Multiple Set Point Partially Reduced SQP Method for Optimal Control of PDE

H. G. Bock, E. Kostina, A. Schäfer, J. P. Schlöder and V. Schulz
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H. G. Bock: Universität Heidelberg, Interdisziplinäres Zentrum für Wissenschaftliches Rechnen (IWR)
E. Kostina: Universität Heidelberg, Interdisziplinäres Zentrum für Wissenschaftliches Rechnen (IWR)
A. Schäfer: Universität Heidelberg, Interdisziplinäres Zentrum für Wissenschaftliches Rechnen (IWR)
J. P. Schlöder: Universität Heidelberg, Interdisziplinäres Zentrum für Wissenschaftliches Rechnen (IWR)
V. Schulz: Universität Trier, FB IV - Mathematik

A chapter in Reactive Flows, Diffusion and Transport, 2007, pp 147-175 from Springer

Abstract: Summary Optimization of dynamic processes described by partial differential-algebraic equations (PDAE) is a challenging task due to dimension and complexity of the problems. Fast solutions methods are achieved by using a simultaneous approach for a close coupling of the optimization aspect of the overall algorithm with the solution method of the dynamic system. Especially using partially reduced sequential quadratic programming (PRSQP) approaches reduces the computational complexity while still being able to incorporate inequality constraints. An effective and straightforward generalization of the methods to treat optimization tasks modeled as multiple set point optimization problems is shown. Based on the simultaneous approach for optimization problems in NMPC an efficient real-time iteration technique is developed. As industrial applications we present shape optimization of turbine blades, operation optimization of a catalytic tube reactor and the real-time optimization of a continuous distillation column.

Keywords: Turbine Blade; Multiple Shooting; Sequential Quadratic Programming; Path Constraint; Sequential Quadratic Programming Method (search for similar items in EconPapers)
Date: 2007
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DOI: 10.1007/978-3-540-28396-6_7

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