Trust-region proper orthogonal decomposition for flow control

Authors:
E. Arian;M. Fahl;and E.W. Sachs
Affiliations:
-;-;-
Venue:
Trust-region proper orthogonal decomposition for flow control
Year:
2000

Citing 0
Cited 9

Error estimates for abstract linear-quadratic optimal control problems using proper orthogonal decomposition

Computational Optimization and Applications - Special issue: Numerical analysis of optimization in partial differential equations
Optimal control of the cylinder wake in the laminar regime by trust-region methods and POD reduced-order models

Journal of Computational Physics
Error estimates for abstract linear---quadratic optimal control problems using proper orthogonal decomposition

Computational Optimization and Applications
Enablers for robust POD models

Journal of Computational Physics
POD a-posteriori error estimates for linear-quadratic optimal control problems

Computational Optimization and Applications
Reduced-order modeling of transonic flows around an airfoil submitted to small deformations

Journal of Computational Physics
Control of laser surface hardening by a reduced-order approach using proper orthogonal decomposition

Mathematical and Computer Modelling: An International Journal
Reduced order modeling based on POD of a parabolized Navier-Stokes equations model II: Trust region POD 4D VAR data assimilation

Computers & Mathematics with Applications
On the optimal control of the Schlögl-model

Computational Optimization and Applications

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Abstract

The proper orthogonal decomposition (POD) is a model reduction technique for the simulation of physical processes governed by partial differential equations, e.g. fluid flows. It can also be used to develop reduced order control models. Fundamental is the computation of POD basis functions that represent the influence of the control action on the system in order to get a suitable control model. We present an approach where suitable reduced order models are derived successively and give global convergence results.