Reduced Order Model based Multiobjective Optimal Control of Fluids (INVITED)

Abstract eng:
In this article, we show how to combine reduced order modeling and multiobjective optimal control techniques in order to efficiently solve multiobjective optimal control problems constrained by PDEs. Using Galerkin projection and Proper Orthogonal Decomposition (POD), the underlying PDE is replaced by a system of ordinary differential equations, thereby drastically reducing the computational effort. We develop a gradient based algorithm by using an adjoint approach in combination with a scalarization method and the numerical results are illustrated with the example of the two-dimensional incompressible flow around a cylinder.

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