<b>Artificial neural networks to control chlorine dosing in a water treatment plant
DOI:
https://doi.org/10.4025/actascitechnol.v40i1.37275Keywords:
computational intelligence, process optimization, set-point control, water treatment plant.Abstract
Artificial neural networks in the multivariable control of chlorine dosing in the post-chlorination stage in a water treatment plant in the Greater São Paulo, Brazil, are analyzed. The plant has constant fluctuations in chlorine demand caused by natural influences related to raw water from surface source. Modeling and computer simulation were implemented in MATLAB/Simulink® environment, according to the physical and operational characteristics of the water treatment plant. Moreover, a Proportional-Integral (PI) controller was incorporated to provide better stability. Simulation results showed improved stability of free residual chlorine when compared to method currently employed, i.e. Proportional-Integral-Derivative (PID) controller that would reduce chlorine consumption in water treatment process.
Â
Downloads
Downloads
Published
How to Cite
Issue
Section
License
DECLARATION OF ORIGINALITY AND COPYRIGHTS
I Declare that current article is original and has not been submitted for publication, in part or in whole, to any other national or international journal.
The copyrights belong exclusively to the authors. Published content is licensed under Creative Commons Attribution 4.0 (CC BY 4.0) guidelines, which allows sharing (copy and distribution of the material in any medium or format) and adaptation (remix, transform, and build upon the material) for any purpose, even commercially, under the terms of attribution.
Read this link for further information on how to use CC BY 4.0 properly.
8.png){kind=logo}
