ONLINE IDENTIFICATION AND ADAPTIVE CONTROL OF BIOLOGICAL WASTEWATER TREATMENT PROCESS

TL;DRAbstract

The activated sludge process is a nonlinear, time-varying, multi-input-multi-output system. It is important to design an adaptive control strategy, which can not only track the setpoint changes quickly, but also adapt to the system uncertainties and disturbance signals. The current work presents a single-input-single-output Generalized Predictive Controller to regulate the dissolved oxygen concentration and a multi-loop Generalized Predictive Control scheme to control the dissolved oxygen concentration and the substrate concentration. The control is tested with both a simplified four-state model and an activated sludge model no. 1 (ASM1) benchmark of an activated sludge process. In the univariate algorithm, the manipulated variable (controller output) is the air flow rate (or the oxygen transfer coefficient) and the controlled variable (measured variable) is the dissolved oxygen concentration. On the other hand, for the multivariable process, two separate control loops are taken into c

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