Research On Temperature Control System Of Rubber Extruder Based On BP Neural Network And PID

With the widespread use of rubber products,there is an increasing demand for high performance rubber products.In order to obtain high-performance rubber products,the rubber extruder is one of the most basic production equipment in the rubber production process.In the extrusion process of rubber products,the performance of the extruded semi-finished products is determined by the temperature control of the rubber in the barrel and the temperature control of the machine head.Therefore,in order to improve the performance of extruded rubber products and improve production efficiency,how to improve the temperature control ability of rubber extruders has become an important research direction in the field of temperature control.In this paper,the temperature control system of rubber extruder is taken as the research object,which is carried out in four parts: control algorithm,hardware composition,software design and experimental simulation.Firstly,the BP neural network algorithm and PID control algorithm used in this temperature control system are introduced and analyzed in detail.For the temperature control system,the conventional PID control can not be used to self-tuning the PID control parameters.This paper uses BP neural network to come from the BP neural network.The control parameters of the PID are adjusted to combine the control advantages of the two as the control algorithm of the temperature control system.Secondly,for the hardware circuit part of the rubber extruder temperature control system,the hardware selection of the microcontroller module,temperature data acquisition module,human-computer interaction module and temperature control execution module with STM32 as the core is analyzed,and Altium is used.Designer hardware circuit design software draws thecircuit diagram of each module and makes the PCB main control board.Thirdly,for the software part of the rubber extruder temperature control system,the modular design of the program is adopted.The BP neural network PID control algorithm main control program module,temperature data acquisition sub-module,heating and cooling sub-module,liquid crystal display sub-module are introduced.And the software design of the button processing sub-module,and the anti-interference design and debugging of the software part of the temperature control system,thereby improving the anti-interference of the control system.Finally,for the simulation and experimental part of the rubber extruder temperature control system,the conventional PID controller model and BP neural network PID controller model are constructed respectively.The simulation analysis and experimental research of the two controllers are carried out.The results show that BP The neural network PID composite controller can simultaneously ensure the control requirements of the temperature control system with small overshoot and small steady-state error during the temperature control process,and can also better set the control parameters required by the PID controller online.Going to the use of a conventional PID controller requires an empirical formula to calculate the control parameters.Experiments show that the BP neural network PID composite control algorithm used in this paper makes the temperature control accuracy of the rubber extruder±1?,the system steady-state error is less than 0.5?,which can meet the temperature control requirements of the rubber extruder.