NEURO-FUZZY MODELLING IN ANAEROBIC WASTEWATER TREATMENT FOR PREDICTION AND CONTROL

Authors

  • Snejana Yordanova
  • Rusanka Petrova
  • Nelly Noykova
  • Plamen Tzvetkov

DOI:

https://doi.org/10.47839/ijc.5.1.381

Keywords:

Anaerobic digestion of organic waste, neuro-fuzzy modelling, sensitivity, simulation, predictive control

Abstract

The aim of the present paper is to develop neuro-fuzzy prediction models in MATLAB environment of the anaerobic organic digestion process in wastewater treatment from laboratory and simulated experiments accounting for the variable organic load, ambient influence and microorganisms state. The main contributions are determination of significant model parameters via graphical sensitivity analysis, simulation experimentation, design and study of two “black-box” models for the biogas production rate, based on classical feedforward backpropagation and Sugeno fuzzy logic neural networks respectively. The models application is demonstrated in process predictive control

References

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Published

2014-08-01

How to Cite

Yordanova, S., Petrova, R., Noykova, N., & Tzvetkov, P. (2014). NEURO-FUZZY MODELLING IN ANAEROBIC WASTEWATER TREATMENT FOR PREDICTION AND CONTROL. International Journal of Computing, 5(1), 51-56. https://doi.org/10.47839/ijc.5.1.381

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