摘要
以工业生产中具有重要地位的粉末冶金烧结炉为研究对象,对其原传统控制方案进行分析,提出一种基于模糊神经网络的温度控制方案,充分利用模糊控制的推理性和神经网络控制的记忆和学习功能。仿真实验及现场测试结果表明,模糊神经网络用于粉末冶金烧结炉温度控制较原传统控制方案具有明显的优越性。
According to importance of powder metallurgy furnace in industry production, the conventional control method of it control system was analyzed. A temperature control project based on FNN was designed and it made full use of inference of fuzzy and memory and leaming-function of neural network. The result of simulation and scene measurement validated temperature control based on fuzzy neural network had obvious advantage in contrast to the traditional control.
出处
《现代制造工程》
CSCD
北大核心
2010年第1期75-77,共3页
Modern Manufacturing Engineering
关键词
模糊神经网络
粉末冶金烧结炉
温度控制
Fuzzy Neural Network （FNN）
powder metallurgy sintering furnace
temperature control
