Web Tension and Speed Control in Roll-to-Roll Systems

Jingyang Yan, Xian Du
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引用次数: 1

Abstract

Roll-to-roll (R2R) printing shows great potential for high-throughput and cost-effective production of flexible electronics, including solar cells, wearable sensors, and so on. In roll-to-roll process, precise control of the web speed and tension is critical to ensure product quality, since improper web speed and tension would lead to severe damages to the substrates. In this chapter, we will focus on the advanced control algorithms of web tension and speed control in roll-to-roll system. Two concepts of control algorithms will be presented, which are model-based control and data-based control. For model-based control algorithms, the modeling of web dynamics and an application of robust H ∞ controller will be reviewed; for data-based control algorithms, two methods of neural network control learning methods will be introduced, and the application of neural network control in web tension and speed control will be presented. Moreover, performances of different control algorithms are compared.
卷对卷系统中的卷筒纸张力和速度控制
卷对卷(R2R)印刷在高通量和高成本效益的柔性电子产品生产方面显示出巨大的潜力,包括太阳能电池、可穿戴传感器等。在卷对卷过程中,精确控制卷筒纸速度和张力对保证产品质量至关重要,因为不适当的卷筒纸速度和张力会导致基材严重损坏。在本章中,我们将重点讨论卷筒对卷筒系统中卷筒纸张力和速度控制的先进控制算法。本文提出了基于模型的控制和基于数据的控制这两个控制算法的概念。对于基于模型的控制算法,将回顾web动力学建模和鲁棒H∞控制器的应用;对于基于数据的控制算法,将介绍两种神经网络控制学习方法,并介绍神经网络控制在卷筒纸张力和速度控制中的应用。此外,还比较了不同控制算法的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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