Methods are presented for the design of a static estimator which infers unmeasurable product qualities from secondary measurements. The secondary measurements are selected so as to minimize the number of such measurements required to obtain an accurate estimate which is insensitive to modeling errors. Unlike previous work, the number of secondary measurements can be fewer than the number of unmeasured disturbances. If the statistics of the disturbances and/or measurement noise are available, this information can be incorporated into the design procedure to obtain an optimal static estimator.
The design procedure is illustrated by application to a simulated industrial debutanizer. Data for the simulation were supplied by the Marathon Oil Company. Deviations in bottoms product quality are compared for the current control policy (maintenance of a stage temperature at its set point) and the inferential control system with the column subjected to representative feed composition disturbances. Results show that inferential control based on four, five, or six tray temperature measurements improves the steady state control performance by as much as 400%.