Control of the Activated Sludge System Using Neural Network Model Predictive Control, M.Sc. Thesis Sharif University of Technology ; Shaygan Salek, Jalaloddin (Supervisor)
Abstract
Activated sludge systems are widespread biological wastewater treatment systems that have a very complex and nonlinear dynamics with a wide range of time constants and, as a consequence, are difficult to model and control. On the other hand, using neural networks as function approximators has provided a reliable tool for modeling complex dynamic systems like activated sludge. In this study a multi-input multi-output neural network model predictive controller (NNMPC) is developed and tested based on the basic control strategy of a benchmark simulation model (called BSM1) suggested by european co-operation in the field of science and technical research (COST) actions 682/624. The controller...
Cataloging briefControl of the Activated Sludge System Using Neural Network Model Predictive Control, M.Sc. Thesis Sharif University of Technology ; Shaygan Salek, Jalaloddin (Supervisor)
Abstract
Activated sludge systems are widespread biological wastewater treatment systems that have a very complex and nonlinear dynamics with a wide range of time constants and, as a consequence, are difficult to model and control. On the other hand, using neural networks as function approximators has provided a reliable tool for modeling complex dynamic systems like activated sludge. In this study a multi-input multi-output neural network model predictive controller (NNMPC) is developed and tested based on the basic control strategy of a benchmark simulation model (called BSM1) suggested by european co-operation in the field of science and technical research (COST) actions 682/624. The controller...
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