Referential process–reaction curve for batch operations

Abstract

This paper shows an extension of the well-known process reaction curve method to empirically determine reduced-complexity models aimed to the design and tuning of feedback controllers for non-stationary batch processes. The basic idea is to isolate the dynamics associated to the manipulated variable from the main time-variable behavior that characterizes the operation, by taking the time evolution of a previous run as reference. One or more input-perturbed evolutions can then be compared to the previous dynamic pattern yielding referential reaction curves. This modeling approach cancels out most of the non-stationary behavior, allows capturing the dominant manipulated-variable dynamics and the use of available tuning rules for integrating systems. The effectiveness of this procedure is illustrated by using a nonlinear model of a bioreactor that simulates the production of Xanthan gum.