摘要
针对氧乐果合成反应过程温度具有时变、延时等非线性特性,研究了补偿模糊神经网络控制系统。首先确定了补偿模糊神经网络的初始结构和初始参数,再通过动态调整补偿的改进BP算法来调整参数,实现温度的实时控制。仿真结果表明:补偿模糊神经网络控制系统收敛速度快、适应性强,在温度控制方面取得了比较满意的控制效果。
A new type controller of compensatory fuzzy neural network is presented I to control the temperature of Omethoate synthetic process,which exist time-varying,time-delay and nonlinear characteristics.First,initial structure and parameters of compensatory fuzzy neural would be determined,and then adjust the parameters by the dynamic adjustment compensation of the improved BP algorithm to control real time temperature.The results of simulation prove that the superiority of CFNN,which has the advantage of shorting training time and strong adaptability.it requires satisfactory effect.
出处
《农机化研究》
北大核心
2012年第5期75-78,共4页
Journal of Agricultural Mechanization Research
关键词
氧乐果
模糊控制
补偿算子
模糊神经网络
omethoate
fuzzy control
compensatory operator
fuzzy neural network
