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Abstract.
The paper addresses the selection of controlled variables,that is,
"what should we control". The concept of self-optimizing control
provides a systematic tool for this, and in the paper we show how it
may be applied to the Tennessee Eastman process which has a very large
number of candidate variables. In the paper we present a systematic
procedure for reducing the number of alternatives. One step is to
eliminate variables which with constant setpoints result in large
losses or infeasibility when there are disturbances (with the
remaining degrees of freedom reoptimized).