张伟鹏,柴承文,武淑琴,王美鸥,黄嘉树,王仪明,乔俊伟.卷到卷多功能印刷机张力控制系统研究[J].包装工程,2025,(9):224-232.
ZHANG Weipeng,CHAI Chengwen,WU Shuqin,WANG Meiou,HUANG Jiashu,WANG Yiming,QIAO Junwei.Tension Control System for Reel-to-reel Multifunctional Printing Machine[J].Packaging Engineering,2025,(9):224-232. |
| 卷到卷多功能印刷机张力控制系统研究 |
| Tension Control System for Reel-to-reel Multifunctional Printing Machine |
| 投稿时间：2024-11-07 |
| DOI：10.19554/j.cnki.1001-3563.2025.09.026 |
| 中文关键词: 卷到卷多功能印刷机 张力控制 解耦控制 RBF神经网络自抗扰控制器 |
| 英文关键词:reel-to-reel multifunctional printing machine tension control decoupling control RBF neural network active disturbance rejection controller |
| 基金项目:国家新闻出版署智能与绿色柔版印刷重点实验室招标课题资助项目（ZBKT202403） |
| 作者 | 单位 |
| 张伟鹏 | 北京印刷学院，北京 102600 |
| 柴承文 | 北京印刷学院，北京 102600 |
| 武淑琴 | 北京印刷学院，北京 102600 |
| 王美鸥 | 北京印刷学院，北京 102600 |
| 黄嘉树 | 北京印刷学院，北京 102600 |
| 王仪明 | 北京印刷学院，北京 102600 |
| 乔俊伟 | 上海出版印刷高等专科学校，上海 200093 |
|
| Author | Institution |
| ZHANG Weipeng | Beijing Institute of Graphic Communication, Beijing 102600, China |
| CHAI Chengwen | Beijing Institute of Graphic Communication, Beijing 102600, China |
| WU Shuqin | Beijing Institute of Graphic Communication, Beijing 102600, China |
| WANG Meiou | Beijing Institute of Graphic Communication, Beijing 102600, China |
| HUANG Jiashu | Beijing Institute of Graphic Communication, Beijing 102600, China |
| WANG Yiming | Beijing Institute of Graphic Communication, Beijing 102600, China |
| QIAO Junwei | Shanghai Publishing and Printing College, Shanghai 200093, China |
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| 中文摘要: |
| 目的 为了满足卷到卷多功能印刷机系统在张力稳定性方面的需求，提出一种新型张力控制方法，旨在解决张力耦合问题，并增强系统的抗干扰能力和鲁棒性。方法 通过分析张力系统的运行机制，建立放卷单元与印刷单元之间的两级张力耦合数学模型，并推导系统的动态解耦与静态解耦模型。基于自抗扰控制（Active Disturbance Rejection Control，ADRC）方法，引入径向基函数（Radial Basis Function，RBF）神经网络对非线性组合部分的关键参数进行在线调整，设计一种RBF神经网络自抗扰控制器（RBF-ADRC）。结果 与其他控制器的仿真对比结果显示，RBF-ADRC能够有效实现张力系统的解耦控制，显著提升系统的恒张力稳定性，并增强其内部鲁棒性和抗干扰能力。结论 RBF神经网络自抗扰控制策略成功解决了张力耦合控制问题，不仅实现了系统的恒张力稳定运行，还显著提高系统的抗干扰能力和鲁棒性，实现了研究目标。 |
| 英文摘要: |
| In order to meet the demand of tension stability in reel-to-reel multifunctional printing machine system, the work aims to propose a new tension control method to solve the tension coupling problem and enhance the anti-interference ability and robustness of the system. By analyzing the operating mechanism of the tension system, the two-stage tension coupling mathematical model between the unwinding unit and the printing unit was established, and the dynamic decoupling and static decoupling models of the system were derived. Based on the Active Disturbance Rejection Control (ADRC) method, Radial Basis Function (RBF) neural network was introduced to adjust the key parameters of the nonlinear composite part online. An RBF neural network active disturbance rejection controller (RBF-ADRC) was designed. Compared with the simulation results of other controllers, RBF-ADRC could effectively realize the decoupling control of the tension system, significantly improve the constant tension stability of the system, and enhance the internal robustness and anti-interference ability. RBF neural network active disturbance rejection control strategy successfully solves the tension coupling control problem, which not only realizes the stable operation of the system at constant tension, but also significantly improves the anti-interference ability and robustness of the system, achieving the research goal. |
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