We used real plant data obtained from a water treatment plant in Peninsular Malaysia to develop a model to predict fluoride concentration in treated water.We validated the model with real plant data and demonstrated that the model yields good prediction, with mean absolute percentage error close to 10% or less. The validated model was then used to design an internal model control (IMC) tuned feedback controller, combined with a time-varying feedforward control approach by exploiting the predictable and repetitive pattern of the inlet water flow rate. Simulation studies using random and real disturbance data show that the proposed control has successfully prevented over fluoridation in treated water. The validated model, due to its simplicity, is suitable for future online implementation. It can also be readily applied to model-based control approaches (e.g., model predictive control) in future studies.
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