Predictive–feedback control of short-HRT enhanced coagulation: toward automated and operator-independent water treatment

Map of the United States shows multiple utilities potentially interested in the presented technology. Pilot project revealed that combining predictive and feedback control reduced clarified-water turbidity variability and provided more robust process control than either strategy alone. Automation of coagulant dosing offers a potential solution to a growing shortage of skilled water treatment plant operators, reducing operator workload while improving process stability. This study tested four process control strategies in a pilot-scale enhanced coagulation system, each evaluated against a clarified water turbidity target of 1.0 NTU: (1) manual flow-proportional dosing, (2) feedback control based on clarified water turbidity, (3) predictive control using a geometric coagulation model with raw water turbidity and UV254 inputs, and (4) a hybrid predictive–feedback controller. Manual dosing offered the least accuracy, produced clarified water turbidities ranging from 1.10 to 4.53 NTU (median 2.57 NTU), with poor stability (SD = 1.02 NTU). Feedback control improved accuracy (median 1.09 NTU) but lagged during rapid turbidity spikes. Predictive control provided immediate response to raw water quality changes, but with reduced precision (median 1.27 NTU). The hybrid controller achieved the best performance, combining accuracy and real-time responsiveness with high stability (median 1.09 NTU; SD = 0.25 NTU). These results demonstrate that a hybrid predictive–feedback control can enhance resilience, reduce operator reliance, and maintain regulatory compliance, offering a viable pathway for automating coagulation in small- and medium-scale water treatment facilities.