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Two-Layer Predictive Control of the Copper Smelting Process Blowed by Enriched Oxygen at Bottom
Wang B(王斌)1,2,3; Wang Z(王卓)1,3; Yu HB(于海斌)1,3; Jia Y(贾洋)1,3
Department数字工厂研究室
Conference Name7th IEEE Annual International Conference on CYBER Technology in Automation, Control, and Intelligent Systems, CYBER 2017
Conference DateJuly 31 - August 4, 2017
Conference PlaceHawaii, USA
Author of SourceIEEE Robotics and Automation Society
Source Publication2017 IEEE 7th Annual International Conference on CYBER Technology in Automation, Control, and Intelligent Systems, CYBER 2017
PublisherIEEE
Publication PlaceNew York
2017
Pages986-989
Indexed ByEI ; CPCI(ISTP)
EI Accession number20183905873487
WOS IDWOS:000447628700179
Contribution Rank1
ISBN978-1-5386-0489-2
KeywordCopper Smelting Process Blowed By Enriched Oxygen At Bottom Two-layer Predictive Control Scheme Dynamic Matrix Control
Abstract

Due to the nonlinearity, coupling, and delay during the copper smelting process blowed by enriched oxygen at bottom, a novel two-layer predictive control scheme is presented. The objective of the scheme is to minimize the cost of the material. The two-layer predictive control method achieves the steady-state optimal setpoints and resolves the multivariable dynamic control problems synchronously. Industrial test results show that the two-layer predictive control strategy leads to a significant improvement of control performance, as compared to manual controller within a multiloop framework.

Language英语
Citation statistics
Document Type会议论文
Identifierhttp://ir.sia.cn/handle/173321/22828
Collection数字工厂研究室
Corresponding AuthorWang B(王斌)
Affiliation1.Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China
2.University of Chinese Academy of Sciences, Beijing, China
3.Key Laboratory of Networked Control Systems, Chinese Academy of Sciences, Shenyang, China
Recommended Citation
GB/T 7714
Wang B,Wang Z,Yu HB,et al. Two-Layer Predictive Control of the Copper Smelting Process Blowed by Enriched Oxygen at Bottom[C]//IEEE Robotics and Automation Society. New York:IEEE,2017:986-989.
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