中文摘要：

为了更好地消除聚丙烯晴碳纤维（polyacryionitrile carbon fiber,PANCF）牵伸过程中相关状态间的耦合效应,基于因子网络数学模型,与解耦控制相结合,提出一种多级协同的解耦网络（cytokine network based decoupling network,CNDN）,并植入具体的解耦控制算法;将该结构和算法应用于牵伸水浴的温度、浓度以及液位多个耦合量的解耦控制.仿真结果标明：CNDN对于控制量的改变反应更加迅速,较传统解耦方法可以基本实现控制量的完全解耦和平滑调节,抗干扰能力强,稳定性好.

英文摘要：

To improve the decoupling effectiveness of multiple variables in polyacrylonitrilc carbon fiber （PANCF） production line, based on the artificial cytokine network （ACN） and its mathmatical model, a network structure of the stretching process was proposed and investigated. With decoupling compensation algorithm embedded in the calculation center, a complete cytokine network based decoupling network （CNDN） was proposed, which realized the deeoupling of three variables in the stretching tank： temperature, concentration, and liquid level. Simulation results show that the CNDN not only can rapidly respond the set-points of control variables, but also completely eliminate the influence on other variables coupling with it; moreover, it has a better ability of resistance against the interference.