摘要
针对PVC片材压延过程是一个复杂的非线性过程、难以建立精确数学模型的特点,提出了厚度自动控制神经网络模糊智能方法,设计了输入为"编码"的神经网络模糊控制器。通过仿真证明了神经网络模糊控制的可行性,其控制精度优于常规方法。
Because PVC sheet calendering was a complex nonlinear process, it was difficult to establish a precise mathematical model on thickness control. Therefore, a neural network fuzzy intelligent method to automatically control the thickness was proposed and a neural network fuzzy controller with coding-in was devised. The simulation proved that the neural network fuzzy control system was feasible and the control precision was better than that of conventional methods.
出处
《塑料》
CAS
CSCD
北大核心
2008年第4期94-96,30,共4页
Plastics
基金
国家自然科学基金(10472034,10590351)
关键词
神经网络模糊推理
编码
压延
厚度控制
neural network fuzzy inference
coding-in
calender
thickness control
