Abstract
This study investigates the iterative learning control of a sequencing batch reactor for the production of polyhydroxybutyrate (PHB). In order to overcome the effect of model plant mismatches and unknown disturbances, a batch to batch iterative learning control strategy with incrementally updated models is developed. The reference batch is taken as the immediate previous batch in order to cope with nonlinearities and process variations. After each batch, the newly obtained process operation data is added to the historical process data base and an updated linearised model is re-identified. To cope with colinearity in the modeling data, principal component regression and partial least squares regression are used in identifying batch-wise linearised models. The proposed technique has been successfully applied to a sequencing batch reactor for the production of PHB.
Original language | English |
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Title of host publication | 2015 20th International Conference on Methods and Models in Automation and Robotics, MMAR 2015 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 459-464 |
Number of pages | 6 |
ISBN (Electronic) | 9781479987016 |
DOIs | |
Publication status | Published - 29 Sep 2015 |
Event | 20th International Conference on Methods and Models in Automation and Robotics, MMAR 2015 - Miedzyzdroje, Poland Duration: 24 Aug 2015 → 27 Aug 2015 |
Conference
Conference | 20th International Conference on Methods and Models in Automation and Robotics, MMAR 2015 |
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Country | Poland |
City | Miedzyzdroje |
Period | 24/08/15 → 27/08/15 |
Keywords
- batch processes
- iterative learning control
- linearised models
- PHB
- sequencing batch reactor