A novel deep ensemble reinforcement learning based control method for strip flatness in cold rolling steel industry-Reference-Cited by-同舟云学术

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A novel deep ensemble reinforcement learning based control method for strip flatness in cold rolling steel industry

Published:2024-08 Issue: Volume:134 Page:108695
ISSN:0952-1976
Container-title:Engineering Applications of Artificial Intelligence
language:en
Short-container-title:Engineering Applications of Artificial Intelligence

Author:

Peng Wen^ORCID,Lei Jiawei,Ding Chengyan,Yue Chongxiang,Ma Gengsheng,Sun Jie^ORCID,Zhang Dianhua

Publisher

Elsevier BV

Reference39 articles.

1. Coupled approach for flatness prediction in cold rolling of thin strip;Abdelkhalek;Int. J. Mech. Sci.,2011

2. Post-buckling modeling for strips under tension and residual stresses using asymptotic numerical method;Abdelkhalek;Int. J. Mech. Sci.,2015

3. Optimization-based automatic flatness control in cold tandem rolling;Bemporad;J. Process Control,2010

4. Flatness analysis and control of strips with different thickness in 2250 mm hot tandem rolling;Chai;Steel Res. Int.,2018

5. Model-free emergency frequency control based on reinforcement learning;Chen;IEEE Trans. Ind. Inf.,2020

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