201. A dynamic subspace model for predicting burn-through point in iron sintering process.
- Author
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Cao, Weihua, Wu, Min, She, Jinhua, Zhang, Yongyue, and Cao, Yuan
- Subjects
- *
SINTERING , *IRON metallurgy , *SUBSPACES (Mathematics) , *DYNAMIC models , *GENETIC programming - Abstract
This paper presents a dynamic modeling method for predicting the exhaust-gas temperature (EGT) of the burn-through point (BTP) in an iron sintering process. First, a subspace modeling method is used to build a steady-state subspace model (SSSM) for the EGT at a steady state. Then, a dynamic subspace model (DSM) that is driven by the errors of the SSSMs is developed to improve the accuracy of the EGT prediction in a continuous process. Finally, a grid search dynamic subspace model (GSDSM) is established to find the best parameters for each SSSM in the DSM. Verification results show that the GSDSM yields a predicted EGT with a high precision, which can be implemented in a predicting controller an actual sintering process. [ABSTRACT FROM AUTHOR]
- Published
- 2018
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