Dynamic Multi-Scenario Approach to Robust and Profitable Online Optimization & Optimal Control of Batch Processes

Abstract We propose a novel integrated methodology for taking into account model uncertainty, in the form of uncertain parameters, within a previously published real time dynamic optimization and optimal control strategy. The combined approach, designed for batch processes, is scenario-based and consists of two interacting layers: one, which computes the optimal operating conditions and takes control actions in response to disturbances, and the other, which executes the dynamic scenario updating strategy. The approach is applied to a fed-batch reactor to demonstrate its effectiveness and flexibility.