摘要
双螺杆挤出机温度控制系统通常存在大扰动、非线性以及滞后性等特点,拥有固定参数的传统PID控制策略控制效果并不理想,为此提出了一种基于模糊神经网络PID控制的温度控制方法,对于现场无法充分预估的情况,该控制方法能够根据具体情况对PID参数做出适当调整。首先介绍了双螺杆挤出机温度采集与控制系统组成,将模糊控制理论、神经网络控制与传统PID控制相结合,利用模糊控制和神经网络对PID参数实现在线实时调整。最后,将模糊神经网络PID控制与常规PID和模糊PID控制进行仿真对比,模糊神经网络PID控制对螺杆机温度控制效果更佳,采用该控制方法可以大大提高产品合格率。
Twin-screw extruder temperature control system usually has the characteristics of large disturbance, non-linearity and lag. The control effect of traditional PID control strategy with fixed parameters is unsatisfactory. Therefore, a temperature control method based on fuzzy neural network PID control is proposed. For the situation that the field can not be fully predicted, the control method can make appropriate PID parameters according to the specific situation. Adjustment. Firstly, the composition of temperature acquisition and control system of twin screw extruder is introduced. The fuzzy control theory, neural network control and traditional PID control are combined to realize online real-time adjustment of PID parameters by using fuzzy control and neural network. Finally, the fuzzy neural network PID control is compared with the conventional PID control and the fuzzy PID control. The fuzzy neural network PID control has better effect on temperature control of screw machine. The qualified rate of products can be greatly improved by using this control method.
作者
冯润根
Feng Rungen(Liaocheng Vocational&Technical College, Liaocheng 252000, China)
出处
《塑料科技》
CAS
北大核心
2019年第6期78-81,共4页
Plastics Science and Technology
关键词
双螺杆挤出机
温度控制
模糊控制
神经网络
Twin screw extruder
Temperature control
Fuzzy control
Neural network