Adaptive fuzzy synchronization for a class of fractional-order neural networks

被引：0
|
作者：
刘恒 [1 ,2 ]
李生刚 [1 ]
王宏兴 [2 ]
李冠军 [2 ]
机构：
[1] College of Mathematics and Information Science,Shaanxi Normal Universtiy
[2] Department of Applied Mathematics, Huainan Normal University
来源：
Chinese Physics B | 2017年 / 03期
基金：
中国国家自然科学基金; 中央高校基本科研业务费专项资金资助;
关键词：
fractional-order neural network; adaptive fuzzy control; fractional-order adaptation law;
D O I：
暂无
中图分类号：
TP183 [人工神经网络与计算]; TP13 [自动控制理论];
学科分类号：
0711 ; 071102 ; 0811 ; 081101 ; 081103 ; 081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, synchronization for a class of uncertain fractional-order neural networks with external disturbances is discussed by means of adaptive fuzzy control. Fuzzy logic systems, whose inputs are chosen as synchronization errors,are employed to approximate the unknown nonlinear functions. Based on the fractional Lyapunov stability criterion, an adaptive fuzzy synchronization controller is designed, and the stability of the closed-loop system, the convergence of the synchronization error, as well as the boundedness of all signals involved can be guaranteed. To update the fuzzy parameters,fractional-order adaptations laws are proposed. Just like the stability analysis in integer-order systems, a quadratic Lyapunov function is used in this paper. Finally, simulation examples are given to show the effectiveness of the proposed method.
引用
收藏
页码：262 / 271
页数：10
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