A case study on the IMC for ozone dosing process of drinking water treatment

Abstract

Ozonation is one of the most important processes during drinking water treatment. To improve the efficiency of ozonation and to stabilize the quality of the treated water, the ozone dosage should be a good trade-off between the requirement of disinfection and the restriction of bromate formation. However, because of the changes of raw water quality and the nonlinear behavior of ozonation process, the ozone dosing process is very difficult to be controlled. In this paper, the control strategy of keeping a constant ozone exposure is attempted instead of conventional keeping a constant ozone dosage or dissolved ozone residual. To this end, internal model control (IMC) scheme based on the radial basis function (RBF) neural network model is proposed to maintain a constant ozone exposure by adjusting ozone dosage. With the proposed control scheme, a RBF neural network model is established which could be used for IMC. And then an IMC controller is designed. The full-scale experimental studies demonstrate the efficiency and effectiveness of proposed control scheme.