Title :
Structure identification and adaptive control of neuro-fuzzy systems by a non-parametric regression technique
Author :
Cruz-Vega, Israel ; Moreno-Ahedo, L.O.
Author_Institution :
TESCo, Unidad de Estudios de Posgrado e Investig., Coacalco de Berriozábal, Mexico
Abstract :
The usefulness of control systems by neuro-fuzzy networks has been proved as an effective tool for non-linear systems. Determine the structure of a fuzzy system is not an easy task. In this paper, the initial structure of an adaptive neuro-fuzzy control system is determined by a non-parametric regression technique. This structure is used in conjunction with neural networks to deal with plant changes. The simulation results show the efficiency of this process.
Keywords :
adaptive control; fuzzy control; neurocontrollers; nonlinear control systems; regression analysis; adaptive neuro-fuzzy control system; neural networks; nonlinear systems; nonparametric regression technique; structure identification; Approximation methods; Equations; Fuzzy systems; Hydrocarbons; Kernel; Mathematical model; Smoothing methods;
Conference_Titel :
Electronics, Communications and Computing (CONIELECOMP), 2013 International Conference on
Conference_Location :
Cholula
Print_ISBN :
978-1-4673-6156-9
DOI :
10.1109/CONIELECOMP.2013.6525783
