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Related Experiment Videos

Endogenous model state and parameter estimation from an extensive batch experiment.

K J Keesman1, H Spanjers

  • 1Systems and Control Group, Wageningen University and Research Centre, Bomenweg 4, 6703 HD Wageningen, The Netherlands. karel.keesman@user.aenf.wau.nl

Biotechnology and Bioengineering
|April 4, 2000
PubMed
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This study analyzes aerobic biodegradation using batch experiments. Researchers modified a four-compartmental model based on mixed liquor volatile suspended solids and respiration rate data, improving accuracy with an Extended Kalman filter.

Area of Science:

  • Environmental microbiology
  • Biochemical engineering
  • Process modeling and control

Background:

  • Understanding endogenous respiration is crucial for optimizing aerobic biodegradation processes.
  • Accurate modeling of microbial dynamics, including substrate and biomass changes, is essential for effective wastewater treatment.
  • Existing models may require refinement to capture complex behaviors observed in real-world conditions.

Purpose of the Study:

  • To investigate endogenous process behavior in aerobic biodegradation through extensive batch experiments.
  • To analytically reconstruct states and unknown parameters of a four-compartmental model using experimental data.
  • To apply a recursive state estimation procedure, specifically an Extended Kalman filter, for noise handling and model refinement.

Main Methods:

Related Experiment Videos

  • Conducted extensive batch experiments measuring mixed liquor volatile suspended solids (MLVSS) and respiration rate.
  • Employed analytical reconstruction to determine states and parameters within a four-compartmental model.
  • Utilized an Extended Kalman filter-based observer for recursive state estimation and noise filtering.

Main Results:

  • Successfully reconstructed states and unknown parameters from experimental data.
  • The Extended Kalman filter effectively handled data noise properties during state estimation.
  • Identified the necessity to modify the initial model structure, particularly the hydrolysis term.

Conclusions:

  • The study highlights the importance of model structure validation against experimental data.
  • Refinement of the hydrolysis term is critical for accurately representing endogenous process behavior.
  • The applied methodology provides a robust approach for analyzing and improving biodegradation models.