TY - JOUR
T1 - Hierarchical fuzzy CMAC control for nonlinear systems
AU - Rodríguez, Floriberto Ortiz
AU - de Jesús Rubio, José
AU - Gaspar, Carlos R.Mariaca
AU - Tovar, Julio César
AU - Armendáriz, Marco A.Moreno
PY - 2013
Y1 - 2013
N2 - In this study, a novel indirect adaptive controller is introduced for a class of unknown nonlinear systems. The proposed method provides a simple control architecture that merges from the cerebellar model articulation controller (CMAC) network and hierarchical fuzzy logic; therefore, the complicated CMAC structure can be simplified. The overall adaptive scheme guarantees the uniform stability of the closed-loop system. A simulation is presented to demonstrate the performance of the proposed methodology.
AB - In this study, a novel indirect adaptive controller is introduced for a class of unknown nonlinear systems. The proposed method provides a simple control architecture that merges from the cerebellar model articulation controller (CMAC) network and hierarchical fuzzy logic; therefore, the complicated CMAC structure can be simplified. The overall adaptive scheme guarantees the uniform stability of the closed-loop system. A simulation is presented to demonstrate the performance of the proposed methodology.
KW - Adaptive control
KW - Fuzzy systems
KW - Neural networks
KW - Nonlinear system
UR - http://www.scopus.com/inward/record.url?scp=84888848726&partnerID=8YFLogxK
U2 - 10.1007/s00521-013-1423-x
DO - 10.1007/s00521-013-1423-x
M3 - Artículo
SN - 0941-0643
VL - 23
SP - 323
EP - 331
JO - Neural Computing and Applications
JF - Neural Computing and Applications
IS - SUPPL1
ER -