Q-learning-based controller for fed-batch yeast fermentation
Industrial fed-batch yeast fermentation process is a typical nonlinear dynamic process that requires good control technique and monitoring to optimize the yeast production. This chapter explores the applicability of Q-learning in determining the feed flow rate in a fed-batch yeast fermentation proce...
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2013
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my.ums.eprints.203542018-06-27T01:23:20Z https://eprints.ums.edu.my/id/eprint/20354/ Q-learning-based controller for fed-batch yeast fermentation Chuo, Helen Sin Ee Tan, Min Keng Tham, Heng Jin Teo, Kenneth Tze Kin TP Chemical technology Industrial fed-batch yeast fermentation process is a typical nonlinear dynamic process that requires good control technique and monitoring to optimize the yeast production. This chapter explores the applicability of Q-learning in determining the feed flow rate in a fed-batch yeast fermentation process to achieve multiobjectives optimization. However, to develop such control system, the complex nature of the yeast metabolism that will affect the system stability has to be considered. Q-learning is well known for its interactive properties with the process environment and is suitable for the learning of system dynamic. Therefore, the utilization and performance of Q-learning to seek for the optimal gain for the controller is studied in this chapter. Meanwhile, the performance of Q-learning under the process disturbance is also tested. © Springer Science+Business Media New York 2013. Springer US 2013 Book Chapter NonPeerReviewed text en https://eprints.ums.edu.my/id/eprint/20354/1/Q.pdf Chuo, Helen Sin Ee and Tan, Min Keng and Tham, Heng Jin and Teo, Kenneth Tze Kin (2013) Q-learning-based controller for fed-batch yeast fermentation. Developments in Sustainable Chemical and Bioprocess Technology. pp. 219-225. ISSN 978-1-4614-6207-1 https://dx.doi.org/10.1007/978-1-4614-6208-8_28 |
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TP Chemical technology Chuo, Helen Sin Ee Tan, Min Keng Tham, Heng Jin Teo, Kenneth Tze Kin Q-learning-based controller for fed-batch yeast fermentation |
| description |
Industrial fed-batch yeast fermentation process is a typical nonlinear dynamic process that requires good control technique and monitoring to optimize the yeast production. This chapter explores the applicability of Q-learning in determining the feed flow rate in a fed-batch yeast fermentation process to achieve multiobjectives optimization. However, to develop such control system, the complex nature of the yeast metabolism that will affect the system stability has to be considered. Q-learning is well known for its interactive properties with the process environment and is suitable for the learning of system dynamic. Therefore, the utilization and performance of Q-learning to seek for the optimal gain for the controller is studied in this chapter. Meanwhile, the performance of Q-learning under the process disturbance is also tested. © Springer Science+Business Media New York 2013. |
| format |
Book Chapter |
| author |
Chuo, Helen Sin Ee Tan, Min Keng Tham, Heng Jin Teo, Kenneth Tze Kin |
| author_facet |
Chuo, Helen Sin Ee Tan, Min Keng Tham, Heng Jin Teo, Kenneth Tze Kin |
| author_sort |
Chuo, Helen Sin Ee |
| title |
Q-learning-based controller for fed-batch yeast fermentation |
| title_short |
Q-learning-based controller for fed-batch yeast fermentation |
| title_full |
Q-learning-based controller for fed-batch yeast fermentation |
| title_fullStr |
Q-learning-based controller for fed-batch yeast fermentation |
| title_full_unstemmed |
Q-learning-based controller for fed-batch yeast fermentation |
| title_sort |
q-learning-based controller for fed-batch yeast fermentation |
| publisher |
Springer US |
| publishDate |
2013 |
| url |
https://eprints.ums.edu.my/id/eprint/20354/1/Q.pdf https://eprints.ums.edu.my/id/eprint/20354/ https://dx.doi.org/10.1007/978-1-4614-6208-8_28 |
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