Autors: Yordanova, S. T., Petrova R., Noykova N., Tzvetkov, P. M.
Title: Neuro-fuzzy modelling in anaerobic wastewater treatment for prediction and control
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

    Issue

    International Journal of Computing, vol. 5, issue 1, pp. 51-56, 2006, Ukraine,

    Цитирания (Citation/s):
    1. Anfal Majid Salal, Dr.Basim Hussein Khudair, Influent Flow Rate Effect On Sewage Pump Station Performance Based On Organic And Sediment Loading, Journal of Engineering 25(9), pp. 1-11 - 2019 - от чужди автори в чужди издания, неиндексирани в Scopus или Web of Science
    2. Islam, S.I., Shi, P. & Lim, CC. Robust functional observer for stabilising uncertain fuzzy systems with time-delay. Granul. Comput. 5, pp.55–69 , https://doi.org/10.1007/s41066-018-0138-x - 2020 - в издания, индексирани в Scopus или Web of Science

    Вид: статия в списание, публикация в реферирано издание