Transfer learning for nonlinear batch process operation optimization

doi:10.1016/j.jprocont.2021.03.002

CORC > 自动化研究所 > 中国科学院自动化研究所 > 复杂系统管理与控制国家重点实验室 > 先进控制与自动化团队

	Transfer learning for nonlinear batch process operation optimization
	Chu, Fei 2,3,4; Wang, Jiachen 4; Zhao, Xu 4; Zhang, Shuning 1; Chen, Tao 6; Jia, Runda 5; Xiong, Gang 2
刊名	JOURNAL OF PROCESS CONTROL
	2021-05-01
卷号	101 页码:11-23
关键词	Transfer learning Nonlinear batch process Insufficient data Operation optimization Data selection
ISSN号	0959-1524
DOI	10.1016/j.jprocont.2021.03.002
通讯作者	Chu, Fei(chufeizhufei@sina.com)
英文摘要	This paper concerns with the JY-KPLS model based transfer learning for the operation optimization of nonlinear batch processes. Due to problems of data insufficiency and uncertainties in a new nonlinear batch process that has just been put into production, the model-(new) process mismatch is usually inevitable, which is also the main reason for the poor performance of the batch process. To solve this problem, this paper first adopts the JY-KPLS model to capture the behavior of the nonlinear batch process, and takes full advantage of the information in similar batch processes to assist the modeling and operation optimization of a new process. Then, a data selection based batch-to-batch optimization control strategy is proposed in this paper to reduce the adverse effects of this mismatch on the operation of the new batch process. Finally, the feasibility of the proposed method is demonstrated by simulations. (C) 2021 Elsevier Ltd. All rights reserved.
资助项目	National Natural Science Foundation of China[61973304] ; National Natural Science Foundation of China[61503384] ; National Natural Science Foundation of China[61873049] ; National Natural Science Foundation of China[62073060] ; National Key Research and Development Program of China[2018YFB1702701] ; Natural Science Foundation of Jiangsu Province[BK20191339] ; Selection and Training Project of High-level Talents in the Sixteenth ``Six Talent Peaks'' of Jiangsu Province[DZXX-045] ; Xuzhou science and technology plan project[KC19055] ; Open Subject of State Key Laboratory of Process Automation in Mining Metallurgy[BGRIMM-KZSKL-2019-10]
WOS关键词	PARTIAL LEAST-SQUARES ; ADAPTIVE-CONTROL ; DATA-DRIVEN ; PRODUCT TRANSFER ; QUALITY ; PLS
WOS研究方向	Automation & Control Systems ; Engineering
语种	英语
出版者	ELSEVIER SCI LTD
WOS记录号	WOS:000641987500002
资助机构	National Natural Science Foundation of China ; National Key Research and Development Program of China ; Natural Science Foundation of Jiangsu Province ; Selection and Training Project of High-level Talents in the Sixteenth ``Six Talent Peaks'' of Jiangsu Province ; Xuzhou science and technology plan project ; Open Subject of State Key Laboratory of Process Automation in Mining Metallurgy
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/44512]
专题	自动化研究所_复杂系统管理与控制国家重点实验室_先进控制与自动化团队
通讯作者	Chu, Fei
作者单位	1.Ludong Univ, Sch Informat & Elect Engn, Yantai 264025, Peoples R China 2.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China 3.Beijing Gen Res Inst Min & Met, State Key Lab Proc Automat Min & Met, Beijing Key Lab Proc Automat Min & Met, Beijing 100160, Peoples R China 4.China Univ Min & Technol, Underground Space Intelligent Control Engn Res Ct, Sch Informat & Control Engn, Minist Educ, Xuzhou 221116, Jiangsu, Peoples R China 5.Northeastern Univ, Coll Informat Sci & Engn, Shenyang 110819, Peoples R China 6.Univ Surrey, Dept Chem & Proc Engn, Guildford GU2 7XH, Surrey, England
推荐引用方式 GB/T 7714	Chu, Fei,Wang, Jiachen,Zhao, Xu,et al. Transfer learning for nonlinear batch process operation optimization[J]. JOURNAL OF PROCESS CONTROL,2021,101:11-23.
APA	Chu, Fei.,Wang, Jiachen.,Zhao, Xu.,Zhang, Shuning.,Chen, Tao.,...&Xiong, Gang.(2021).Transfer learning for nonlinear batch process operation optimization.JOURNAL OF PROCESS CONTROL,101,11-23.
MLA	Chu, Fei,et al."Transfer learning for nonlinear batch process operation optimization".JOURNAL OF PROCESS CONTROL 101(2021):11-23.