Towards Nonlinear Model-Based Predictive Optimal Control of Large-Scale Process Models with Application to Air Separation Plants

Thomas Kronseder, Oskar von Stryk, Roland Bulirsch and Andreas Kröner
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Thomas Kronseder: Technische Universität München, Lehrstuhl für Höhere Mathematik und Numerische Mathematik
Oskar von Stryk: Technische Universität Darmstadt, Fachgebiet Simulation und Systemoptimierung
Roland Bulirsch: Technische Universität München, Lehrstuhl für Höhere Mathematik und Numerische Mathematik
Andreas Kröner: Linde AG, Process Engineering and Contracting Division

A chapter in Online Optimization of Large Scale Systems, 2001, pp 385-410 from Springer

Abstract: Abstract We propose a concept for model predictive control of large-scale dynamical systems. This concept has been designed for the optimal control of chemical engineering processes, in particular for cryogenic air separation plants which are modelled by large systems of coupled differential and algebraic equations of (differential) index two with state dependent discontinuities. Our concept considers different time scales for various tasks which are prescribed by the real-time nature of the process of interest. In this paper (items refer to Figure 4) the components (a)-(d) and (f) of the general concept are considered in detail. Until now there has been a lack of a clear concept for real-time optimality. Therefore, we conclude by discussing some fundamental issues of the notion of real-time optimality.

Keywords: Optimal Control Problem; Model Predictive Control; Load Change; State Dependent Switching; Sensitivity Transfer (search for similar items in EconPapers)
Date: 2001
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-662-04331-8_21

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DOI: 10.1007/978-3-662-04331-8_21

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