Adaptive neural network control of uncertain minimum-phase nonlinear systems

被引:0
|
作者
Wang, Weihua [1 ]
Chen, Dingfang
机构
[1] Wuhan Univ Technol, Coll Logist Engn, Wuhan 430070, Peoples R China
[2] Hubei Univ, Fac Math & Comp Sci, Wuhan 430062, Peoples R China
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D O I
暂无
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
The paper considers the problem of practical disturbance attenuation for a class of minimum-phase uncertain nonlinear systems. The system under consideration is cascaded by a zero-input asymptotically stable nonlinear sub-system and a triangle cascade one with some uncertainties and disturbance. For the purpose of reducing the reservation which appears in robust control method, by using the backstepping technique, we construct a neural network control method. Under the controller, the resultant closed loop system is input to state practically stable and the response of the output to the disturbance is practically attenuated. The simulation example shows that the controller has a small control gain and the resultant closed-loop system has good performance.
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页码:251 / 255
页数:5
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