摘要
针对电阻炉具有时变,分布参数的非线性特性,将模糊神经网络控制应用于电阻炉温度控制系统.该控制器自适应能力强,利用系统偏差和神经网络辨识模型的输出对模糊神经网络控制器的参数通过一种改进的BP算法进行在线调节,达到对电阻炉温度的实时控制。仿真结果表明:模糊神经网络控翻器具有良好的控制效果,优于一般PID控制。
Fuzzy neural network(FNN)control is applied in the resistance furnace temperature control system, based on the time-variable and distributed parameters nonlinear features of resistance furnace.This controller has the adaptive ability,uses the system error and the output of neural network identification(NNI)model to rectify the parameters of the fuzzy neural network controller(FNNC)on line through an improved BP algorithm,so that the temperature car be controlled in time.The results of simulation prove that the FNNC has good performances and the effect is better than that of PID control.
出处
《辽宁工程技术大学学报(自然科学版)》
CAS
北大核心
2005年第z2期135-137,共3页
Journal of Liaoning Technical University (Natural Science)
关键词
电阻炉
模糊神经网络
系统辨识
温度控制
resistance furnace
FNN
system Identification
temperature control