Hybrid modelling of anaerobic wastewater treatment processes

• Published in: Water science and technology 2001, Vol.43 (1), p.43-50
• Main Authors: KARAMA, A, BERNARD, O, GENOVESI, A, DOCHAIN, D, BENHAMMOU, A, STEYER, J-P
• Format: Article
• Language: English
• Subjects: Anaerobic digestion; Anaerobic processes; Anaerobic treatment; Applied sciences; Bacteria; Bacteria, Anaerobic - metabolism; Biological and medical sciences; Biological treatment of waters; Biotechnology; Differential equations; Earth Sciences; Environment and pollution; Exact sciences and technology; Fundamental and applied biological sciences. Psychology; General purification processes; Growth rate; Hydrology; Industrial applications and implications. Economical aspects; Kinetics; Knowledge bases (artificial intelligence); Mathematical models; Modelling; Models, Theoretical; Neural networks; Neural Networks (Computer); Pollution; Process parameters; Sciences of the Universe; Static models; Training; Waste Disposal, Fluid; Wastewater; Wastewater treatment; Wastewaters; Water treatment and pollution
• ISSN: 0273-1223; 1996-9732
• DOI: 10.2166/wst.2001.0011

This paper presents a hybrid approach for the modelling of an anaerobic digestion process. The hybrid model combines a feed-forward 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.