Comparison of Six Implicit Real-Time Optimization Schemes

Real-time optimization (RTO) is a class of methods that use measurements to reject the effect of uncertainty on optimal performance. This article compares six implicit RTO schemes, that is, schemes that implement optimality not through numerical optimization but rather via the control of appropriate variables. For unconstrained processes, the ideal controlled variable is the cost gradient. It is shown that, because of their structural differences, model-free and model-based techniques exhibit different features in terms of required excitation, convergence, scalability with the number of inputs and rejection of uncertainty. This comparison is illustrated through a simulated CSTR.


Published in:
Journal Européen des Systèmes Automatisés, 46, 2-3, 291-305
Year:
2012
Publisher:
Lavoisier
ISSN:
1269-6935
Keywords:
Laboratories:




 Record created 2011-12-09, last modified 2018-01-28

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