Robust Inferential Control for a Packed-Bed Reactor

Abstract

An inferential robust control technique is applied to an experimental fixed bed reactor. The controlled variables are the exit concentration and the maximum bed temperature. Both controlled variables are inferred from one single temperature measurement. The location of this measurement is selected to optimize the performance of the closed-loop system when model uncertainty is allowed. Closed-loop experiments are conducted to test the robustness characteristics of the controller. From these experiments, the operating regions most sensitive to modelling uncertainty are determined. The nonlinear system characteristics can cause significant offset in the inferred controlled variables.