Case study on the advanced control for ozone dosing process of drinking water treatment

Ozonation is one of the most important steps in drinking water treatment plants. The efficiency of ozonation is directly related to the treated water quality. However, ozone dosing process is very difficult to be controlled because of its complicated nonlinear behaviour. In this paper, an advanced control scheme based on model predictive control (MPC) is proposed for the ozone dosing process. With the proposed control scheme, a RBF neural network model is established which could be used for MPC. The control strategy of maintaining a constant ozone exposure is adopted for effective disinfection requirements. The full-scale experimental results demonstrate the effectiveness of this advanced control method.