This paper presents a hybrid approach for the modelling of an anaerobic digestion process. The hybrid model combines a feedforward network, describing the bacterial kinetics, and the a priori knowledge based on the mass balances of the process components. We have considered an architecture which incorporates the neural network as a static model of unmeasured process parameters (kinetic growth rate) and an integrator for the dynamic representation of the process using a set of dynamic differential equations. The paper contains a description of the neural network component training procedure. The performance of this approach is illustrated with experimental data.
Hybrid modelling of anaerobic wastewater treatment processes
A. Kamara, O. Bernard, A. Genovesi, D. Dochain, A. Benhammou, J.-P. Steyer; Hybrid modelling of anaerobic wastewater treatment processes. Water Sci Technol 1 January 2001; 43 (1): 43–50. doi: https://doi.org/10.2166/wst.2001.0011
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