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Parameter identification of a reduced order LFT model of anaerobic digestion

Parameter identification of a reduced order LFT model of anaerobic digestion

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Owing to their complexity, accurate and detailed models of anaerobic digestion cannot be used for online monitoring and control. To this aim reduced order models have to be considered. In this chapter, a modification of the well-known AMOCO model is first proposed in order to widen its field of applicability. Then, to perform parameter identification, a linear fractional transformation (LFT) formulation is derived, thanks to the use of a symbolic manipulation tool applied to an object-oriented model formulation. The approach has been applied to two case tests: in the first test, the data used for identification have been generated by a simulation of the fully detailed Anaerobic Digestion Model no. 1 (ADM1) model, assuming waste activated sludge as influent substrate, and in the second, the data have been collected on a real plant, used for anaerobic digestion of agricultural wastes.

Chapter Contents:

  • Abstract
  • 14.1 Introduction
  • 14.2 ADM1 model
  • 14.3 Modified AMOCO model
  • 14.4 LFT modelling and identification
  • 14.5 Parameter identification based on ADM1 model simulation data
  • 14.6 Parameter identification based on experimental data
  • 14.7 Conclusion
  • Acknowledgements
  • Appendix A. LFT model for parameter identification based on ADM1 model simulation data
  • Appendix B. LFT model for parameter identification based on experimental data
  • References

Inspec keywords: wastewater treatment; linear algebra; sludge treatment; parameter estimation; reduced order systems

Other keywords: waste activated sludge; object-oriented model formulation; reduced order LFT model; linear fractional transformation; agricultural wastes; AMOCO model; anaerobic digestion model; wastewater treatment; symbolic manipulation tool; parameter identification; ADM1

Subjects: Systems theory applications; Algebra; Environmental issues; Systems theory applications in natural resources and ecology; Algebra; Simulation, modelling and identification

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