Advanced Thickness and Flatness Control System for Sendzimir Mill

2019 ◽  
Author(s):  
J. Yao ◽  
T. Gong ◽  
L. Nii
Keyword(s):  
Control System ◽  
Flatness Control ◽  
Sendzimir Mill

A Flatness Control System Design Based on Actuator Efficiency Factors for Cold Rolling Mill

2010 ◽  
Vol 139-141 ◽  
pp. 1889-1893 ◽  
Author(s):  
Peng Fei Wang ◽  
Dian Hua Zhang ◽  
Xu Li ◽  
Jia Wei Liu
Keyword(s):  
Control System ◽  
Rolling Force ◽  
Quantitative Description ◽  
Learning Model ◽  
Feed Forward Control ◽  
Flatness Control ◽  
Stand Type ◽  
Loop Feedback ◽  
Efficiency Factors ◽  
Self Learning

In order to improve the flatness of cold rolled strips, strategies of closed loop feedback flatness control and rolling force feed forward control were established respectively, based on actuator efficiency factors. As the basis of flatness control system, efficiencies of flatness actuators provide a quantitative description to the law of flatness control. For the purpose of obtaining accurate efficiency factors matrixes of actuators, a self-learning model of actuator efficiency factors was established. The precision of actuator efficiency factors could be improved continuously by correlative measurement flatness data inputs. Meanwhile, the self-learning model of actuator efficiency factors permits the application of this flatness control for all possible types of actuators and every stand type. The developed flatness control system has been applied to a 1250mm single stand 6-H reversible UCM cold mill. Applications show that the flatness control system based on actuator efficiency factors is capable to obtain good flatness.

scholarly journals Decoupling Adaptive Smith Prediction Model of Flatness Closed-Loop Control and Its Application

Processes ◽  
2020 ◽  
Vol 8 (8) ◽  
pp. 895
Author(s):  
Mingming Song ◽  
Hongmin Liu ◽  
Yanghuan Xu ◽  
Dongcheng Wang ◽  
Yangyang Huang
Keyword(s):  
Mathematical Model ◽  
Control System ◽  
Time Delay ◽  
Control Method ◽  
Delay System ◽  
Control Performance ◽  
Time Delay System ◽  
Single Loop ◽  
Flatness Control ◽  
Pure Time Delay

Flatness control system is characterized by multi-parameters, strong coupling, pure time delay, which complicate the establishment of an accurate mathematical model. Therefore, a control scheme that combines dynamic decoupling, PI (Proportion and Integral) control and adaptive Smith predictive compensation is proposed. To this end, a dynamic matrix is used to decouple the control system. A multivariable coupled pure time-delay system is transformed into several independent generalized single-loop pure time-delay systems. Then, a PI-adaptive Smith predictive controller is constructed for the decoupled generalized single-loop pure time-delay system. Simulations show that the scheme has a simple and feasible structure, and good control performance. When the mathematical model of the control system is inaccurate, the control performance of adaptive Smith control method is evidently better than that of the ordinary Smith control method. The model is successfully applied to the cold rolling production site through LabVIEW, and the control accuracy is within 5I. This study reveals a new solution to the problem of coupled pure time-delay in flatness control system.

Optimization design of RBF-ARX model and application research on flatness control system

2016 ◽  
Vol 38 (1) ◽  
pp. 19-35 ◽  
Author(s):  
Xiu-Ling Zhang ◽  
Long Cheng ◽  
Shuang Hao ◽  
Wu-Yang Gao ◽  
Yong-Jin Lai
Keyword(s):  
Control System ◽  
Optimization Design ◽  
Application Research ◽  
Arx Model ◽  
Flatness Control

The Partial High Point and the Influence to the Hot Strip Profile Control

2012 ◽  
Vol 152-154 ◽  
pp. 1143-1148
Author(s):  
Xu Tao Zheng ◽  
Jie Zhang ◽  
Hong Bo Li ◽  
Hui Hui Li ◽  
Yi Su ◽  
...  
Keyword(s):  
Control System ◽  
Term Effect ◽  
Hot Strip ◽  
Long Term Effect ◽  
Strip Profile ◽  
Profile Control ◽  
Flatness Control ◽  
Strip Crown

The partial high points, always appearing when the hot strip is being rolled, not only negatively influence the quality of the hot strip, but also make a long term effect on the profile control. Via quantifying and separating the partial high points and analyzing the calculation of the strip crown, we can obtain the calculation method of the error resulted from the high points; then, on the basis of the way that the high points affect the profile and flatness control system, we can present some tactics to lessen the high points’ effect.

Flatness Control System for Hot Strip Mills

1981 ◽  
Vol 14 (2) ◽  
pp. 2483-2488
Author(s):  
N. Kitao ◽  
Y. Hirose ◽  
K. Hamada
Keyword(s):  
Control System ◽  
Hot Strip ◽  
Flatness Control ◽  
Hot Strip Mills

Improved shape control performance of a Sendzimir mill using wavelet radial basis function network and fuzzy logic actuator

2014 ◽  
Vol 229 (2) ◽  
pp. 227-243 ◽  
Author(s):  
Jeon Hyun Park ◽  
Jong Shik Kim ◽  
Seong Ik Han
Keyword(s):  
Control System ◽  
Shape Control ◽  
Fuzzy Controller ◽  
Actuator Saturation ◽  
Shape Recognition ◽  
Radial Basis Function Network ◽  
Control Performance ◽  
Radial Basis ◽  
Sendzimir Mill ◽  
Function Network

A shape control system based on a wavelet radial basis function network for a Sendzimir mill (ZRM) and fuzzy control are developed to improve the shape control performance of a conventional ZRM system. The conventional shape recognition system for a ZRM adopted an incomplete multi-layer perceptron neural network system that was constructed two decades ago. The poor shape recognition of this system leads to actuator saturation and shape control performance deterioration. Therefore, the full automatic operation of a ZRM is often stopped, and manual input need to be performed. This affects the quality, causes a decline in the productivity of the steel strip and an unnecessary waste of manpower. In this paper, a wavelet radial basis network is developed to replace the multi-layer perceptron network and consequently improve shape recognition performance. A modified fuzzy controller is also constructed to prevent actuator saturation that occurs in a conventional shape control system owing to the use of a fixed gain-based fuzzy controller. A comparative simulation based on the data measured from an actual ZRM plant demonstrates the efficacy of the proposed shape control system.

scholarly journals Decoupling Strategy and Mechanism-intelligent Model of Non Square Flatness Control System

2021 ◽  
Author(s):  
Ming-ming Song ◽  
Hong-min Liu ◽  
Yang-huan Xu ◽  
Xin-cheng Gao ◽  
Dong-cheng Wang
Keyword(s):  
Control System ◽  
Flatness Control ◽  
Intelligent Model

Advanced Flatness Control Strategies for Multivariable Optimisation Flatness Control System of Foil Rolling Mill

2013 ◽  
Vol 655-657 ◽  
pp. 1450-1455 ◽  
Author(s):  
Liang Hao ◽  
H.S. Di ◽  
D.Y. Gong ◽  
D.B. Wei ◽  
Z.Y. Jiang
Keyword(s):  
Control System ◽  
Control Systems ◽  
Rolling Mill ◽  
Rolling Force ◽  
Control Strategies ◽  
Bending Force ◽  
Foil Rolling ◽  
Flatness Control ◽  
Application Fields ◽  
Flatness Error

In cold strip or foil rolling, flatness control is an integral part of modern mill. This paper introduces two typical flatness control systems, pattern recognisation flatness control system and multivariable flatness control. It is found that the latter is effective and has wider application fields. The FEM models of its core parameters, flatness actuator efficiency, are constructed. Influencing factors, such as the rolling force, bending force as well as the tilting force are discussed. Control strategies are proposed for foil rolling. The results demonstrate that the control strategies can reduce flatness error and improve flatness quality.

Flatness adaptive control of a hot strip in finishing mills

2003 ◽  
Vol 217 (9) ◽  
pp. 1243-1252 ◽  
Author(s):  
W K Hong ◽  
J J Choi ◽  
J S Kim ◽  
J J Yi
Keyword(s):  
Control System ◽  
Work Roll ◽  
Rolled Strip ◽  
Least Mean Square ◽  
Strip Rolling ◽  
Measuring Device ◽  
Hot Strip ◽  
Flatness Control ◽  
Self Tuning ◽  
Looper System

In order to improve the flatness of a hot rolled strip in hot strip finishing mills, a new segmented looper system was developed, which is called the flatness sensing inter-stand looper (FlatSIL) system. The FlatSIL system measures the tension along the width of the strip by using segmented rolls and the tension profile is calculated. Using the tension profile, the flatness control system of the hot strip can be constructed. The new flatness control system works for the full strip length during strip rolling as long as the tension profile-measuring device and the work roll bender are activated. To control the flatness of the hot strip, a self-tuning algorithm using the recursive least mean square method was applied to update proportional-integral (PI) gains. By computer simulation and experimentation, the performance of flatness control systems was compared with fixed and self-tuning PI gains.

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