Recursive regression and Wiener deconvolution for coagulation optimization in water treatment plant

A coagulation optimization strategy was developed which utilizes the Wiener deconvolution filter to estimate steady-steady values, and then updates the optimization model using recursive kernel regression. The regression-based dose controller is capable of maintaining a target turbidity level with changing raw water conditions. Various pilot test experiments were performed to validate the effectiveness of the proposed strategy.