The Control Algorithm Research of Yarn Tension for Winding Machine Based on Grey Prediction Model

Can Cai Wang; Hai Xia Zhao

doi:10.4028/www.scientific.net/AMM.519-520.1305

Paper Titles

Construction and Application of Remote Sensing Based Evapotranspiration System in Hai Basin
p.1281

Preliminary Analysis on the Wind Retrieval Method in Nowcasting
p.1287

A Class of Difference Inequality and an Application to Discrete-Time Control Systems
p.1295

The Pest Management Model with Impulsive Control
p.1299

The Control Algorithm Research of Yarn Tension for Winding Machine Based on Grey Prediction Model
p.1305

An Improvement of IED Configuration Tool and Modeling for Transformer Condition Monitoring IED
p.1309

Research of Trajectory Planning of a High-Altitude Long-Range Gliding Unmanned Underwater Vehicle
p.1313

Study of Electric Power Grid Based on Improved Data Envelopment Analysis Model
p.1321

A Solution for Single Point of Failure of Cloud Computing Platform in Electric Power Corporation
p.1325

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 519-520The Control Algorithm Research of Yarn Tension for...

The Control Algorithm Research of Yarn Tension for Winding Machine Based on Grey Prediction Model

Abstract:

For building high precision yarn tension control model, grey prediction method was first employed in this paper. The commonly used GM(1,1) model was modified by means of changing the coefficient a and b. Then the next tension value was forecasted from the previous test values by the modified GM(1,1) model. Then the forecasted values and the referred value were import into the self-adaption PID model. And the PID model output the control sign to magnetic particle clutch. The simulation of the control algorithm was completed in MATLAB 7.0. The simulation result showed that the proposed control algorithm had better precision than general PID and general grey prediction control algorithm.

You might also be interested in these eBooks

View Preview

Info:

Periodical:

Applied Mechanics and Materials (Volumes 519-520)

Pages:

1305-1308

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.519-520.1305

Citation:

Cite this paper

Online since:

February 2014

Authors:

Can Cai Wang*, Hai Xia Zhao

Keywords:

Grey Prediction, Winding Machine, Yarn Tension

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

* - Corresponding Author

References

[1] Wang Chunxiaong, Yang Ruqing. Research on a precision tension control system with a magnetic particle clutch as the actuator[J]. Int J Adv Manuf Technol. Vol. 27 (2005), pp.7-13.

DOI: 10.1007/s00170-004-2190-8

Google Scholar

[2] Susanta. Improving yarn quality through multi-response optimization of electronic yarn clearer in winding machine[J]. Int J Adv Manuf Technol. Vol. 56(2011), pp.387-396.

DOI: 10.1007/s00170-011-3163-3

Google Scholar

[3] Liu Hong-jun. Adaptive grey prediction PID control for time-variance large delay system[J]. Journal of North China Electric Power University. Vol. 31(2009). pp.44-50.

Google Scholar

[4] Chun-I Chen. The necessary and sufficient condition for GM(1, 1) grey prediction model[J]. Applied Mathematics and Computation. Vol, 219(2013), pp.6152-6162.

DOI: 10.1016/j.amc.2012.12.015

Google Scholar

[5] Tzu-Li Tien. A research on the grey prediction model GM(1, n)[J]. Applied Mathematics and Computation. Vol, 218(2012), pp.4903-4916.

DOI: 10.1016/j.amc.2011.10.055

Google Scholar

[6] G. Hivet. Design and Potentiality of an Apparatus for Measuring Yarn/Yarn and Fabric/Fabric Friction[J]. Experimental Mechanics. Vol. 52(2012), p.1123–1136.

DOI: 10.1007/s11340-011-9566-0

Google Scholar

[7] Young Seok Koo. Correlation of Yarn Tension with Parameters in the Knitting Process[J]. Fibers and Polymers. Vol. 3(2002), pp.80-84.

DOI: 10.1007/bf02875404

Google Scholar