Abstract
Model Predictive Control is an effective control method for nonlinear plants with constraints. However, application to large-scale systems and/or processes that require high sampling rate is quite challenging because of the heavy computation. Here we consider MPC approach for the cooling process of hot-rolled strip having 3D thermal distribution. To solve this large-scale problem, we propose a method to change the resolution of the model dynamically according to the uniformity of the thermal distributions in the directions of interest. Combined with a hierarchical control strategy to flatten the thermal distribution in a certain direction, one can balance the computational load across the cooling process.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the IECON 2016 - 42nd Annual Conference of the Industrial Electronics Society |
| Publisher | IEEE Computer Society |
| Pages | 215-222 |
| Number of pages | 8 |
| ISBN (Electronic) | 9781509034741 |
| DOIs | |
| Publication status | Published - Dec 21 2016 |
| Event | 42nd Conference of the Industrial Electronics Society, IECON 2016 - Florence, Italy Duration: Oct 24 2016 → Oct 27 2016 |
Other
| Other | 42nd Conference of the Industrial Electronics Society, IECON 2016 |
|---|---|
| Country | Italy |
| City | Florence |
| Period | 10/24/16 → 10/27/16 |
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Keywords
- Model Predictive Control
- Multi Resolution
- Process Modeling
ASJC Scopus subject areas
- Control and Systems Engineering
- Electrical and Electronic Engineering
Cite this
Model predictive control of hot-rolled strip cooling process using variable-resolution model. / Hirata, Kentaro; Udagawa, Daijiro; Masui, Yoichiro; Nakamura, Yukinori.
Proceedings of the IECON 2016 - 42nd Annual Conference of the Industrial Electronics Society. IEEE Computer Society, 2016. p. 215-222 7793811.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Model predictive control of hot-rolled strip cooling process using variable-resolution model
AU - Hirata, Kentaro
AU - Udagawa, Daijiro
AU - Masui, Yoichiro
AU - Nakamura, Yukinori
PY - 2016/12/21
Y1 - 2016/12/21
N2 - Model Predictive Control is an effective control method for nonlinear plants with constraints. However, application to large-scale systems and/or processes that require high sampling rate is quite challenging because of the heavy computation. Here we consider MPC approach for the cooling process of hot-rolled strip having 3D thermal distribution. To solve this large-scale problem, we propose a method to change the resolution of the model dynamically according to the uniformity of the thermal distributions in the directions of interest. Combined with a hierarchical control strategy to flatten the thermal distribution in a certain direction, one can balance the computational load across the cooling process.
AB - Model Predictive Control is an effective control method for nonlinear plants with constraints. However, application to large-scale systems and/or processes that require high sampling rate is quite challenging because of the heavy computation. Here we consider MPC approach for the cooling process of hot-rolled strip having 3D thermal distribution. To solve this large-scale problem, we propose a method to change the resolution of the model dynamically according to the uniformity of the thermal distributions in the directions of interest. Combined with a hierarchical control strategy to flatten the thermal distribution in a certain direction, one can balance the computational load across the cooling process.
KW - Model Predictive Control
KW - Multi Resolution
KW - Process Modeling
UR - http://www.scopus.com/inward/record.url?scp=85010029783&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85010029783&partnerID=8YFLogxK
U2 - 10.1109/IECON.2016.7793811
DO - 10.1109/IECON.2016.7793811
M3 - Conference contribution
AN - SCOPUS:85010029783
SP - 215
EP - 222
BT - Proceedings of the IECON 2016 - 42nd Annual Conference of the Industrial Electronics Society
PB - IEEE Computer Society
ER -