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针对木塑复合材料挤出过程中挤出温度采用传统PID控制的不足,设计研究了木塑挤出机温度的BP神经网络PID控制系统。针对挤出温度控制过程中的高非线性和分段温度的特点,提出BP神经网络PID控制算法以改善温度系统性能,实现对温度模型的高效控制。木塑挤出机温度的传统PID控制与木塑挤出机温度的BP神经网络PID控制进行仿真对比,结果表明木塑挤出机温度的BP神经网络PID控制在系统升温的速度、超调量、调节时间、抗干扰能力方面具有明显优势,在控制精度方面更符合木塑挤出机温度控制要求。
Aiming at the shortcomings of using traditional PID control in extruding temperature of wood-plastic composite material, a BP neural network PID control system of wood-plastic extruder temperature was designed and studied. In view of the characteristics of high nonlinearity and segment temperature during extrusion temperature control, a BP neural network PID control algorithm is proposed to improve the performance of the temperature system and achieve the efficient control of the temperature model. The traditional PID control of wood-plastic extruder temperature and BP neural network PID control of wood-plastic extruder temperature are simulated and compared. The results show that the temperature of wood-plastic extruder BP neural network PID control system heating speed, overshoot , Adjust the time, anti-interference ability has obvious advantages in terms of control accuracy is more in line with the temperature control of wood-plastic extruder requirements.