Artificial neural networks to control chlorine dosing in a 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.