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.
