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Article
| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Yuan Tian Jie Zhang Morris, J. |
| Copyright Year | 2001 |
| Description | Author affiliation: Dept. of Chem. & Process Eng., Univ. of Newcastle, Newcastle upon Tyne, UK (Yuan Tian) |
| Abstract | A hybrid recurrent neural network model based on-line re-optimisation control strategy is developed for batch polymerisation reactors. The hybrid model contains a simplified mechanistic model covering material balance and simplified reaction kinetics only and recurrent neural networks. Based on this hybrid neural network model, optimal control policy can be calculated. A difficulty in the optimal control of batch polymerisation reactors is that optimisation effort can be seriously hampered by unknown disturbances such as reactive impurities and reactor fouling. A technique for on-line estimation of reactive impurity and reactor fouling has been developed by Zhang et al. (1999). In this contribution, on-line reactive impurity estimation is combined with batch reactor optimal control to form a novel re-optimisation control strategy. When there exists an unknown amount of reactive impurities, the off-line calculated optimal control profile will be no longer optimal. On-line impurity estimation is applied to estimate the amount of reactive impurities during the early stage of the batch. Based on the estimated amount of reactive impurities, on-line re-optimisation is applied to calculate the optimal reactor temperature profile for the remaining time period of the batch reactor operation. This approach is illustrated on the optimisation control of a simulated batch MMA polymerisation process. |
| Sponsorship | American Autom. Control Council |
| Starting Page | 350 |
| Ending Page | 355 |
| File Size | 511956 |
| Page Count | 6 |
| File Format | |
| ISBN | 0780364953 |
| ISSN | 07431619 |
| DOI | 10.1109/ACC.2001.945569 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2001-06-25 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | American Automatic Control Council(AACC) |
| Subject Keyword | Polymers Inductors Optimal control Impurities Neural networks Recurrent neural networks Chemical analysis Process control Chemical technology Kinetic theory |
| Content Type | Text |
| Resource Type | Article |
| Subject | Electrical and Electronic Engineering |
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