A comparative study between Neural Networks (NN)-based and adaptive-PID controllers for the optimal bio-hydrogen gas production in microbial electrolysis cell reactor
The main challenge of the hydrogen production study for the MEC reactor is to obtain a good automatic control system due to the nonlinearity and complexity of the microbial interactions. To address this issue an integrated approach involving process modeling, optimization and advanced control has to...
| Main Authors: | , , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2015
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| Online Access: | http://eprints.um.edu.my/14129/1/A_Comparative_study_between_Neural_Networks.pdf |
| _version_ | 1825720473622675456 |
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| author | Azwar, M.Y. Hussain, Mohd Azlan Wahab, Ahmad Khairi Abdul Zanil, M.F. |
| author_facet | Azwar, M.Y. Hussain, Mohd Azlan Wahab, Ahmad Khairi Abdul Zanil, M.F. |
| author_sort | Azwar, M.Y. |
| collection | UM |
| description | The main challenge of the hydrogen production study for the MEC reactor is to obtain a good automatic control system due to the nonlinearity and complexity of the microbial interactions. To address this issue an integrated approach involving process modeling, optimization and advanced control has to be implemented. This work focus on the
controller’s performance in the control system; neural network (NN)-based and Adaptive-PID controllers. The study has been carried out under optimal condition for the production of bio-hydrogen gas wherein the controller output are based on the correlation of the optimal current and voltage to the MEC. A Ziegler–Nichols tuning method and an adaptive gain technique have been used to design the PID controller, while the neural network controller has been designed from the inverse response of the MEC neural network model. |
| first_indexed | 2024-03-06T05:35:41Z |
| format | Conference or Workshop Item |
| id | um.eprints-14129 |
| institution | Universiti Malaya |
| language | English |
| last_indexed | 2024-03-06T05:35:41Z |
| publishDate | 2015 |
| record_format | dspace |
| spelling | um.eprints-141292021-02-10T03:22:08Z http://eprints.um.edu.my/14129/ A comparative study between Neural Networks (NN)-based and adaptive-PID controllers for the optimal bio-hydrogen gas production in microbial electrolysis cell reactor Azwar, M.Y. Hussain, Mohd Azlan Wahab, Ahmad Khairi Abdul Zanil, M.F. TP Chemical technology The main challenge of the hydrogen production study for the MEC reactor is to obtain a good automatic control system due to the nonlinearity and complexity of the microbial interactions. To address this issue an integrated approach involving process modeling, optimization and advanced control has to be implemented. This work focus on the controller’s performance in the control system; neural network (NN)-based and Adaptive-PID controllers. The study has been carried out under optimal condition for the production of bio-hydrogen gas wherein the controller output are based on the correlation of the optimal current and voltage to the MEC. A Ziegler–Nichols tuning method and an adaptive gain technique have been used to design the PID controller, while the neural network controller has been designed from the inverse response of the MEC neural network model. 2015-06 Conference or Workshop Item PeerReviewed application/pdf en http://eprints.um.edu.my/14129/1/A_Comparative_study_between_Neural_Networks.pdf Azwar, M.Y. and Hussain, Mohd Azlan and Wahab, Ahmad Khairi Abdul and Zanil, M.F. (2015) A comparative study between Neural Networks (NN)-based and adaptive-PID controllers for the optimal bio-hydrogen gas production in microbial electrolysis cell reactor. In: 12th International Symposium on Process Systems Engineering and 25th European Symposium on Computer Aided Process Engineering, 31 May – 4 June 2015, Copenhagen, Denmark. |
| spellingShingle | TP Chemical technology Azwar, M.Y. Hussain, Mohd Azlan Wahab, Ahmad Khairi Abdul Zanil, M.F. A comparative study between Neural Networks (NN)-based and adaptive-PID controllers for the optimal bio-hydrogen gas production in microbial electrolysis cell reactor |
| title | A comparative study between Neural Networks (NN)-based and adaptive-PID controllers for the optimal bio-hydrogen gas production in microbial electrolysis cell reactor |
| title_full | A comparative study between Neural Networks (NN)-based and adaptive-PID controllers for the optimal bio-hydrogen gas production in microbial electrolysis cell reactor |
| title_fullStr | A comparative study between Neural Networks (NN)-based and adaptive-PID controllers for the optimal bio-hydrogen gas production in microbial electrolysis cell reactor |
| title_full_unstemmed | A comparative study between Neural Networks (NN)-based and adaptive-PID controllers for the optimal bio-hydrogen gas production in microbial electrolysis cell reactor |
| title_short | A comparative study between Neural Networks (NN)-based and adaptive-PID controllers for the optimal bio-hydrogen gas production in microbial electrolysis cell reactor |
| title_sort | comparative study between neural networks nn based and adaptive pid controllers for the optimal bio hydrogen gas production in microbial electrolysis cell reactor |
| topic | TP Chemical technology |
| url | http://eprints.um.edu.my/14129/1/A_Comparative_study_between_Neural_Networks.pdf |
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