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Robust Process Control by Dynamic Stochastic Programming

Please always quote using this URN: urn:nbn:de:0297-zib-7959
  • Unnecessarily conservative behavior of standard process control techniques can be avoided by stochastic programming models when the distribution of random disturbances is known. In an earlier study we have investigated such an approach for tank level constraints of a distillation process. Here we address techniques that have accelerated the numerical solution of the large and expensive stochastic programs by a factor of six, and then present a refined optimization model for the same application.

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Metadaten
Author:Marc Steinbach
Document Type:ZIB-Report
Tag:Process control; multistage stochastic program; random disturbance; relatively complete recourse; tree-sparse NLP
MSC-Classification:90-XX OPERATIONS RESEARCH, MATHEMATICAL PROGRAMMING / 90Cxx Mathematical programming [See also 49Mxx, 65Kxx] / 90C06 Large-scale problems
90-XX OPERATIONS RESEARCH, MATHEMATICAL PROGRAMMING / 90Cxx Mathematical programming [See also 49Mxx, 65Kxx] / 90C15 Stochastic programming
93-XX SYSTEMS THEORY; CONTROL (For optimal control, see 49-XX) / 93Cxx Control systems / 93C15 Systems governed by ordinary differential equations [See also 34H05]
93-XX SYSTEMS THEORY; CONTROL (For optimal control, see 49-XX) / 93Cxx Control systems / 93C95 Applications
Date of first Publication:2004/06/02
Series (Serial Number):ZIB-Report (04-20)
ZIB-Reportnumber:04-20
Published in:Appeared in : Proc. Appl. Math. Mech. (4)1, (2004) 11-14
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