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  • 标题:Modeling Method Based on Output-layer Structure Feedback Elman Neural Network and PID Decoupling Control of PVC Stripping Process
  • 本地全文:下载
  • 作者:Hong-Yu Wang ; Dong Wei ; Jie-Sheng Wang
  • 期刊名称:IAENG International Journal of Computer Science
  • 印刷版ISSN:1819-656X
  • 电子版ISSN:1819-9224
  • 出版年度:2020
  • 卷号:47
  • 期号:4
  • 语种:English
  • 出版社:IAENG - International Association of Engineers
  • 摘要:The PVC stripping process is a complex industrial process with highly nonlinear and time varying. It is difficult to establish an accurate mathematical model due to multivariable, nonlinear, coupled and large hysteresis, etc. So the modeling method based on output-layer structure feedback Elman (OSF-Elman) neural network and PID decoupling control strategy of PVC stripping process is proposed. Firstly, the OSF-Elman neural network modeling method is proposed to establish the controlled object model with the actual operational data of the vinyl chloride stripping process. Then a neural network decentralized decoupling controller is used to decouple the stripping process to obtain two SISO systems (slurry flow - tower top temperature and steam flow-tower bottom temperature). Finally, the whale optimization algorithm (WOA) based PID controller is applied to the decoupled stripper system to achieve the effective performance for the PVC stripping process. The simulation results verify the effectiveness of the proposed integrated control strategy.
  • 关键词:PVC stripping process;Elman neural network;PID decoupling control;Whale optimization algorithm
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