LFU:online

Upon successful completion of the course, students understand selected mathematical tools for addressing certain classes of optimization problems involving parameters or control functions. They are able to identify selected optimization techniques in order to solve specific control problems. They are also able to deploy these techniques, and proceed with the practical solving of these optimization problems. 

The course covers an essential set of mathematical techniques for addressing optimal control problems such as stabilization problems, parameter identification problems, learning problems (machine learning) and feedback control problems in the context of dynamical systems, in a large sense. This contains in particular the Lagrangian techniques, adjoint methods, design of feedback operators, model-order reduction methods, gradient methods, machine learning problems and sparsity techniques. The approach will rely on the study of examples in order to explain how the methods aforementioned can help us to solve a large class of optimization problems constrained with discrete or continuous dynamical systems.

Lehrveranstaltungsprüfung gemäß § 7 Satzungsteil, Studienrechtliche Bestimmungen