Automatic Gauge Control in Rolling Process Based on Multiple Smith Predictor Models
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 contro...
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| Format: | Article |
| Language: | English |
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Wiley
2014-01-01
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| Series: | Abstract and Applied Analysis |
| Online Access: | http://dx.doi.org/10.1155/2014/872418 |
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| author | Jiangyun Li Kang Wang Yang Li |
| author_facet | Jiangyun Li Kang Wang Yang Li |
| author_sort | Jiangyun Li |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-f47244b9a0804cacbf66272416be5fe2 |
| institution | Kabale University |
| issn | 1085-3375 1687-0409 |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Abstract and Applied Analysis |
| spelling | doaj-art-f47244b9a0804cacbf66272416be5fe22025-02-03T01:30:12ZengWileyAbstract and Applied Analysis1085-33751687-04092014-01-01201410.1155/2014/872418872418Automatic Gauge Control in Rolling Process Based on Multiple Smith Predictor ModelsJiangyun Li0Kang Wang1Yang Li2School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, ChinaSchool of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, ChinaSchool of International Studies, Communication University of China (CUC), Beijing 100024, ChinaAutomatic 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.http://dx.doi.org/10.1155/2014/872418 |
| spellingShingle | Jiangyun Li Kang Wang Yang Li Automatic Gauge Control in Rolling Process Based on Multiple Smith Predictor Models Abstract and Applied Analysis |
| title | Automatic Gauge Control in Rolling Process Based on Multiple Smith Predictor Models |
| title_full | Automatic Gauge Control in Rolling Process Based on Multiple Smith Predictor Models |
| title_fullStr | Automatic Gauge Control in Rolling Process Based on Multiple Smith Predictor Models |
| title_full_unstemmed | Automatic Gauge Control in Rolling Process Based on Multiple Smith Predictor Models |
| title_short | Automatic Gauge Control in Rolling Process Based on Multiple Smith Predictor Models |
| title_sort | automatic gauge control in rolling process based on multiple smith predictor models |
| url | http://dx.doi.org/10.1155/2014/872418 |
| work_keys_str_mv | AT jiangyunli automaticgaugecontrolinrollingprocessbasedonmultiplesmithpredictormodels AT kangwang automaticgaugecontrolinrollingprocessbasedonmultiplesmithpredictormodels AT yangli automaticgaugecontrolinrollingprocessbasedonmultiplesmithpredictormodels |