Neural Network Adaptive Control for a Class of SISO Nonlinear Systems

Abstract:

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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 et al., "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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Price:

$35.00

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