TY - GEN
T1 - Decentralized indirect adaptive fuzzy-neural multi-model control of a distributed parameter bioprocess plant
AU - Baruch, Ieroham S.
AU - Galvan-Guerra, Rosalba
AU - Mariaca-Gaspar, Carlos Roman
AU - Melin, Patricia
PY - 2008
Y1 - 2008
N2 - The paper proposed to use recurrent Fuzzy-Neural Multi-Model (FNMM) identifier 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 plant output variables with respect to the space variable. The local and global weight parameters and states of the proposed FNMM identifier are implemented by a Hierarchical Fuzzy-Neural Multi-Model Sliding Mode Controller (HFNMM-SMC). 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.
AB - The paper proposed to use recurrent Fuzzy-Neural Multi-Model (FNMM) identifier 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 plant output variables with respect to the space variable. The local and global weight parameters and states of the proposed FNMM identifier are implemented by a Hierarchical Fuzzy-Neural Multi-Model Sliding Mode Controller (HFNMM-SMC). 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.
UR - http://www.scopus.com/inward/record.url?scp=56349133742&partnerID=8YFLogxK
U2 - 10.1109/IJCNN.2008.4634020
DO - 10.1109/IJCNN.2008.4634020
M3 - Contribución a la conferencia
AN - SCOPUS:56349133742
SN - 9781424418213
T3 - Proceedings of the International Joint Conference on Neural Networks
SP - 1657
EP - 1664
BT - 2008 International Joint Conference on Neural Networks, IJCNN 2008
T2 - 2008 International Joint Conference on Neural Networks, IJCNN 2008
Y2 - 1 June 2008 through 8 June 2008
ER -