摘要
建立关于湿度、硬度、入磨物料量等原粮品质的磨粉机能耗数学模型,利用模糊神经网络PID(Proportion-Integration-Differentiation)控制器对小麦制粉过程中磨粉机能耗进行控制,利用模糊神经网络算法对PID控制器参数进行在线整定,最后进行仿真验证。仿真结果表明,改进的PID控制器具有响应快、超调小、抗干扰性好等优点。
The mathematical model of the energy consumption, which has close relationship with the raw wheat quality such as humidity, hardness and granularity of raw, was firstly established for the wheat flour milling. Then a fuzzy neural network PID controller was proposed to realize the wheat flour milling process control. In the proposed algorithm, the parameters of PID controller were online tuned by the fuzzy neural network algorithm, and the performance of the proposed controller was finally verified by the simulation. The results indicated that the improved PID controller took the characteristics of fast response, small overshoot, and good anti-interference.
作者
张会娟
刘杰
陈红梅
刘楠嶓
ZHANG Hui-juan;LIU Jie;CHEN Hong-mei;LIU Nan-bo(Henan University of Technology,Zhengzhou 450001,Henan,China)
出处
《粮食与油脂》
北大核心
2019年第3期27-30,共4页
Cereals & Oils
基金
粮食公益性行业科研专项(201513003)
河南省教育厅高等学校重点科研项目(17B590001)
河南省科技厅科技攻关项目(172102210214
122102110107
152102110074)
关键词
能耗模型
模糊神经网络控制
制粉
磨粉机
原粮品质
energy-consuming model
fuzzy and neural network
flour-milling
mill
quality of raw grain