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Communication

Optimizing Yarn Tension in Textile Production with Tension–Position Cascade Control Method Using Kalman Filter

1
School of Mechanical Engineering, Yeungnam University, 280 Daehak-Ro, Gyeongsan 38541, Republic of Korea
2
Energy System Research Center, Korea Textile Machinery Convergence Research Institute, Gyeongsan 38542, Republic of Korea
*
Authors to whom correspondence should be addressed.
Sensors 2023, 23(12), 5494; https://doi.org/10.3390/s23125494
Submission received: 6 April 2023 / Revised: 19 May 2023 / Accepted: 30 May 2023 / Published: 11 June 2023
(This article belongs to the Topic Industrial Control Systems)

Abstract

The production of textiles has undergone a considerable transformation, progressing from its primitive origins in hand-weaving to the implementation of contemporary automated systems. Weaving yarn into fabric is a crucial process in the textile industry that requires meticulous attention to output quality products, particularly in the tension control section. The efficiency of the tension controller in relation to the yarn tension significantly affects the quality of the resulting fabric, as proper tension control leads to strong, uniform, and aesthetically pleasing fabric, while poor tension control can cause defects and yarn breakage, leading to production downtime and increased costs. Maintaining the desired yarn tension during textile production is crucial, although it poses several problems, such as the continuous diameter change of the unwinder and rewinder sections leading to system change. Another problem faced by the industrial operation is maintaining proper tension on the yarn while changing the roll-to-roll operation velocity. In this paper, an optimized method for controlling yarn tension through the cascade control of tension and position, incorporating feedback controllers, feedforward, and disturbance observers, has been proposed to make the system more robust and suitable for industrial use. In addition, an optimum signal processor has been designed to obtain sensor data with reduced noise and minimal phase difference.
Keywords: roll-to-roll control; tension–position cascade control; control schematic with disturbance observer; signal processing with Kalman filter; robustness control roll-to-roll control; tension–position cascade control; control schematic with disturbance observer; signal processing with Kalman filter; robustness control

Share and Cite

MDPI and ACS Style

Neaz, A.; Lee, E.H.; Jin, T.H.; Cho, K.C.; Nam, K. Optimizing Yarn Tension in Textile Production with Tension–Position Cascade Control Method Using Kalman Filter. Sensors 2023, 23, 5494. https://doi.org/10.3390/s23125494

AMA Style

Neaz A, Lee EH, Jin TH, Cho KC, Nam K. Optimizing Yarn Tension in Textile Production with Tension–Position Cascade Control Method Using Kalman Filter. Sensors. 2023; 23(12):5494. https://doi.org/10.3390/s23125494

Chicago/Turabian Style

Neaz, Ahmed, Eun Ha Lee, Tae Hwan Jin, Kyung Chul Cho, and Kanghyun Nam. 2023. "Optimizing Yarn Tension in Textile Production with Tension–Position Cascade Control Method Using Kalman Filter" Sensors 23, no. 12: 5494. https://doi.org/10.3390/s23125494

APA Style

Neaz, A., Lee, E. H., Jin, T. H., Cho, K. C., & Nam, K. (2023). Optimizing Yarn Tension in Textile Production with Tension–Position Cascade Control Method Using Kalman Filter. Sensors, 23(12), 5494. https://doi.org/10.3390/s23125494

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