POD-Galerkin Model Order Reduction for Parametrized Time Dependent Linear Quadratic Optimal Control Problems in Saddle Point Formulation

Understand

In this work we recast parametrized time dependent optimal control problems governed by partial differential equations in a saddle point formulation and we propose reduced order methods as an effective strategy to solve them.

• Indeed, on one hand parametrized time dependent optimal control is a very powerful mathematical model which is able to describe several physical phenomena; on the other hand, it requires a huge computational effort.
• Reduced order methods are a suitable approach to have rapid and accurate simulations.
• We rely on POD-Galerkin reduction over the physical and geometrical parameters of the optimality system in a space-time formulation.