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Abstract.
This paper provides a case study on the selection of controlled
variables for the implementation of real time optimization results
in a crude unit heat exchanger network. Two different control
strategies with 22 different control structures are evaluated. The
idea is to select the controlled variables that give the best plant
economic (smallest loss) when there are disturbances (self-optimizing
control). The disturbances are correlated and a simple principal
component analysis is used to generate a more realistic set of
disturbance variations for evaluation of the different control
structures. This analysis shows a large variation of loss for
different control structures and that a control structure evaluation
is necessary to collect the benefits from a RTO system.