Decentralized and Centralized Indirect Adaptive I-term Neural Control of a Distributed Parameter Bioprocess Plant
نویسندگان
چکیده
The paper proposed to use decentralized and centralized I-term neural sliding mode control of 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 decentralized and centralized neural identifiers and the issued parameter and state information is used to build up decentralized and centralized sliding mode control with I-term for each collocation point output variables. For sake of comparison some control results are given for centralized optimal control of DPS. 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.
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