A Tutorial on the Optimization of Batch Processes: II. Handling Uncertainty Using Measurements

The optimization of batch processes has received attention recently because, in the face of growing competition, it represents a natural choice for reducing production costs, improving product quality, meeting safety requirements or environmental regulations. The main bottleneck in using optimization in industry is the way uncertainty is handled, which forms the subject of this series of two papers. The first part dealt with the characterization of the nominal solution using Pontryagin’s Maximum Principle. This second part reviews various strategies for optimization under uncertainty, namely the robust, run-to-run and on-line optimization schemes. A novel feedback-based optimization framework is proposed, which combines feedback control and the complementary aspects from the various optimization strategies and does not necessitate on-line numerical optimization.