Artificial Neural Networks Based Model Predictive Control of the Wastewater Treatment Plant
نویسنده
چکیده
A statistical model, using Artificial Neural Networks (ANN), has been developed for the aerobic suspended growth Wastewater Treatment (WWT) plant. The paper presents the way ANN model has been designed and trained. The emerged recurrent ANN model has been used to perform WWT control using Model Predictive Control (MPC) algorithm. Model Predictive Control of the WWT soluble substrate and dissolved oxygen concentration has been investigated in the presence of setpoint changes and disturbance action. Cases of feedback provided by direct measurement of the soluble substrate concentration but also by using a special trained ANN soluble substrate estimator based on dissolved oxygen concentration measurement are shown. Incentives of the ANN model and ANN estimator based MPC are presented.
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