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Web Tension Observer Based Control for Single-Span Roll to Roll Systems

EasyChair Preprint 5212

7 pagesDate: March 24, 2021

Abstract

Roll-to-roll (R2R) systems show great potential for high-throughput and cost-effective production of flexible electronics, including solar cells, wearable sensors, and so on. Actually, most of design methods for tension controller of web transport system (such as paper, plastic film, etc.) we need to take the state variables as feedback. In the field of, these variables we can measure directly using the sensors. However, when the complex systems, as more the variables as more feedback signals, need more sensors which makes the system bulky and expensive. Moreover, the accuracy of the sig-nals from sensor will be affect in a serious problem for many industrial components operating (dust, high temperature, noise, etc.). In some cases, direct measurements are difficult or tend to be inaccurate. In which, precise regulation of span tension in R2R is critical to ensure product quality. Elevated tension causes web fracture during operation; depressed or highly variable tension leads to irregular and unacceptable spool. The approach in this paper is to model how to observer state equations with only a small number of sensors so we will propose a method to build tension controller based on backstepping controller without using tension sensor from the system. Simulation has shown that the proposed controllers without a ten-sion measurement perform well against the inertia disturbances.

Keyphrases: Backstepping controller, Lyapunov stability, Roll to Roll System, Tension Observer, Web Tension Control, sensorless

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
@booklet{EasyChair:5212,
  author    = {Ly Tong Thi and Duc Duong Minh and Huy Nguyen Danh and Lam Nguyen Tung},
  title     = {Web Tension Observer Based Control for Single-Span Roll to Roll Systems},
  howpublished = {EasyChair Preprint 5212},
  year      = {EasyChair, 2021}}
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