Stochastic Greybox Modeling for Control of an Alternating Activated Sludge Process

Rasmus Fogtmann Halvgaard, Luca Vezzaro, M. Grum, Thomas Munk-Nielsen, Peter Tychsen, Henrik Madsen

Research output: Book/ReportReportResearch

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Abstract

We present a stochastic greybox model of a BioDenitro WWTP that can be used for short time horizon Model Predictive Control. The model is based on a simplified ASM1 model and takes model uncertainty in to account. It estimates unmeasured state variables in the system, e.g. the inlet concentration or the sensor measurements in case of temporary sensor faults. This improves control performance without adding additional or redundant sensors. We fitted the parameters of the model to actual plant data and demonstrate the state estimation capabilities with this data set. The model now runs online at a WWTP in Denmark
Original languageEnglish
PublisherDTU Compute
Number of pages9
Publication statusPublished - 2017
SeriesDTU Compute-Technical Report-2017
Volume08
ISSN1601-2321

Keywords

  • WWTP
  • ASM1
  • Stochastic
  • Greybox
  • Alternating
  • BioDenitro

Cite this

Halvgaard, R. F., Vezzaro, L., Grum, M., Munk-Nielsen, T., Tychsen, P., & Madsen, H. (2017). Stochastic Greybox Modeling for Control of an Alternating Activated Sludge Process. DTU Compute. DTU Compute-Technical Report-2017, Vol.. 08
Halvgaard, Rasmus Fogtmann ; Vezzaro, Luca ; Grum, M. ; Munk-Nielsen, Thomas ; Tychsen, Peter ; Madsen, Henrik. / Stochastic Greybox Modeling for Control of an Alternating Activated Sludge Process. DTU Compute, 2017. 9 p. (DTU Compute-Technical Report-2017, Vol. 08).
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Halvgaard, RF, Vezzaro, L, Grum, M, Munk-Nielsen, T, Tychsen, P & Madsen, H 2017, Stochastic Greybox Modeling for Control of an Alternating Activated Sludge Process. DTU Compute-Technical Report-2017, vol. 08, DTU Compute.

Stochastic Greybox Modeling for Control of an Alternating Activated Sludge Process. / Halvgaard, Rasmus Fogtmann; Vezzaro, Luca; Grum, M.; Munk-Nielsen, Thomas; Tychsen, Peter; Madsen, Henrik.

DTU Compute, 2017. 9 p. (DTU Compute-Technical Report-2017, Vol. 08).

Research output: Book/ReportReportResearch

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T1 - Stochastic Greybox Modeling for Control of an Alternating Activated Sludge Process

AU - Halvgaard, Rasmus Fogtmann

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AU - Grum, M.

AU - Munk-Nielsen, Thomas

AU - Tychsen, Peter

AU - Madsen, Henrik

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N2 - We present a stochastic greybox model of a BioDenitro WWTP that can be used for short time horizon Model Predictive Control. The model is based on a simplified ASM1 model and takes model uncertainty in to account. It estimates unmeasured state variables in the system, e.g. the inlet concentration or the sensor measurements in case of temporary sensor faults. This improves control performance without adding additional or redundant sensors. We fitted the parameters of the model to actual plant data and demonstrate the state estimation capabilities with this data set. The model now runs online at a WWTP in Denmark

AB - We present a stochastic greybox model of a BioDenitro WWTP that can be used for short time horizon Model Predictive Control. The model is based on a simplified ASM1 model and takes model uncertainty in to account. It estimates unmeasured state variables in the system, e.g. the inlet concentration or the sensor measurements in case of temporary sensor faults. This improves control performance without adding additional or redundant sensors. We fitted the parameters of the model to actual plant data and demonstrate the state estimation capabilities with this data set. The model now runs online at a WWTP in Denmark

KW - WWTP

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Halvgaard RF, Vezzaro L, Grum M, Munk-Nielsen T, Tychsen P, Madsen H. Stochastic Greybox Modeling for Control of an Alternating Activated Sludge Process. DTU Compute, 2017. 9 p. (DTU Compute-Technical Report-2017, Vol. 08).