Gugat M (2009)
Publication Language: English
Publication Type: Journal article, Original article
Publication year: 2009
Publisher: Sociedade Brasileira de Matemática Aplicada e Computacional
Book Volume: 28
Pages Range: 231-257
Journal Issue: 2
DOI: 10.1590/S1807-03022009000200006
Open Access Link: http://www.scielo.br/scielo.php?pid=S1807-03022009000200006&script=sci_arttext&tlng=es
A Lavrentiev prox-regularization method for optimal control problems with point-wise 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. © 2009 Sociedade Brasileira de Matemática Aplicada e Computacional.
APA:
Gugat, M. (2009). Lavrentiev-prox-regularization for optimal control of PDEs with state constraints. Computational and Applied Mathematics, 28(2), 231-257. https://doi.org/10.1590/S1807-03022009000200006
MLA:
Gugat, Martin. "Lavrentiev-prox-regularization for optimal control of PDEs with state constraints." Computational and Applied Mathematics 28.2 (2009): 231-257.
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