We consider the optimal control of elastic contact problems in the regime of finite deformations. We derive a result on existence of optimal solutions and propose a regularization of the contact constraints by a penalty formulation. Subsequential convergence of sequences of solutions of the regularized problem to original solutions is studied. Based on these results, a numerical path-following scheme is constructed and its performance is tested.

Optimal control of hyperelastic contact problems in the regime of finite strains combines various severe theoretical and algorithmic difficulties. Apart from being large scale, the main source of difficulties is the high nonlinearity and non-convexity of the elastic energy functional which precludes uniqueness of solutions and simple local sensitivity results. In addition, the contact conditions add non-smoothness to the overall problem.In this paper, we discuss algorithmic approaches to address these issues. In particular, the non-smoothness is tackled by a path-following approach, whose theoretical properties are reviewed. The subproblems are highly nonlinear optimal control problems, which can be solved by an affine invariant composite step method. For increased robustness and efficiency this method has to be adapted to the particular problem, taking into account its large scale nature, its function space structure and its non-convexity.

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We consider a linear iterative solver for large scale linearly constrained quadratic minimization problems that arise, for example, in optimization with PDEs. By a primal-dual projection (PDP) iteration, which can be interpreted and analysed as a gradient method on a quotient space, the given problem can be solved by computing sulutions for a sequence of constrained surrogate problems, projections onto the feasible subspaces, and Lagrange multiplier updates. As a major application we consider a class of optimization problems with PDEs, where PDP can be applied together with a projected cg method using a block triangular constraint preconditioner. Numerical experiments show reliable and competitive performance for an optimal control problem in elasticity.