Artificial neural networks to control chlorine dosing in a water treatment plant

Author(s)

Henriques Librantz, Andre Felipe ^[1] ; Rodrigues dos Santos, Fabio Cosme ^{[1, 2]} ; Dias, Cleber Gustavo ^[1]

Affiliation

^[1] Univ Nove Julho, Rua Vergueiro 235-249, BR-01504000 Sao Paulo, SP - Brazil

^[2] Companhia Saneamento Basico Estado Sao Paulo, Rua Nicolau Gagliardi 313, BR-05429010 Sao Paulo, SP - Brazil

• Document type: Journal article
• Source: ACTA SCIENTIARUM-TECHNOLOGY; v. 40, 2018.
• Web of Science Citations: 0

Abstract

Artificial neural networks in the multivariable control of chlorine dosing in the postchlorination stage in a water treatment plant in the Greater Sao 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 (R) 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. (AU)

• FAPESP's process: 16/02641-1 - Computational intelligence applied to optimization of water treatment process parameters
• Grantee: Andre Felipe Henriques Librantz
• Support Opportunities: Regular Research Grants