A Joint Tikhonov Regularization and Augmented Lagrange Approach for Ill-posed State Constrained Control Problems with Sparse Controls

TL;DR

This paper introduces a combined Tikhonov regularization and augmented Lagrange method to effectively solve ill-posed state-constrained elliptic optimal control problems with sparse controls, ensuring convergence and stability.

Contribution

It develops a novel coupling of Tikhonov regularization with an augmented Lagrange approach, guaranteeing bounded multipliers and strong convergence in sparse control problems.

Findings

Proves strong convergence of controls and states.

Demonstrates boundedness of multipliers.

Validates method through numerical examples.

Abstract

We provide a modified augmented Lagrange method coupled with a Tikhonov regularization for solving ill-posed state-constrained elliptic optimal control problems with sparse controls. We consider a linear quadratic optimal control problem without any additional $L^2$ regularization terms. The sparsity is guaranteed by an additional $L^1$ term. Here, the modification of the classical augmented Lagrange method guarantees us uniform boundedness of the multiplier that corresponds to the state constraints. We present a coupling between the regularization parameter introduced by the Tikhonov regularization and the penalty parameter from the augmented Lagrange method, which allows us to prove strong convergence of the controls and their corresponding states. Moreover convergence results proving the weak convergence of the adjoint state and weak*-convergence of the multiplier are provided. Finally, we demonstrate our method in several numerical examples.