A Unified Framework for Combined Quality and Tracking Control of Batch Processes

摘要

A novel control technique specifically designed for batch processes is proposed as a unified framework where end-product quality and tracking control can be done simultaneously in a predictive manner. The proposed technique is designed bycombining iterative learning with model predictive control (MPC). As a consequence, both the quality variable as well as other controlled variables can progressively reduce their control error as the batch number increases while rejecting real-timedisturbances, and finally reach the best achievable states dictated by a quadratic criterion even when there is significant model error. Performance of the proposed control technique is illustrated through numerical examples.