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In this thesis, starting from the point of view of practical application , object to , the small mills economic machine quantitative moisture control system , the economy , a small paper mill paper machine quantitative , moisture control system process work processes and systems automatically control principle . Uncertainty for the system , multivariate strong coupling , strongly nonlinear , large dead time , the state is not fully measured , frequent changes in operating conditions and other characteristics , taking into account the complexity of conventional methods of mathematical modeling , so system modeling using multiple linear regression methods . The model has been established and then the PID control' dissertation">BP neural network PID controller and the conventional PID controller to control the BP neural network PID controller is proved through theoretical analysis and computer simulations , and conventional PID controller , effectively raising the transition time , to ensure the quality of the system , and achieved good control effect .
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