On handling cost gradient uncertainty in real-time optimization

Publikationstyp
Conference Paper
Date Issued
2015
Sprache
English
Author(s)
Singhal, Martand
Faulwasser, Timm  
Bonvin, Dominique  
TORE-URI
https://hdl.handle.net/11420/46153
Journal
IFAC-PapersOnLine  
Volume
28
Issue
8
Start Page
176
End Page
181
Citation
IFAC-PapersOnLine 28 (8): 176-181 (2015)
Contribution to Conference
9th IFAC Symposium on Advanced Control of Chemical Processes, ADCHEM 2015  
Publisher DOI
10.1016/j.ifacol.2015.08.177
Scopus ID
2-s2.0-84992488095
Publisher
Elsevier
This paper deals with the real-time optimization of uncertain plants and proposes an approach based on surrogate models to reach the plant optimum when the plant cost gradient is imperfectly known. It is shown that, for processes with only box constraints, the optimum is reached upon convergence if the multiplicative gradient uncertainty lies within some bounded interval. For the case of general constraints, conditions are derived that guarantee plant feasibility and, in principle, allow enforcing cost decrease at each iteration.
Subjects
Convergence
Monotonic cost decrease
Real-time optimization
Uncertain gradients
DDC Class
510: Mathematics