Abstract
In the past decade a large number of studies concerning the application of modern state estimation techniques to chemical processes have been reported. However, the vast majority of these studies have been in simulation, and do not adequately demonstrate the utility of an estimator. For this reason, a practical study of Kalman-type estimation algorithms has been made. A real chemical process was interfaced to a small digital computing system and the process modelled analytically. Extensive simulation studies, which verified previous work, were performed before applying the Kalman estimation algorithms to the real process. It was found that the extended Kalman filter could usefully be applied to the problem of chemical process state estimation. Techniques for improving estimation when the process' was erroniously modelled in the filter, were successfully demonstrated. Incorporation of the filter in a feedback control loop enabled the use of modern control algorithms which gave good control. The Kalman estimation algorithms were then applied to the process which was under either open-loop or feedback control. The results, which were presented both graphically and in tabular form, clearly showed the practical advantages of using this kind of state estimator.