TY - CHAP
T1 - Decentralized adaptive soft computing control of distributed parameter bioprocess plant
AU - Baruch, Ieroham S.
AU - Galvan-Guerra, Rosalba
PY - 2010
Y1 - 2010
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 hierarchical fuzzy-neural direct and indirect multi-model controllers. 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 very closed to that of 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 hierarchical fuzzy-neural direct and indirect multi-model controllers. 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 very closed to that of the optimal control.
UR - http://www.scopus.com/inward/record.url?scp=77957743194&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-13428-9_9
DO - 10.1007/978-3-642-13428-9_9
M3 - Capítulo
AN - SCOPUS:77957743194
SN - 9783642134272
T3 - Studies in Computational Intelligence
SP - 201
EP - 228
BT - Intelligent Systems
A2 - Hadjiski, Mincho
A2 - Sgurev, Vassil
A2 - Kacprzyk, Janusz
ER -