基于模糊神经网络PID的塑料薄膜厚度控制系统设计  

Design of Plastic Film Thickness Control System Based on Fuzzy Neural Network PID

作　　者：王全刚[1] 程良伦[1] 李锦棠[2] 

机构地区：[1]广东工业大学自动化学院,广东广州510006 [2]江门市辉隆塑料机械有限公司,广东江门529080

出　　处：《机床与液压》2016年第14期145-148,共4页Machine Tool & Hydraulics

基　　金：2012年广东省数控一代机械产品创新应用示范工程专项资金入库项目(2012B011300038)

摘　　要：针对当前塑料挤出行业薄膜厚度控制系统普遍存在的强非线性、大时滞、控制精度低的现状,设计了一种将模糊控制、神经网络与经典PID控制算法结合的塑料薄膜厚度智能控制系统,通过模糊控制与神经网络自学习算法相结合,实现了控制系统PID参数的在线自整定。实验证明:与传统厚度控制方式相比,该系统可以大大降低收敛时间,提高控制精度,将薄膜厚度误差控制在2μm以内。For the universal phenomenon that the plastic film thickness control system had the characteristic of strong nonlineari-ty, large time delay, low control precision, a plastic film thickness smart control system was designed combined with fuzzy control, neural network and classic PID control.Through combining fuzzy control with neural network, control parameters of PID were regulated on-line automatically.After field testing, comparing with traditional thickness control, using this system, convergence time is reduced greatly and the control precision is improved, the error of film thickness is reduced to 2μm.

关 键 词：模糊控制 神经网络 PID控制 薄膜厚度控制 

分 类 号：TP29[自动化与计算机技术—检测技术与自动化装置]