摘要
针对造纸过程中纸浆浓度控制的特点,通过BP神经网络与PID相结合,组成神经网络控制器,用于纸浆浓度控制。利用神经网络自学习、自适应的功能,根据实际工况在线实时调整PID参数,使纸浆浓度的控制处于一种最优状态,达到较好的控制品质。
Considering the features of the papermaking process of pulp concentration control, this paper uses BP network combing with PID controller for pulp concentration. Using self-learning neural networks, adaptive functions, according to the actual status of online real-time adjustment of PID parameters, the control system offers an optimum working condition to the pulp concentration control and to better control quality.
出处
《轻工机械》
CAS
2007年第6期57-60,共4页
Light Industry Machinery
关键词
纸浆浓度
BP神经网络
PID控制
pulp consistency control
BP neural network
PID control
