Adaptive neural network control for excitation of power systems

被引:0
|
作者
Li, Wenlei [1 ]
Liu, Shirong [1 ]
Jiang, Gangyi [1 ]
机构
[1] Ningbo Univ, Sch Informat Sci & Engn, Ningbo 315211, Peoples R China
关键词
D O I
暂无
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
For the nonlinear excitation system with unknown nonlinear uncertainties and external disturbances, a novel adaptive neural network control scheme based on the backstepping design method was presented in this paper. In order to deal with the influence of the uncertainties to the excitation system, the unknown nonlinear functions of the system are approximated by the RBF neural networks, and the unknown control gain is dealt with by using the Nussbaum gain function, in addition, the external disturbances are attenuated by the nonlinear damping terms within controller design procedure. The Semi-global uniformly ultimately boundedness of all the signals in the closed loop is guaranteed under the deduced controller, and the problems of control directions and control singularity are also solved. The further simulations executed in closed-loop systems demonstrate the effectiveness of proposed control scheme.
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收藏
页码:2027 / 2031
页数:5
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