Dynamic optimization of batch processes.

Abstract

Batch processes are common in the pharmaceuticals, specialty and fine chemicals industries. Unlike continuous processes, batch processes are dynamic in nature. Therefore, they are often not operated with the control variables at fixed setpoints. Instead, control trajectories that vary with time are often implemented to transfer the systems from their initial states to their final states. Process optimization has the potential to achieve (i) savings from lowering of production costs; (ii) improvement in product quality; and (iii) ensuring product consistency. In this work, the fundamentals of dynamic optimization and its application to improve operation of batch processes were explored. The simultaneous approach was used to determine the optimal control trajectories for a fed-batch bioreactor and a batch cooling crystallizer. Through the examples, it was shown that improvements in batch performance can be obtained through the application of dynamic optimization. 2 important issues in dynamic optimization were also studied, namely (i) singular optimal control problem; and (ii) effect of parametric uncertainty on the optimization of the batch operation. Several techniques that are proposed in the literatures to handle such issues were reviewed and their effectiveness was tested with the examples.