Numerical approximation of control problems of non-monotone and non-coercive semilinear elliptic equations

Author:

Casas Eduardo,Mateos Mariano,Rösch Arnd

Abstract

AbstractWe analyze the numerical approximation of a control problem governed by a non-monotone and non-coercive semilinear elliptic equation. The lack of monotonicity and coercivity is due to the presence of a convection term. First, we study the finite element approximation of the partial differential equation. While we can prove existence of a solution for the discrete equation when the discretization parameter is small enough, the uniqueness is an open problem for us if the nonlinearity is not globally Lipschitz. Nevertheless, we prove the existence and uniqueness of a sequence of solutions bounded in $$L^\infty (\varOmega )$$ L ( Ω ) and converging to the solution of the continuous problem. Error estimates for these solutions are obtained. Next, we discretize the control problem. Existence of discrete optimal controls is proved, as well as their convergence to solutions of the continuous problem. The analysis of error estimates is quite involved due to the possible non-uniqueness of the discrete state for a given control. To overcome this difficulty we define an appropriate discrete control-to-state mapping in a neighbourhood of a strict solution of the continuous control problem. This allows us to introduce a reduced functional and obtain first order optimality conditions as well as error estimates. Some numerical experiments are included to illustrate the theoretical results.

Funder

Universidad de Oviedo

Publisher

Springer Science and Business Media LLC

Subject

Applied Mathematics,Computational Mathematics

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Non-coercive Neumann Boundary Control Problems;Results in Mathematics;2024-08-17

2. On an optimal control problem of the Leray-α model;Journal of Computational and Applied Mathematics;2024-01

3. Finite element error analysis of affine optimal control problems;ESAIM: Control, Optimisation and Calculus of Variations;2024

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