English

Numerical approximation of regularized non-convex elliptic optimal control problems by the finite element method

Optimization and Control 2022-09-26 v1

Abstract

We investigate the numerical approximation of an elliptic optimal control problem which involves a nonconvex local regularization of the LqL^q-quasinorm penalization (with q(0,1)q\in(0,1)) in the cost function. Our approach is based on the \emph{difference-of-convex} function formulation, which leads to first-order necessary optimality conditions, which can be regarded as the optimality system of an auxiliar convex L1L^1-penalized optimal control problem. We consider piecewise-constant finite element approximation for the controls, whereas the state equation is approximated using piecewise-linear basis functions. Then, convergence results are obtained for the proposed approximation. Under certain conditions on the support's boundary of the optimal control, we deduce an order of h12h^\frac12 approximation rate of convergence where hh is the associated discretization parameter. We illustrate our theoretical findings with numerical experiments that show the convergence behavior of the numerical approximation

Keywords

Cite

@article{arxiv.2209.11384,
  title  = {Numerical approximation of regularized non-convex elliptic optimal control problems by the finite element method},
  author = {Pedro Merino and Alexander Nenjer},
  journal= {arXiv preprint arXiv:2209.11384},
  year   = {2022}
}
R2 v1 2026-06-28T01:56:33.917Z