Abstract
In Neitzel et al. (Strategies for time-dependent PDE control using an integrated modeling and simulation environment. Part one: problems without inequality constraints. Technical Report 408, Matheon, Berlin, 2007) we have shown how time-dependent optimal control for partial differential equations can be realized in a modern high-level modeling and simulation package. In this article we extend our approach to (state) constrained problems. “Pure” state constraints in a function space setting lead to non-regular Lagrange multipliers (if they exist), i.e. the Lagrange multipliers are in general Borel measures. This will be overcome by different regularization techniques. To implement inequality constraints, active set methods and barrier methods are widely in use. We show how these techniques can be realized in a modeling and simulation package. We implement a projection method based on active sets as well as a barrier method and a Moreau Yosida regularization, and compare these methods by a program that optimizes the discrete version of the given problem.
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Ira Neitzel’s research was supported by the DFG Schwerpunktprogramm SPP 1253.
Uwe Prüfert’s research was supported by the DFG Research Center Matheon.
Thomas Slawig’s research was supported by the DFG Cluster of Excellence The Future Ocean and the DFG Schwerpunktprogramm SPP 1253.
Website www.math.tu-berlin.de/Strategies-for-time-dependent-PDE-control.html
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Neitzel, I., Prüfert, U. & Slawig, T. Strategies for time-dependent PDE control with inequality constraints using an integrated modeling and simulation environment. Numer Algor 50, 241–269 (2009). https://doi.org/10.1007/s11075-008-9225-4
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DOI: https://doi.org/10.1007/s11075-008-9225-4