摘要
张力与转速是一对强耦合的被控量,在任何情况下减小因转速的变化而造成的张力瞬时变化是最为关键的一点。针对两电机驱动的张力伺服系统,采用解析式的方式给出其数学模型。基于该模型设计了BP神经网络PID控制器,对系统中的转速和张力变量进行自适应解耦控制。仿真结果表明,与常规PID定参数控制系统相比,该系统能够根据环境变化自动获得最优PID参数,对系统转速和张力实现了较好的解耦控制,具有良好的动静态性能及较强的鲁棒性。
Tensile force and speed are a pair of strong coupling controlled variables.It is vital to decrease the speed change caused by the change of tensile force in the tension servo system.This paper employed an analysis approach to construct the mathematical model of the two-motor tension servo control system.It designed a PID controller based on BP neural network to carry on the adaptive decoupling control for the speed and tension variable in the system.The simulation results showed that compared with the traditional PID constant parameters control,the designed control system could obtain optimal parameters of the PID controller according to environmental change,realize better decoupling control of speed and tension,and possess great dynamic and static characteristics and good robustness.
作者
陈冲
杨学民
CHEN Chong;YANG Xue-min(School of Electrical Engineering,Yancheng Institute of Technology,Yancheng 224051,China;School of Economics and Management,China University of Petroleum,Beijing 102249,China)
出处
《电工电气》
2022年第11期33-37,共5页
Electrotechnics Electric
基金
教育部产学合作协同育人项目资助(202102307006)。
关键词
神经网络
张力伺服系统
解耦控制
转速
皮带张力
neural network
tension servo system
decoupling control
speed
belt tension
