Polyvinyl chloride(PVC) stripping process is a typical complicated non-linear industrial process with the
characteristics of highly non-linear and time variety. Firstly，the controlled object model of the stripping process is
established based on the data-driven dynamic fuzzy neural network(D-FNN) method. Then the decentralized neural network
controller is adopted to decouple the stripping process into the two single-input-single-output(SISO) of slurry flux versus
tower top temperature and steam flux versus tower bottom temperature. Finally, the BP neural network PID controller is used
to control the decoupled SISO system. Simulation results show the effectiveness of the proposed integrated control strategy.