神经网络PID控制器在纸浆浓度调节中的应用

Application of Neural Network Based on PID Controller in Pulp Consistency

在造纸过程中,针对纸浆浓度控制系统的大滞后和模型不确定的特性,利用BP神经网络所具有的自学习能力和任意非线性表达能力,提出了用BP神经网络自整定PID参数的控制策略,对纸浆浓度的调节进行控制,并使用MATLAB软件进行仿真研究。仿真结果表明:基于BP神经网络的PID控制器具有很强的适应性,可以获得满意的控制效果。

The characteristics of large time lag and non- accurate mathematic model existed in the process of papermaking of pulp consistency system,using the self- learning ability and describing any non- linear ability of BP neural network,a NN PID controller of parameters self- tuning could be constructed to control pulp consistercy system. This article used the MATLAB software to simulate reality. The result of simulation shows that the Neural Network based PID controller has stronger adaptability and can get satisfied result.