文献类型：会议论文

英文题名：Adaptive optimal output regulation for industrial hydrocracking process

作者：Li, Zhongmei[1];Huang, Mengzhe[2];Xue, Dong[1];Du, Wenli[1]

机构：[1]East China Univ Sci & Technol, Key Lab Adv Control & Optimizat Chem Proc, Shanghai 200237, Peoples R China;[2]NYU, Tandon Sch Engn, Brooklyn, NY 11201 USA

会议论文集：Chinese Automation Congress (CAC)

会议日期：NOV 06-08, 2020

会议地点：Shanghai, PEOPLES R CHINA

语种：英文

外文关键词：Hydrocracking process; adaptive dynamic programming (ADP); optimal tracking

摘要：Hydrocracking is an important petrochemical process, in which the reactor temperature determines the final product distribution and quality. In this paper, a new data-driven optimal reactor temperature control method is proposed through the integration of reinforcement learning, adaptive dynamic programming (ADP) and output regulation theory. Different from the existing literature, the reactor temperature control problem is formulated as an output regulation problem, and a policy iteration (PI) based ADP algorithm is employed to find the adaptive optimal controller. The simulation results show that the actual nitrogen content in the stream of R101 outlet can be regulated to the desired value and keep the reaction temperature of each bed in R101 to a minimum while disturbance rejection is achieved.