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Real-Time optimization based on adaptation of surrogate models
Publikationstyp
Conference Paper
Date Issued
2016
Sprache
English
Author(s)
Journal
Volume
49
Issue
7
Start Page
412
End Page
417
Citation
IFAC-PapersOnLine 49 (7): 412-417 (2016)
Contribution to Conference
Publisher DOI
Scopus ID
Publisher
Elsevier
Recently, different real-time optimization (RTO) schemes that guarantee feasibility of all RTO iterates and monotonic convergence to the optimal plant operating point have been proposed. However, simulations reveal that these schemes converge very slowly to the plant optimum, which may be prohibitive in applications. This note proposes an RTO scheme based on second-order surrogate models of the objective and the constraints, which enforces feasibility of all RTO iterates, i.e., plant constraints are satisfied at all iterations. In order to speed up convergence, we suggest an online adaptation strategy of the surrogate models that is based on trust-region ideas. The efficacy of the proposed RTO scheme is demonstrated in simulations via both a numerical example and the steady-state optimization of the Williams-Otto reactor.
Subjects
online adaptation
plant feasibility
plant-model mismatch
real-time optimization
DDC Class
004: Computer Sciences
621: Applied Physics