模糊神经网络锅炉温度控制系统

Boiler Temperature Control System Based on Fuzzy Neural Network

采用模糊神经网络和PID控制相结合的控制方式,设计了一种现代电站锅炉的温度监测系统。通过BP模糊神经网络实现对数据的模糊化处理,再通过PID控制器调节,最终实现对温度实时控制,利用Simulink软件建模,并进行电站锅炉温度监测,仿真和监测结果证明BP模糊神经网络采用梯度下降法逐层调节权值系数,实现误差均方值大幅度减小,模糊神经网络PID控制能够加快系统的运算速度,提高控制精度,获得更快的响应速度以及较小的超调量。

A control method combined with fuzzy neural network and PID control was used to design a temperature monitoring system for modern power station boilers.The BP fuzzy neural network is used to achieve fuzzy processing of the data,and then is adjusted by the PID controller to achieve real-time temperature control.From the simulation using the Simulink software and monitoring the temperature of the power plant boilers,it is shown that the BP fuzzy neural network uses gradient descent to adjust layer by layer.The weight coefficient realizes a significant reduction of the mean square error.The fuzzy neural network PID control can speed up the system′s operation speed,improve the control accuracy,and obtain a faster response speed and a smaller amount of overshoot.