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Real-Time Optimization for Large Scale Processes: Nonlinear Model Predictive Control of a High Purity Distillation Column

  • Moritz Diehl
  • Ilknur Uslu
  • Rolf Findeisen
  • Stefan Schwarzkopf
  • Frank Allgöwer
  • H. Georg Bock
  • Tobias Bürner
  • Ernst Dieter Gilles
  • Achim Kienle
  • Johannes P. Schlöder
  • Erik Stein
Chapter

Abstract

The purpose of this paper is an experimental proof-of-concept of the application of NMPC for large scale systems using specialized dynamic optimization strategies. For this aim we investigate the application of modern, computationally efficient NMPC schemes and realtime optimization techniques to a nontrivial process control example, namely the control of a high purity binary distillation column. All necessary steps are discussed, from formulation of a DAE model with 164 states up to the final application to the experimental apparatus. Especially an efficient real-time optimization scheme based on the direct multiple shooting method is introduced. It is characterized by an initial value embedding strategy, that allows to immediately respond to disturbances, and real-time iterations, that dovetail the optimization iterations with the real process development. Using this scheme, sampling times of 10 seconds are feasible on a standard PC. This shows that an efficient NMPC scheme based on large scale DAE models is feasible for the real-time control of a pilot scale distillation column.

Keywords

Extend Kalman Filter Model Predictive Control Distillation Column Manipulate Variable Distribute Control System 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • Moritz Diehl
    • 1
  • Ilknur Uslu
    • 2
  • Rolf Findeisen
    • 3
  • Stefan Schwarzkopf
    • 2
  • Frank Allgöwer
    • 3
  • H. Georg Bock
    • 1
  • Tobias Bürner
    • 1
  • Ernst Dieter Gilles
    • 2
    • 4
  • Achim Kienle
    • 4
  • Johannes P. Schlöder
    • 1
  • Erik Stein
    • 4
  1. 1.Interdisziplinäres Zentrum für wissenschaftliches RechnenUniversität HeidelbergGermany
  2. 2.Institut für Systemdynamik und Regelungstechnik (ISR)Universität StuttgartGermany
  3. 3.Institut für Systemtheorie technischer Prozesse (IST)Universität StuttgartGermany
  4. 4.Max-Planck-Institut für Dynamik komplexer technischer SystemeMagdeburgGermany

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