Control of a batch polymerization system using hybrid neural network first principle model
In this work, the utilization of neural network in hybrid with first principle models for modelling and control of a batch polymerization process was investigated. Following the steps of the methodology, hybrid neural network (HNN) forward models and HNN inverse model of the process were first devel...
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| Format: | Article |
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Canadian Journal of Chemical Engineering
2007
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| _version_ | 1825719316414201856 |
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| author | Wei, N.C. Hussain, Mohd Azlan Wahab, Ahmad Khairi Abdul |
| author_facet | Wei, N.C. Hussain, Mohd Azlan Wahab, Ahmad Khairi Abdul |
| author_sort | Wei, N.C. |
| collection | UM |
| description | In this work, the utilization of neural network in hybrid with first principle models for modelling and control of a batch polymerization process was investigated. Following the steps of the methodology, hybrid neural network (HNN) forward models and HNN inverse model of the process were first developed and then the performance of the model in direct inverse control strategy and internal model control (IMC) strategy was investigated. For comparison purposes, the performance of conventional neural network and PID controller in control was compared with the proposed HNN. The results show that HNN is able to control perfectly for both set points tracking and disturbance rejection studies. |
| first_indexed | 2024-03-06T05:17:49Z |
| format | Article |
| id | um.eprints-7046 |
| institution | Universiti Malaya |
| last_indexed | 2024-03-06T05:17:49Z |
| publishDate | 2007 |
| publisher | Canadian Journal of Chemical Engineering |
| record_format | dspace |
| spelling | um.eprints-70462021-02-10T03:46:11Z http://eprints.um.edu.my/7046/ Control of a batch polymerization system using hybrid neural network first principle model Wei, N.C. Hussain, Mohd Azlan Wahab, Ahmad Khairi Abdul TA Engineering (General). Civil engineering (General) TP Chemical technology In this work, the utilization of neural network in hybrid with first principle models for modelling and control of a batch polymerization process was investigated. Following the steps of the methodology, hybrid neural network (HNN) forward models and HNN inverse model of the process were first developed and then the performance of the model in direct inverse control strategy and internal model control (IMC) strategy was investigated. For comparison purposes, the performance of conventional neural network and PID controller in control was compared with the proposed HNN. The results show that HNN is able to control perfectly for both set points tracking and disturbance rejection studies. Canadian Journal of Chemical Engineering 2007 Article PeerReviewed Wei, N.C. and Hussain, Mohd Azlan and Wahab, Ahmad Khairi Abdul (2007) Control of a batch polymerization system using hybrid neural network first principle model. Canadian Journal of Chemical Engineering, 85 (6). pp. 936-945. ISSN 0008-4034, http://www.scopus.com/inward/record.url?eid=2-s2.0-38349092708&partnerID=40&md5=ab1ad1231ec2198fdd0453ec74d4760e |
| spellingShingle | TA Engineering (General). Civil engineering (General) TP Chemical technology Wei, N.C. Hussain, Mohd Azlan Wahab, Ahmad Khairi Abdul Control of a batch polymerization system using hybrid neural network first principle model |
| title | Control of a batch polymerization system using hybrid neural network first principle model |
| title_full | Control of a batch polymerization system using hybrid neural network first principle model |
| title_fullStr | Control of a batch polymerization system using hybrid neural network first principle model |
| title_full_unstemmed | Control of a batch polymerization system using hybrid neural network first principle model |
| title_short | Control of a batch polymerization system using hybrid neural network first principle model |
| title_sort | control of a batch polymerization system using hybrid neural network first principle model |
| topic | TA Engineering (General). Civil engineering (General) TP Chemical technology |
| work_keys_str_mv | AT weinc controlofabatchpolymerizationsystemusinghybridneuralnetworkfirstprinciplemodel AT hussainmohdazlan controlofabatchpolymerizationsystemusinghybridneuralnetworkfirstprinciplemodel AT wahabahmadkhairiabdul controlofabatchpolymerizationsystemusinghybridneuralnetworkfirstprinciplemodel |