Azwar, - and Hussain, Mohd Azlan and Ramachandran, K.B. (2006) The study of neural network-based controller for controlling dissolved oxygen concentration in a sequencing batch reactor. Bioprocess and Biosystems Engineering, 28 (4). pp. 251-265. ISSN 1615-7591, DOI https://doi.org/10.1007/s00449-005-0031-2.
Full text not available from this repository.Abstract
The design and development of the neural network (NN)-based controller performance for the activated sludge process in sequencing batch reactor (SBR) is presented in this paper. Here we give a comparative study of various neural network (NN)-based controllers such as the direct inverse control, internal model control (IMC) and hybrid NN control strategies to maintain the dissolved oxygen (DO) level of an activated sludge system by manipulating the air flow rate. The NN inverse model-based controller with the model-based scheme represents the controller, which relies solely upon the simple NN inverse model. In the IMC, both the forward and inverse models are used directly as elements within the feedback loop. The hybrid NN control consists of a basic NN controller in parallel with a proportional integral (PI) controller. Various simulation tests involving multiple set-point changes, disturbances rejection and noise effects were performed to review the performances of these various controllers. From the results it can be seen that hybrid controller gives the best results in tracking set-point changes under disturbances and noise effects.
| Item Type: | Article |
|---|---|
| Funders: | UNSPECIFIED |
| Additional Information: | 018HB Times Cited:0 Cited References Count:24 |
| Uncontrolled Keywords: | sequencing batch reactor; dissolved oxygen; direct inverse neural network control; internal model control; hybrid neural network control; activated-sludge process; water treatment-plant; waste-water; removal; identification; model. |
| Subjects: | T Technology > TA Engineering (General). Civil engineering (General) T Technology > TP Chemical technology |
| Divisions: | Faculty of Engineering |
| Depositing User: | Mr Jenal S |
| Date Deposited: | 10 Jul 2013 04:35 |
| Last Modified: | 17 Dec 2020 01:09 |
| URI: | http://eprints.um.edu.my/id/eprint/7055 |
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