Lavrentiev-prox-regularization for optimal control of PDEs with state constraints
نویسنده
چکیده
A Lavrentiev prox-regularization method for optimal control problems with pointwise state constraints is introduced where both the objective function and the constraints are regularized. The convergence of the controls generated by the iterative Lavrentiev prox-regularization algorithm is studied. For a sequence of regularization parameters that converges to zero, strong convergence of the generated control sequence to the optimal control is proved. Due to the proxcharacter of the proposed regularization, the feasibility of the iterates for a given parameter can be improved compared with the non-prox Lavrentiev-Regularization. Mathematical subject classification: 49J20, 49M37.
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