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 by combining 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-time disturbances, 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.