Optimal control of batch reactors using generic model control (GMC) and neural network
On-line implementation of the optimal reactor temperature profiles in batch reactors is considered here. The optimal reactor temperature profiles are obtained by solving dynamic optimisation problems off-line to achieve maximum conversion to the desired product. Generic Model Control (GMC) algorithm...
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| 主要な著者: | , , |
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| フォーマット: | 論文 |
| 出版事項: |
Elsevier
2000
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| 主題: | |
| オンライン･アクセス: | http://eprints.um.edu.my/7093/ http://www.scopus.com/inward/record.url?eid=2-s2.0-33747412716&partnerID=40&md5=5b1b30263c1b013c3fbe5141a4bd821b |
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| 要約: | On-line implementation of the optimal reactor temperature profiles in batch reactors is considered here. The optimal reactor temperature profiles are obtained by solving dynamic optimisation problems off-line to achieve maximum conversion to the desired product. Generic Model Control (GMC) algorithm is used to design the controller to track the optimal temperature profiles (dynamic set points). Neural Network technique is used as the on-line estimator to estimate the amount of heat released by the chemical reaction. A complex reaction scheme is considered in this work to illustrate the ideas. The results clearly show that the GMC controller coupled with a Neural Network based estimator tracks the optimal temperature profiles very well to obtain the desired products on target. |
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