Study on the Switching Model Predictive Control Algorithm in Batch Polymerization Process

Abstract

In the batch polymerization process, temperature control is generally a challenging task. In this paper, a new switching model predictive control algorithm that can be effectively used for the temperature control of batch polymerization process is developed and its effectiveness is verified by introducing it to industrial batch polyvinyl chloride polymerization process. Firstly, a general analysis of the polymerization process is conducted, and based on this, the reaction starting point is determined. Secondly, a switching model identification method considering the reaction starting point and the reaction heat generated after the reaction starts is proposed. Finally, a switching model predictive control algorithm that determines the optimal manipulated value based on the on-line updated step response model is constructed, and a cascade control system using this algorithm is introduced to the temperature control of batch polyvinyl chloride suspension polymerization process. The results show that the proposed control system can significantly improve temperature control performance (overshoot: 0.2%, root mean square error: 0.3) compared to before introduction (overshoot: 1.1%, root mean square error: 1.2ྟC) .