A robust integrated model predictive iterative learning control strategy for batch processes

查看全文 作　　者：Liuming [1]ZHOU;Li [1]JIA;Yu-Long [1]WANG

机构地区：[1]School of Mechatronic Engineering and Automation, Shanghai University

出　　处：《Science China(Information Sciences)》索引2019年第62卷第11期,共3页

基　　金：supported by National Natural Science Foundation of China(Grant Nos.61873335,61773251,61833011);Shanghai Science Technology Commission(Grant Nos.16111106300,17511109400);Programme of Introducing Talents of Discipline to Universities(111 Project)(Grant No.D18003);Program for Professor of Special Appointment(Eastern Scholar)at Shanghai Institutions of Higher Learning,China 摘　　要：Dear editor,The modern process industry is evolving from the production of basic materials in large quantities to the production of many varieties of high-quality professional products in small batches.Batch process refers to the conversion of limited quantities of raw materials into specific product outputs in finite time and obtaining more products through repeated processes.Owing to the flexibility and lower equipment investment,batch processes are widely used in the process industry. 关键词：A ROBUST INTEGRATED MODEL ITERATIVE LEARNING

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A robust integrated model predictive iterative learning control strategy for batch processes

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