摘要
针对当前化工领域中,特别是氯化工艺领域控制的精度要求,结合传统的PID控制存在的问题,提出一种采用BP进行改进的方法。即通过BP神经网络在自学习方面的优势,通过BP优化减少输入参数与输出参数的误差。最后,以氯化工艺中的压力控制为例,通过仿真对工艺进行模拟优化,结果表明,经BP优化后的PID在延迟量等方面,都有很大的优势。
In view of the control accuracy requirements in the field of chemical industry,especially in the field of chlorination process,combined with the problems existing in the traditional PID control,this paper puts forward a method of improvement by using BP.That is to say,through the advantages of BP neural network in self-learning,through BP optimization to reduce the error of input parameters and output parameters.Finally,taking the pressure control of chlorination process as an example,the process is simulated and optimized by simulation.The results show that the PID optimized by BP has great advantages in delay and other aspects.
作者
娄勇
LOU Yong(School of Electronic Engineering,Shaanxi Institute of Mechatronic Technology,Baoji Shaanxi 721001,China)
出处
《粘接》
CAS
2020年第9期50-53,共4页
Adhesion
关键词
BP神经网络
PID控制
仿真
氯化工艺
BP neural network
PID control
simulation
chlorination process
