Computational-based framework for optimizing dynamic processes with plantmodel mismatch
A general computational sequence in optimizing the operation of a dynamic process is firstly highlighted in this paper. However, in most cases these dynamic processes include process-model mismatch, which shifts the optimal operation of the process. To overcome this, a model-mismatch estimator such...
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| Main Authors: | , |
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| Format: | Article |
| Language: | en |
| Published: |
Faculty of Computer Science and Information Technology, University of Malaya
2000
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| Subjects: | |
| Online Access: | http://eprints.um.edu.my/7087/1/Computational-based_framework_for_optimizing_dynamic_processes_with_plantmodel_mismatch.pdf http://eprints.um.edu.my/7087/ https://ejournal.um.edu.my/index.php/MJCS/article/view/5817 |
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| Summary: | A general computational sequence in optimizing the operation of a dynamic process is firstly highlighted in this paper. However, in most cases these dynamic processes include process-model mismatch, which shifts the optimal operation of the process. To overcome this, a model-mismatch estimator such as the neural network technique has been implemented in the optimization strategy. A modified general computational framework to incorporate these mismatches is developed for this purpose. The framework also allows the use of discrete process data in a continuous model to predict discrete and/or continuous mismatch profiles. The strategy is applied on a batch distillation system and the optimal operation using model mismatches is found to be comparable to that using the actual process model. |
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