Automatic Gauge Control in Rolling Process Based on Multiple Smith Predictor Models

Joint Authors

Li, Jiang-Yun
Wang, Kang
Li, Yang

Source

Abstract and Applied Analysis

Issue

Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-10, 10 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2014-11-24

Country of Publication

Egypt

No. of Pages

10

Main Subjects

Mathematics

Abstract EN

Automatic rolling process is a high-speed system which always requires high-speed control and communication capabilities.

Meanwhile, it is also a typical complex electromechanical system; distributed control has become the mainstream of computer control system for rolling mill.

Generally, the control system adopts the 2-level control structure—basic automation (Level 1) and process control (Level 2)—to achieve the automatic gauge control.

In Level 1, there is always a certain distance between the roll gap of each stand and the thickness testing point, leading to the time delay of gauge control.

Smith predictor is a method to cope with time-delay system, but the practical feedback control based on traditional Smith predictor cannot get the ideal control result, because the time delay is hard to be measured precisely and in some situations it may vary in a certain range.

In this paper, based on adaptive Smith predictor, we employ multiple models to cover the uncertainties of time delay.

The optimal model will be selected by the proposed switch mechanism.

Simulations show that the proposed multiple Smith model method exhibits excellent performance in improving the control result even for system with jumping time delay.

American Psychological Association (APA)

Li, Jiang-Yun& Wang, Kang& Li, Yang. 2014. Automatic Gauge Control in Rolling Process Based on Multiple Smith Predictor Models. Abstract and Applied Analysis،Vol. 2014, no. 2014, pp.1-10.
https://search.emarefa.net/detail/BIM-1034064

Modern Language Association (MLA)

Li, Jiang-Yun…[et al.]. Automatic Gauge Control in Rolling Process Based on Multiple Smith Predictor Models. Abstract and Applied Analysis No. 2014 (2014), pp.1-10.
https://search.emarefa.net/detail/BIM-1034064

American Medical Association (AMA)

Li, Jiang-Yun& Wang, Kang& Li, Yang. Automatic Gauge Control in Rolling Process Based on Multiple Smith Predictor Models. Abstract and Applied Analysis. 2014. Vol. 2014, no. 2014, pp.1-10.
https://search.emarefa.net/detail/BIM-1034064

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1034064