Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/61764
Title: Adaptive neural network feedback control of a passive line-of-sight stabilization system
Authors: Lee, T.H. 
Ge, S.S. 
Wong, C.P.
Issue Date: 1-Dec-1998
Source: Lee, T.H.,Ge, S.S.,Wong, C.P. (1998-12-01). Adaptive neural network feedback control of a passive line-of-sight stabilization system. Mechatronics 8 (8) : 887-903. ScholarBank@NUS Repository.
Abstract: An adaptive neural network full-state feedback controller has been designed and applied to the passive line-of-sight (LOS) stabilization system. Model reference adaptive control (MRAC) is well established for linear systems. However, this method cannot be utilized directly since the LOS system is nonlinear in nature. Utilizing the universal approximation property of neural networks, an adaptive neural network controller is presented by generalizing the model reference adaptive control technique, in which the gains of the controller are approximated by neural networks. This removes the requirement of linearizing the dynamics of the system, and the stability properties of the closed-loop system can be guaranteed. © 1998 Elsevier Science Ltd. All rights reserved.
Source Title: Mechatronics
URI: http://scholarbank.nus.edu.sg/handle/10635/61764
ISSN: 09574158
Appears in Collections:Staff Publications

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