Please use this identifier to cite or link to this item: https://doi.org/10.1002/rnc.898
Title: Adaptive backstepping control for a class of nonlinear systems using neural network approximations
Authors: Tan, K.K. 
Huang, S.N. 
Lee, T.H. 
Issue Date: 10-May-2004
Source: Tan, K.K., Huang, S.N., Lee, T.H. (2004-05-10). Adaptive backstepping control for a class of nonlinear systems using neural network approximations. International Journal of Robust and Nonlinear Control 14 (7) : 643-664. ScholarBank@NUS Repository. https://doi.org/10.1002/rnc.898
Abstract: In this paper, an adaptive neural network (NN) backstepping technique is developed for tracking control of a class of nonlinear systems. NNs are used to compensate for the unknown nonlinear functions in the system. A systematic backstepping approach is established to synthesize the adaptive NN control scheme that ensures the boundedness of all the signals in the closed-loop system, and yields a small tracking error. The issue of transient performance is also addressed under an analytical framework. The effectiveness of the proposed scheme is demonstrated by computer simulations. Copyright © 2004 John Wiley & Sons, Ltd.
Source Title: International Journal of Robust and Nonlinear Control
URI: http://scholarbank.nus.edu.sg/handle/10635/54885
ISSN: 10498923
DOI: 10.1002/rnc.898
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