POD basis updates for nonlinear PDE control

2017 ◽  
Vol 65 (5) ◽  
Author(s):  
Carmen Gräßle ◽  
Martin Gubisch ◽  
Simone Metzdorf ◽  
Sabrina Rogg ◽  
Stefan Volkwein

AbstractIn the present paper a semilinear boundary control problem is considered. For its numerical solution proper orthogonal decomposition (POD) is applied. POD is based on a Galerkin type discretization with basis elements created from the evolution problem itself. In the context of optimal control this approach may suffer from the fact that the basis elements are computed from a reference trajectory containing features which are quite different from those of the optimally controlled trajectory. Therefore, different POD basis update strategies which avoid this problem of unmodelled dynamics are compared numerically.

Author(s):  
A Zare ◽  
H Emdad ◽  
E Goshtasbirad

The purpose of this article is to design a reduced order model based on the proper orthogonal decomposition/Galerkin projection and perturbation method to develop a non-autonomous model. The resulting model can be used in optimal control of flow over backward-facing step. The main disadvantage of the proper orthogonal decomposition approach for control purposes is that, controlling parameters or inputs do not show up explicitly in the resulting reduced order system. The perturbation method can solve this problem and insert control inputs in the resulting system. The resulting system captures the time-varying influence of the controlling parameters and precisely predicts the Navier–Stokes response to external excitations. At last, optimal control theory is introduced to design a control law for a non-linear forced reduced model, which attempts to minimize the vorticity content in the fluid domain. The test bed is laminar flow behind backward-facing step [Formula: see text] actuated by a pair of blowing/suction jets. Results show that the wall jet can significantly influence the flow field and delay separation, while the perturbation method can predict the flow field in an accurate manner. The method is also found to be fast and efficient in computational time.


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