Data‐driven plant‐model mismatch estimation for dynamic matrix control systems

2020 ◽  
Vol 30 (17) ◽  
pp. 7103-7129
Author(s):  
Xiaodong Xu ◽  
Jodie M. Simkoff ◽  
Michael Baldea ◽  
Leo H. Chiang ◽  
Ivan Castillo ◽  
...  
Keyword(s):  
Control Systems ◽  
Data Driven ◽  
Dynamic Matrix Control ◽  
Plant Model ◽  
Dynamic Matrix ◽  
Model Mismatch ◽  
Matrix Control

Constrained dynamic matrix control strategy for a monitoring system for AGC of hot strip mills

2020 ◽  
Vol 117 (3) ◽  
pp. 308
Author(s):  
Yin Fang-chen ◽  
Yu Liu-Qi
Keyword(s):  
Monitoring System ◽  
Control Strategy ◽  
Smith Predictor ◽  
Model Parameters ◽  
Control Performance ◽  
Dynamic Matrix Control ◽  
Dynamic Matrix ◽  
Model Mismatch ◽  
Hot Strip ◽  
Matrix Control

In the hot strip rolling process, the performance of a monitoring system for automatic gauge control (MN-AGC) is influenced greatly by the model mismatch which is caused by the variation of model parameters values. A constrained dynamic matrix control (CDMC) strategy that includes a prediction model, rolling optimization, and feedback correction was used in the MN-AGC. First, the conventional Smith prediction-based control strategy for the MN-AGC was analyzed. Second, the performance index function and optimal control of the CDMC strategy were determined. Finally, simulations and industrial experiments were conducted. The results showed that both control strategies provided good control performance. When model mismatch occurred, the Smith predictor-based MN-AGC resulted in significant overshoot or even oscillations but the control performance of the CDMC-based MN-AGC was not influenced by changes in the model parameters.

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