Paper Title:
Neural Network Adaptive Control for a Class of SISO Nonlinear Systems
  Abstract

An adaptive neural network control scheme is presented for a class of SISO affine nonlinear systems. Parameters in neural networks are updated using a gradient descent method. No robustifying control term is used in controller. The convergence of adaptive parameters and tracking error and the boundedness of all states in the corresponding closed-loop system are demonstrated by Lyapunov stability theorem. Simulation results demonstrate the effectiveness of the approach.

  Info
Periodical
Advanced Materials Research (Volumes 211-212)
Edited by
Ran Chen
Pages
953-957
DOI
10.4028/www.scientific.net/AMR.211-212.953
Citation
H. Hu, P. Guo, C. Liu, "Neural Network Adaptive Control for a Class of SISO Nonlinear Systems", Advanced Materials Research, Vols. 211-212, pp. 953-957, 2011
Online since
February 2011
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$32.00
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