Assessment of control loop performance

Abstract For processes described by linear transfer functions with additive disturbances, the best possible control in the mean square sense is realized when a minimum variance controller is implemented. It is shown that an estimate of the best possible control can be obtained by fitting a univariate time series to process data collected under routine control. No ‘identifiabüity’ constraints need be imposed.

The use of this technique is demonstrated with pilot plant and production data.