Artículo
Convergence Results for Optimal Control Problems Governed by Elliptic Quasivariational Inequalities
Fecha de publicación:
08/2020
Editorial:
Taylor & Francis
Revista:
Numerical Functional Analysis and Optimization
ISSN:
0163-0563
e-ISSN:
1532-2467
Idioma:
Inglés
Tipo de recurso:
Artículo publicado
Clasificación temática:
Resumen
We consider an optimal control problem (Formula presented.) governed by an elliptic quasivariational inequality with unilateral constraints. We associate to (Formula presented.) a new optimal control problem (Formula presented.) obtained by perturbing the state inequality (including the set of constraints and the nonlinear operator) and the cost functional, as well. Then, we provide sufficient conditions which guarantee the convergence of solutions of Problem (Formula presented.) to a solution of Problem (Formula presented.) The proofs are based on convergence results for elliptic quasivariational inequalities, obtained by using arguments of compactness, lower semicontinuity, monotonicity, penalty and various estimates. Finally, we illustrate the use of the abstract convergence results in the study of optimal control associated with two boundary value problems. The first one describes the equilibrium of an elastic body in frictional contact with an obstacle, the so-called foundation. The process is static and the contact is modeled with normal compliance and unilateral constraint, associated to a version of Coulomb’s law of dry friction. The second one describes a stationary heat transfer problem with unilateral constraints. For the two problems we prove existence, uniqueness and convergence results together with the corresponding physical interpretation.
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Articulos(CCT - ROSARIO)
Articulos de CTRO.CIENTIFICO TECNOL.CONICET - ROSARIO
Articulos de CTRO.CIENTIFICO TECNOL.CONICET - ROSARIO
Citación
Sofonea, Mircea; Tarzia, Domingo Alberto; Convergence Results for Optimal Control Problems Governed by Elliptic Quasivariational Inequalities; Taylor & Francis; Numerical Functional Analysis and Optimization; 41; 11; 8-2020; 1326-1351
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