Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/62718
Title: Robust adaptive NN feedback linearization control of nonlinear systems
Authors: Ge, S.S. 
Issue Date: Dec-1996
Citation: Ge, S.S. (1996-12). Robust adaptive NN feedback linearization control of nonlinear systems. International Journal of Systems Science 27 (12) : 1327-1338. ScholarBank@NUS Repository.
Abstract: In this paper, a robust adaptive neural network feedback linearization control law is presented for a class of nonlinear dynamic systems. First, the 'GL' matrices and the corresponding operator are introduced, which brings a new methodology into the analysis of neural networks. Secondly, the basic ideas of Feedback Linearization Control (FLC) of nonlinear systems are discussed. Finally, a robust adaptive neural network FLC of nonlinear systems is presented. It is shown that uniformly stable adaptation is assured and asymptotic tracking is achieved if Bounded Basis Functions (BBF) are used, and output tracking errors also converge to zero.
Source Title: International Journal of Systems Science
URI: http://scholarbank.nus.edu.sg/handle/10635/62718
ISSN: 00207721
Appears in Collections:Staff Publications

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