M. Kano et al., INFERENTIAL CONTROL OF DISTILLATION COMPO SITION USING PARTIAL LEAST-SQUARES REGRESSION, Kagaku kogaku ronbunshu, 24(3), 1998, pp. 425-430
In order to control product compositions in a multicomponent distillat
ion column, the composition estimated from measured tray temperatures
is used. In this paper, inferential models of product compositions are
constructed using Partial Least Squares regression, on the basis of s
teady-state and time series temperature measurements. The accuracy of
the estimation is greatly improved by using a dynamic model. It is als
o found that the use of past temperature measurements is effective for
improving the performance of the inferential model. From the detailed
dynamic simulation results, it is found that the cascade control syst
em using the proposed inferential model works very well.