Reduced Order Models for On-Line Parameter Identification of the Activated Sludge Process

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Reduced Order Models for On-Line Parameter Identification of the Activated Sludge Process. / Jeppsson, Ulf; Olsson, Gustaf.

In: Water Science and Technology, Vol. 28, No. 11-12, 1993, p. 173-183.

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TY - JOUR

T1 - Reduced Order Models for On-Line Parameter Identification of the Activated Sludge Process

AU - Jeppsson, Ulf

AU - Olsson, Gustaf

PY - 1993

Y1 - 1993

N2 - A reduced order dynamic model for an activated sludge process performing carbonaceous removal, nitrification, and denitrification is proposed. Based on directly measurable real time data - by methods available today - all model parameters are identified on-line. A simplified extended Kalman filter is used for the actual identification. Verification of the results is based on computer simulations of the IAWQ Activated Sludge Model No. 1. The reduced order model presented herein may serve as a tool for predicting the dynamic behaviour of a biological wastewater treatment plant since the parameters under varying operating conditions can be tracked on-line. The model parameters are effectively estimated even when the measurements are affected by a significant level of noise. The model is aimed for operation and control purposes as an integral part of a hierarchical control structure.

AB - A reduced order dynamic model for an activated sludge process performing carbonaceous removal, nitrification, and denitrification is proposed. Based on directly measurable real time data - by methods available today - all model parameters are identified on-line. A simplified extended Kalman filter is used for the actual identification. Verification of the results is based on computer simulations of the IAWQ Activated Sludge Model No. 1. The reduced order model presented herein may serve as a tool for predicting the dynamic behaviour of a biological wastewater treatment plant since the parameters under varying operating conditions can be tracked on-line. The model parameters are effectively estimated even when the measurements are affected by a significant level of noise. The model is aimed for operation and control purposes as an integral part of a hierarchical control structure.

KW - extended Kalman filtering.

KW - model calibration

KW - model reduction

KW - parameter estimation

KW - simulation

KW - Activated sludge

KW - dynamic modelling

M3 - Article

VL - 28

SP - 173

EP - 183

JO - Water Science and Technology

JF - Water Science and Technology

SN - 0273-1223

IS - 11-12

ER -