PVC stripping process is a kind of complicated industrial process with characteristics of highly nonlinear and time varying. Aiming\nat the problem of establishing the accurate mathematics model due to the multivariable coupling and big time delay, the dynamic\nfuzzy neural network (D-FNN) is adopted to establish the PVC stripping process model based on the actual process operation\ndatum. Then, the PVC stripping process is decoupled by the distributed neural network decoupling module to obtain two singleinput-\nsingle-output (SISO) subsystems (slurry flow to top tower temperature and steamflow to bottomtower temperature). Finally,\nthe PID controller based on BP neural networks is used to control the decoupled PVC stripper system. Simulation results show the\neffectiveness of the proposed integrated intelligent control method.
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