Abstract
The Activated Sludge Model no.1 (ASM1) is selected to describe the biological processes in the reactor. On-line measurements are corrupted by additive white noise and unknown inputs are modelled using fast Fourier transform (FFT) and spectrum analyses. The given procedure aims at reducing the original ASM1 model to an observable and identifiable model, which can be used for joint non-linear state and parameter estimations. Simulation results are presented to demonstrate the effectiveness of the proposed methods and show that on-line
monitoring of SND and XND concentrations is achieved when dynamic input data are used tocharacterize the influent wastewater for the model.
| Language | English |
|---|---|
| Number of pages | 8 |
| Publication status | Published - 2005 |
| Event | 10th International Conference on Urban Drainage - Copenhagen, Denmark Duration: 21 Aug 2005 → 26 Aug 2005 |
Conference
| Conference | 10th International Conference on Urban Drainage |
|---|---|
| Country | Denmark |
| City | Copenhagen |
| Period | 21/08/05 → 26/08/05 |
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Keywords
- activated sludge
- extended kalman filter
- observability
- software sensor
- wastewater treatment
Cite this
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On an application of extended kalman filtering to activated sludge processes: a benchmark study. / Benazzi, F.; Jeppsson, U.; Katebi, M.R.
2005. Paper presented at 10th International Conference on Urban Drainage, Copenhagen, Denmark.Research output: Contribution to conference › Paper
TY - CONF
T1 - On an application of extended kalman filtering to activated sludge processes: a benchmark study
AU - Benazzi, F.
AU - Jeppsson, U.
AU - Katebi, M.R.
PY - 2005
Y1 - 2005
N2 - The growing demand for performance improvements of urban wastewater system operation coupled with the lack of instrumentation in most wastewater treatment plants motivates the need for non-linear observers to be used as virtual sensors for estimation and control of effluent quality. This paper is focused on the development of a general procedure for on-line monitoring of activated sludge processes, using an extended Kalman filter (EKF) approach. The Activated Sludge Model no.1 (ASM1) is selected to describe the biological processes in the reactor. On-line measurements are corrupted by additive white noise and unknown inputs are modelled using fast Fourier transform (FFT) and spectrum analyses. The given procedure aims at reducing the original ASM1 model to an observable and identifiable model, which can be used for joint non-linear state and parameter estimations. Simulation results are presented to demonstrate the effectiveness of the proposed methods and show that on-line monitoring of SND and XND concentrations is achieved when dynamic input data are used tocharacterize the influent wastewater for the model.
AB - The growing demand for performance improvements of urban wastewater system operation coupled with the lack of instrumentation in most wastewater treatment plants motivates the need for non-linear observers to be used as virtual sensors for estimation and control of effluent quality. This paper is focused on the development of a general procedure for on-line monitoring of activated sludge processes, using an extended Kalman filter (EKF) approach. The Activated Sludge Model no.1 (ASM1) is selected to describe the biological processes in the reactor. On-line measurements are corrupted by additive white noise and unknown inputs are modelled using fast Fourier transform (FFT) and spectrum analyses. The given procedure aims at reducing the original ASM1 model to an observable and identifiable model, which can be used for joint non-linear state and parameter estimations. Simulation results are presented to demonstrate the effectiveness of the proposed methods and show that on-line monitoring of SND and XND concentrations is achieved when dynamic input data are used tocharacterize the influent wastewater for the model.
KW - activated sludge
KW - extended kalman filter
KW - observability
KW - software sensor
KW - wastewater treatment
M3 - Paper
ER -