Neural Network Inverse Decoupling Control of Flatness and Edge Drop for Tandem Cold Rolling Mill

Xiaomin Zhou; Yun Feng Wu; Yang Jun Mao

doi:10.4028/www.scientific.net/AMR.562-564.1977

Paper Titles

The Peak Resolution of Diffuse X-Ray Diffraction Pattern of Tibetan Medicine
p.1959

Application of Neural Network for Nonlinear Predictive Control
p.1964

Non-Fragile Robust H∞ Control for Linear Uncertain Switched Systems with Delayed Perturbations
p.1968

Real-Time Detection Method on Draft of Inland Departure Ships
p.1972

Neural Network Inverse Decoupling Control of Flatness and Edge Drop for Tandem Cold Rolling Mill
p.1977

Research on Intrusion Detection for the Internet of Things Based on Clone Selection Principle
p.1982

Study on the Road Rigidity Detecting System Based on LabVIEW
p.1986

Risk Analysis of Distributed Energy Source in the Smart Grid
p.1990

Optimization Design of Marine Waste Heat Recovery System Based on PSO-GA Algorithm
p.1994

HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 562-564Neural Network Inverse Decoupling Control of...

Neural Network Inverse Decoupling Control of Flatness and Edge Drop for Tandem Cold Rolling Mill

Abstract:

Realizing the decoupling control of them is one of the most important issues to achieve the flatness and edge drop high-precision control. In this paper, the flatness and edge drop control capabilities of all the control actuators are analyzed. The coupling relation of flatness and edge drop is analyzed. The neural network inverse decoupling control method is proposed to realize the decoupling control of flatness and edge drop. Simulation results represent that the flatness and edge drop control performance is improved effectively.

You might also be interested in these eBooks

Materials Engineering and Automatic Control

View Preview

Info:

Periodical:

Advanced Materials Research (Volumes 562-564)

Pages:

1977-1981

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.562-564.1977

Citation:

Cite this paper

Online since:

August 2012

Authors:

Xiaomin Zhou, Yun Feng Wu, Yang Jun Mao

Keywords:

Decoupling Control, Edge Drop, Flatness, Inverse System, Neural Network (NN)

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] Yang G H, Zhang J, Cao J G, et al．Edge Control Technology of 4-hi and 6-hi Tandem Cold Rolling Mills[J]．Metallurgical Equipment, 2009，(178)：1-5.

Google Scholar

[2] Lu H T, Cao J G, Zhang J, et al. Edge drop control of a taper roll during continuous cold rolling[J]. Journal of University of Science and Technology Beijing, 2006, 28(8)：774-777.

Google Scholar

[3] Zhou X M, Zhang Q D, Wu P. The Summary of the Strip Edge Drop Control Technology[J]. ShangHai Metals. 2007, 29(1)：21-24.

Google Scholar

[4] Yang G H, Cao J G, Zhang J, et al. Comprehensive Control for Strip Edge Drop&Crown and Flatness on Tandem Cold Rolling Mill[J]．Metallurgical Equipment. 2008，(172)：1-5. ）.

Google Scholar

[5] Zhou X M, Zhang Q D, Wang C S, et al. Edge Drop and Flatness Decoupling Control on UCMW Cold Mill[J]．Iron and Steel. 2007, 42(5)：55-57.

Google Scholar

[6] Hong Y Z, Zhu H Q, Wu Q H, et al．Dynamic Decoupling Control of AC-DC Hybrid Magnetic Bearing Based on Neural Network Inverse Method [A]．International Conference on Electrical Machines and Systems [C]．Zhenjiang, 2008：3940-3944.

Google Scholar

[7] Song Y X, Ma J L, Zhang H X, et al．The Decoupling Control of Induction Motor Based on Artificial Neural Network Inverse System Method [A]．International Conference on Electrical and Control Engineering [C]．Lianyungang, 2010：2287-2291.

DOI: 10.1109/icece.2010.564

Google Scholar

[8] Peng P. Research on Coupling Relations and Decoupling Control for Wide Strip Tandem Cold Mill. [D]. Beijing: University of Science and Technology Beijing, (2008).

Google Scholar