包装覆膜自适应恒张力控制方法研究

Adaptive Constant Tension Control Method of Packaging Coating

目的为解决悬浮包装生产过程中薄膜张力不稳定等问题,建立覆膜过程薄膜张力数学模型。方法针对传统PID控制在薄膜张力控制中的诸多不足,基于BP神经网络设计自适应PID薄膜张力控制方法。根据系统运行状态,调节PID控制器的参数。通过神经网络的自身学习来调整权系数,确保被控对象处于稳定工作状态。为进一步优化BP神经网络控制性能,利用鱼群寻优算法实现初始阈值和权值优化。最后,进行仿真和实验研究。结果仿真和实验结果表明,基于改进BP-PID控制算法进行张力控制时,系统响应速度较快,最大超调量较小。薄膜张力的最大相对误差只有0.5N,误差值都比较小。结论改进BP-PID算法具有较高的控制精度和稳定性,可满足包装覆膜要求。

The work aims to establish a mathematical model of film tension in the process of film mulching,in order to solve the problem of film tension instability in the production process of suspended packaging.Aiming at the shortcomings of traditional PID control in film tension control,an adaptive PID film tension control method was designed based on BP neural network.The parameters of PID controller were adjusted according to the running state of the system.Through the self-learning of neural network,the weight coefficient was adjusted to ensure the stable working state of controlled object.In order to further optimize the control performance of BP neural network,the initial threshold and weight optimization were realized with the fish swarm optimization algorithm.Finally,the simulation and experimental research were carried out.Simulation and experimental results showed that,the system’s response speed was fast and the maximum overshoot was small during tension control based on the improved BP-PID control algorithm.The maximum relative error of film tension was only 0.5 N,which was relatively small.The improved BP-PID algorithm has high control accuracy and stability,and can meet the requirements of packaging coating.