Optimization methods for Dirichlet control problems. (4th May 2018)

• Record Type: Journal Article
• Authors: Mateos, Mariano
• Is Part Of: Optimization. Volume 67:Number 5(2018)
• Page Start: 585
• Page End: 617
• Publication Date: 2018-05-04
• Subjects: Dirichlet optimal control -- discretization -- constrained optimization -- preconditionate conjugate gradient -- semismooth Newton methods; Mathematical optimization -- Periodicals; 519.7
• DOI: 10.1080/02331934.2018.1426578
• Languages: English
• ISSNs: 0233-1934

Abstract

Abstract: We discuss several optimization procedures to solve finite element approximations of linear-quadratic Dirichlet optimal control problems governed by an elliptic partial differential equation posed on a 2D or 3D Lipschitz domain. The control is discretized explicitly using continuous piecewise linear approximations. Unconstrained, control-constrained, state-constrained and control-and-state constrained problems are analysed. A preconditioned conjugate method for a reduced problem in the control variable is proposed to solve the unconstrained problem, whereas semismooth Newton methods are discussed for the solution of constrained problems. State constraints are treated via a Moreau–Yosida penalization. Convergence is studied for both the continuous problems and the finite dimensional approximations. In the finite dimensional case, we are able to show convergence of the optimization procedures even in the absence of Tikhonov regularization parameter. Computational aspects are also treated and several numerical examples are included to illustrate the theoretical results.