Akyurek, EvrimYuceer, MehmetAtasoy, IlknurBerber, Ridvan2024-08-042024-08-042009978-0-444-53433-01570-7946https://hdl.handle.net/11616/9482619th European Symposium on Computer Aided Process Engineering -- JUN 14-17, 2009 -- Cracow, POLANDSix control strategies; PID control, Model Predictive Control (MPC) with linear model, MPC with non-linear model, Nonlinear Autoregressive-Moving Average (NARMA-L2) control, Neural Network Model Predictive Control (NN-MPC) and optimal control with sequential quadratic programming (SQP) algorithm were evaluated via simulation of activated sludge wastewater treatment process. Controller performance assessment was based on rise time, overshoot, Integral Absolute Error (IAE) and Integral Square Error (ISE) performance criteria. As dissolved oxygen level in the aeration tank plays an important role in obtaining the effluent water quality, and in operating cost, it was chosen as the controlled variable. It was concluded consequently that NARMA-L2 controller and optimal control with SQP would outperform the others in achieving the specified objective.eninfo:eu-repo/semantics/closedAccessActivated sludge processMPCNeural Network MPCNARMA-L2Optimal controlConference Object26119712012-s2.0-67649118227Q4WOS:000287727900194N/A