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Improved directional derivatives for modifier-adaptation schemes
Publikationstyp
Conference Paper
Date Issued
2017
Sprache
English
Author(s)
Journal
Volume
50
Issue
1
Start Page
5718
End Page
5723
Citation
IFAC-PapersOnLine 50 (1): 5718-5723 (2017)
Contribution to Conference
Publisher DOI
Scopus ID
Publisher
Elsevier
Modifier adaptation enables the real-time optimization (RTO) of plant operation in the presence of considerable plant-model mismatch. For this, modifier adaptation requires the estimation of plant gradients, which is experimentally expensive as this might involves several online experiments. Recently, a directional modifier-adaptation approach has been proposed, which uses the process model to compute offline a subset of input directions that are critical for plant optimization. This allows estimating directional derivatives only in the critical directions instead of full gradients, thereby reducing the burden of gradient estimation. However, in certain cases such as change of active constraints and large parametric uncertainties, directional modifier adaptation may lead to significant suboptimality. Here, we propose an extension to directional modifier adaptation, whereby, at each RTO iteration, we compute a set of critical directions that are robust to large parametric perturbations. We draw upon a simulation study of the run-to-run optimization of the Williams-Otto semi-batch reactor to illustrate the performance of the proposed extension.
Subjects
directional gradient estimation
modifier adaptation
real-time optimization
DDC Class
004: Computer Sciences
510: Mathematics