Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/69208
Title: Adaptive NN control of partially known nonlinear strict-feedback systems
Authors: Ge, S.S. 
Wang, C.
Issue Date: 2001
Source: Ge, S.S.,Wang, C. (2001). Adaptive NN control of partially known nonlinear strict-feedback systems. Proceedings of the American Control Conference 2 : 1241-1246. ScholarBank@NUS Repository.
Abstract: This paper presents a direct adaptive NN control scheme for partially known strict-feedback systems. In this scheme, a priori information of the system under study can be incorporated into controller design. The benefits of using the a priori information includes: (i) much simplified algorithm, and (ii) much less neurons employed for approximation, which makes the algorithm computationally feasible. With the help of NN approximation, the overparametrization problem in adaptive backstepping design is avoided without using tuning functions. Semi-global uniform ultimate boundedness of all the signals in the closed-loop is guaranteed and the output of the system is proven to converge to a small neighborhood of the desired trajectory. The control performance of the closed-loop system is guaranteed by suitably choosing the design parameters. Simulation studies are conducted to show the effectiveness of the scheme.
Source Title: Proceedings of the American Control Conference
URI: http://scholarbank.nus.edu.sg/handle/10635/69208
ISSN: 07431619
Appears in Collections:Staff Publications

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