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Real-Time Optimization and Nonlinear Model Predictive Control of
Processes Goverened by Differential-Algebraic Equations
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Author(s):
H. G. Bock, M. Diehl, J. P. Schlöder, F. Allgöwer, R. Findeisen,
Z. Nagy
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Publication Info:
Proc. Int. Symp. Adv. Control of Chemical Processes, ADCHEM, 2000,
Pisa, pp. 695-703
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Abstract:
Optimization problems in chemical engineering often involve complex
systems of nonlinear DAE as the model equations. The direct multiple
shooting method has been known for a while as a fast off-line method
for optimization problems in ODE and later in DAE. Some factors
crucial for its fast performance are briefly reviewed.
Recently, this approach has been successfully adapted to the specific
requirements of real-time optimization. Special strategies have been
developed to effectively minimize the on-line computational effort, in
which the progress of the optimization iterations is nested with the
progress of the process. They use precalculated information as far as
possible (e.g. Hessians, gradients and QP presolves for iterated
reference trajectories) to minimize response time in case of
perturbations. In typical real-time problems they have proven much
faster than fast off-line strategies.
Nonlinear Model Predictive Control (NMPC) may be interpreted as a
special real-time optimization problem. Strategies to exploit the
similarities between subsequent NMPC optimization problems are
described. Numerical results for the NMPC of a high-purity
distillation column subject to parameter disturbances are
presented.
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Date:
April 2000
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Type of Publication:
Internal Report 2000-6
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Publisher/Supervisor:
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File Download:
ps,
pdf
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Universität Stuttgart