Diagnosis and rectification of model-process mismatch in chemical reaction systems

Abstract

In chemical reaction systems, a reliable kinetic model is essential to predict the evolution of concentrations. Often, variations in physicochemical or operational conditions lead to change in a part or whole of the reaction kinetics. This leads to a mismatch between the process model and the process. Consequently, the current model fails to capture the behaviour of the underlying system. Hence, it is important to detect such a change and rectify the model appropriately. In this work, we formulate this problem in a fault diagnosis and identification framework. We propose a framework for solving this problem in the following three steps: (1) Detection of overall model-process mismatch, (2) Isolation of faulty rate model, and (3) Rectification of faulty rate model. The detection step is carried out using a global test which identifies if there is a fault in the system. The isolation of faulty reaction is accomplished using a nodal test statistic. The model-process mismatch in that of the isolated reaction is rectified using a bank of extended Kalman filters. The proposed approach is illustrated using a simulation example of the Acetoacetylation of Pyrrole system.