Adaptive Synchronization for a Class of Uncertain Fractional-Order Neural Networks

被引：56
|
作者：
Liu, Heng [1 ,2 ]
Li, Shenggang [1 ]
Wang, Hongxing [2 ]
Huo, Yuhong [2 ]
Luo, Junhai [3 ]
机构：
[1] Shaanxi Normal Univ, Coll Math & Informat Sci, Xian 710119, Peoples R China
[2] Huainan Normal Univ, Dept Appl Math, Huainan 232038, Peoples R China
[3] Univ Elect Sci & Technol China, Sch Elect Engn, Chengdu 611731, Peoples R China
来源：
ENTROPY | 2015年 / 17卷 / 10期
基金：
中国国家自然科学基金;
关键词：
fractional-order neural network; adaptive control; synchronization; FINITE-TIME STABILITY; LYAPUNOV FUNCTIONS; PARAMETERS; CHAOS;
D O I：
10.3390/e17107185
中图分类号：
O4 [物理学];
学科分类号：
0702 ;
摘要：
In this paper, synchronization for a class of uncertain fractional-order neural networks subject to external disturbances and disturbed system parameters is studied. Based on the fractional-order extension of the Lyapunov stability criterion, an adaptive synchronization controller is designed, and fractional-order adaptation law is proposed to update the controller parameter online. The proposed controller can guarantee that the synchronization errors between two uncertain fractional-order neural networks converge to zero asymptotically. By using some proposed lemmas, the quadratic Lyapunov functions are employed in the stability analysis. Finally, numerical simulations are presented to confirm the effectiveness of the proposed method.
引用
收藏
页码：7185 / 7200
页数：16
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