# Kalman-Filter-Based Tension Control Design for Industrial Roll-to-Roll System
## 1 Introduction  
Roll-to-roll (R2R) technology has recently attracted a great deal of attention for the mass production of electronic devices in the field of display and battery [1]. The R2R machine is composed of rewinder, unwinder, and feeder motors. The rewinder motor is used to wind the web made in roll form with the desired tension. On the other hand, the unwinder motor is used to unwind the web. The feeder motor is used for web transfer motions at the proper speed. In the R2R system, tension control is usually achieved by using a load cell or dancer roll. In R2R processing, robust and precise tension control is essential because it affects the quality of the web materials. The web has flexible substrates including metal foils, glass, and ceramics. In particular, these substrates used in electronic devices require precise tension control because coating and printing thickness variation occurs despite minute tension changes, resulting in changes in electrical properties. Some studies have investigated the tension control of R2R equipment. In 1993, [PERSON] investigated web tension control with dancer rolls and load cells [2]. The two different systems have been analyzed and experimental results have been provided. In 1998, [PERSON] designed an adaptive fuzzy control for a web tension control system [3]. In 2002, [PERSON] analyzed modeling and robust control of a winding system [4]. The effectiveness of robust control strategy in a web system is compared to a proportional-integral-derivative (PID) controller commonly used in the industry. In 2007, [PERSON] the effect of tension on the lateral dynamics and control of a moving web [5]. Experimental studies of the lateral motion of a web were carried out and a cross-couple controller was proposed, which automatically tunes the proportional and integral gains of a lateral-position controller according to the web tension. However, despite these numerous studies, tension control is not easy because it has model variations in which the inertia of the web in roll form is changed and external disturbances caused by web slip and crumpled web. To achieve robustness against model variations and external disturbances, robust control such as a disturbance observer (DOB) is required [6; 7; 8; 9; 10]. DOB has been widely used as an effective methodology to overcome model uncertainty and external disturbance. [PERSON] proposed DOB for the robust tension control of the R2R system [11]. Unlike previous studies, we propose feedforward (FF) controller and signal processing technology using the Kalman filter (KF) to improve tension control performance. The web is continuously subjected to various processes for the final production. Particularly, it is important to control the tension when magnitude of the tension varies during process. To improve tracking performance in the transient section where tension changes, the feedforward controller was applied [12; 13; 14]. Moreover, a high-price load cell with a highly accurate and noiseless signal should be used to improve tension control performance in the R2R system. In order to reduce costs, which is an unavoidable issue in today's industry, the KF algorithm was suggested for signal processing [15; 16; 17; 18]. Almost all load cell applications require filtering to remove noise from the measured signal. A signal filter has a trade-off between noise suppression and phase delay. Phase delay may cause a change in phase margin, stability of the whole system, and accuracy of present information in the signal. Unlike the low pass filter (LPF), a conventional signal filter, the KF minimizes the phase delay [19]. The KF is capable of processing the signal by overcoming the phase delay problem even using a low-cost load cell. This paper suggests a robust and precise tension control method for the R2R system and is organized as follows. In Section 2, we suggest dynamic model of the R2R system and how to identify the nominal parameters of the system experimentally. In Section 3, the design of a signal filter is presented.