control-State Constraints
SIAM Journal on Optimization
Lp-Optimal Boundary Control for the Wave Equation
SIAM Journal on Control and Optimization
Optimal Control of PDEs with Regularized Pointwise State Constraints
Computational Optimization and Applications
Smoothed penalty algorithms for optimization of nonlinear models
Computational Optimization and Applications
Exact Controllability for Multidimensional Semilinear Hyperbolic Equations
SIAM Journal on Control and Optimization
Optimal Energy Control in Finite Time by varying the Length of the String
SIAM Journal on Control and Optimization
Mathematics and Computers in Simulation
Optimization Methods & Software
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We consider a system that is governed by a PDE of hyperbolic type, namely, the wave equation, and is controlled by a Dirichlet boundary control. For the penalization of terminal constraints, we compare the convergence of three penalization techniques: a differentiable penalty method, an exact penalization, and a smoothed exact penalization. The error of the solution of the differentiably penalized problem is at most of the order $1/\sqrt{\gamma}$, where $\gamma$ is the penalty parameter. The exact penalization yields the exact solution if $\gamma$ is sufficiently large. If $\gamma$ is sufficiently large for the smoothed exact penalization, we obtain an error bound of the order $1/\sqrt{\beta}$, where $\beta$ is the additional smoothing parameter. This method yields differentiable objective functions that remain uniformly strongly convex, since $\gamma$ need not tend to infinity to obtain convergence. We also consider the penalization of distributed inequality state constraints that prescribe an upper bound for the $L^\infty$-norm of the state. We prove the convergence with respect to the $L^2$-norm for a penalization of the constraint violation measured in the $L^1$-norm. We use this penalization technique to prove the existence of optimal controls for the inequality state constrained problem.