Fuzzy-Neural control of a distributed parameter bioprocess plant

In the paper it is proposed a new recurrent fuzzy-neural multi-model (FNMM) identifier applied for decentralized identification of a distributed parameter anaerobic wastewater treatment digestion bioprocess, carried out in a fixed bed and a recirculation tank. The distributed parameter analytical model of the digestion bioprocess is reduced to a lumped system using the orthogonal collocation method, applied in three collocation points (plus the recirculation tank), which are used as centers of the membership functions of the fuzzyfied space variable of the plant. The states of the proposed FNMM identifier are implemented by a direct feedback-feedforward hierarchical fuzzy-neural controller. The comparative graphical simulation results of the digestion wastewater treatment system identification and control, obtained via learning, exhibited a good convergence, and precise reference tracking outperforming the optimal control.