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Journal of Applied Sciences
  Year: 2009 | Volume: 9 | Issue: 2 | Page No.: 248-257
DOI: 10.3923/jas.2009.248.257
Gaussian Radial Basis Adaptive Backstepping Control for a Class of Nonlinear Systems
F. Farivar, M. Aliyari Shoorehdeli, M.A. Nekoui and M. Teshnehlab

Abstract:
This study proposes a Gaussian Radial Basis Adaptive Backstepping Control (GRBABC) system for a class of n-order nonlinear systems. In the neural backstepping controller, a Gaussian radial basis function is utilized to on-line estimate of the system dynamic function. The adaptation laws of the control system are derived in the sense of Lyapunov function, thus the system can be guaranteed to be asymptotically stable. The proposed GRBABC is applied to two nonlinear chaotic systems which have the different order to illustrate its effectiveness. Simulation results verify that the proposed GRBABC can achieve favorable tracking performance by incorporating of GRBFNN identification, adaptive backstepping control techniques.
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How to cite this article:

F. Farivar, M. Aliyari Shoorehdeli, M.A. Nekoui and M. Teshnehlab, 2009. Gaussian Radial Basis Adaptive Backstepping Control for a Class of Nonlinear Systems. Journal of Applied Sciences, 9: 248-257.

DOI: 10.3923/jas.2009.248.257

URL: https://scialert.net/abstract/?doi=jas.2009.248.257

 
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