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Steady‐state process optimization with guaranteed robust stability and feasibility
Author(s) -
Mönnigmann M.,
Marquardt W.
Publication year - 2003
Publication title -
aiche journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.958
H-Index - 167
eISSN - 1547-5905
pISSN - 0001-1541
DOI - 10.1002/aic.690491212
Subject(s) - robustness (evolution) , flexibility (engineering) , parametric statistics , mathematical optimization , stability (learning theory) , robust optimization , context (archaeology) , optimization problem , control theory (sociology) , process (computing) , computer science , measure (data warehouse) , constraint (computer aided design) , boundary (topology) , mathematics , paleontology , biochemistry , chemistry , statistics , geometry , control (management) , mathematical analysis , database , machine learning , artificial intelligence , biology , gene , operating system
A new approach is presented to the optimization based design of continuous processes in the presence of parametric uncertainty. In contrast to previous works focusing on process feasibility, it allows to consider both feasibility and stability of the process in the presence of parametric uncertainty. The new approach, therefore, permits an integrated treatment of steady‐state flexibility and robust stability in the optimization of continuous processes. The process optimization problem is extended by constraints that ensure a lower bound on the distance of the nominal point of operation to stability and feasibility boundaries in the space of the uncertain parameters. While previous approaches are based on evaluating constraint violation in the range space of the constraints, the measure for flexibility and robustness used here is given in the domain space of the uncertain parameters. The method is discussed in the context of existing approaches to flexibility in process optimization and is illustrated with a continuous polymerization which is known to have a nontrivial stability boundary resulting from multiple steady states and sustained oscillations.