Self-optimizing control of a large-scale plant: The Tennessee Eastman process

This paper addresses the selection of controlled variables, that is, "what should we control". The concept of self-optimizing control provides a syste matic tool for this, and we show how it can be applied to the Tennessee Eas tman process, which has a very large number of candidate variables. In this paper, we present a systematic procedure for reducing the number of altern atives. One step is to eliminate variables that, if they had constant setpo ints, would result in large losses or infeasibility when there were disturb ances (with the remaining degrees of freedom reoptimized). The following co ntrolled variables are recommended for this process: optimally constrained variables, including reactor level (minimum), reactor pressure (maximum), c ompressor recycle valve (closed), stripper steam valve (closed), and agitat or speed (maximum); and unconstrained variables with good self-optimizing p roperties, including reactor temperature, composition of C in purge, and re cycle flow or compressor work. The feasibility of this choice is confirmed by simulations. A common suggestion is to control the composition of inerts . However, this seems to be a poor choice for this process because disturba nces or implementation error can cause infeasibility.