Decentralized indirect adaptive I-term fuzzy-neural control of a distributed parameter bioprocess plant

The paper proposed to use an I-term hierarchical fuzzy-neural sliding mode controller to control distributed parameter wastewater anaerobic digestion bioprocess plant. The bioprocess plant is described by partial differential equations simplified by means of the orthogonal collocation method and used as an input/output data generator. The obtained process data are identified by means of a decentralized fuzzy-neural identifier and the issued local parameter and state information is used to build up a local sliding mode control with I-term for each collocation point. The comparative graphical and numerical simulation results of the digestion wastewater treatment system identification and control, obtained via learning, exhibited a good convergence, and precise reference tracking.