Generación y Optimización de Controladores Difusos Utilizando el Modelo NEFCON

Resumen es: El diseno de algoritmos que operen sobre plantas con dinamicas no modeladas aun representa un reto en el area de control automatico. Una solucion podria ...

[1]  Rudolf Kruse,et al.  A neural fuzzy controller learning by fuzzy error propagation , 1992 .

[2]  Xia Hong,et al.  Adaptive Modelling, Estimation and Fusion from Data: A Neurofuzzy Approach , 2002, Advanced information processing.

[3]  François Chapeau-Blondeau,et al.  Constructive Action of Additive Noise in Optimal Detection , 2005, Int. J. Bifurc. Chaos.

[4]  S. Hyakin,et al.  Neural Networks: A Comprehensive Foundation , 1994 .

[5]  Detlef Nauck,et al.  Foundations Of Neuro-Fuzzy Systems , 1997 .

[6]  Rudolf Kruse,et al.  Neuronale Netze und Fuzzy-Systeme , 1994 .

[7]  Hung-Yuan Chung,et al.  Decoupled fuzzy controller design with single-input fuzzy logic , 2002, Fuzzy Sets Syst..

[8]  Jin S. Lee,et al.  Universal approximation by hierarchical fuzzy system with constraints on the fuzzy rule , 2002, Fuzzy Sets Syst..

[9]  Lon-Chen Hung,et al.  Decoupled control using neural network-based sliding-mode controller for nonlinear systems , 2007, Expert Syst. Appl..

[10]  Marcos Angel Gonzalez-Olvera,et al.  A New Recurrent Neurofuzzy Network for Identification of Dynamic Systems , 2006, ISNN.

[11]  Seok-Beom Roh,et al.  IG-based genetically optimized fuzzy polynomial neural networks with fuzzy set-based polynomial neurons , 2007, Neurocomputing.

[12]  Jyh-Shing Roger Jang,et al.  ANFIS: adaptive-network-based fuzzy inference system , 1993, IEEE Trans. Syst. Man Cybern..

[13]  Richard S. Sutton,et al.  Reinforcement Learning: An Introduction , 1998, IEEE Trans. Neural Networks.

[14]  Richard M. Crowder,et al.  Adaptive neurofuzzy control of a robotic gripper with on-line machine learning , 2004, Robotics Auton. Syst..