Adaptive Synchronization for Uncertain Delayed Fractional-Order Hopfield Neural Networks via Fractional-Order Sliding Mode Control

被引：14
|
作者：
Meng, Bo [1 ,2 ]
Wang, Xiaohong [2 ]
机构：
[1] Shandong Univ Sci & Technol, Coll Elect Engn & Automat, Qingdao 266590, Peoples R China
[2] Shandong Univ Sci & Technol, Coll Math & Syst Sci, Qingdao 266590, Peoples R China
来源：
MATHEMATICAL PROBLEMS IN ENGINEERING | 2018年 / 2018卷
基金：
中国国家自然科学基金;
关键词：
STABILITY ANALYSIS; DIFFERENTIAL-EQUATIONS; EXPONENTIAL STABILITY; NONLINEAR DYNAMICS; UNIQUENESS; SYSTEMS; EXISTENCE; CHAOS;
D O I：
10.1155/2018/1603629
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
Adaptive synchronization for a class of uncertain delayed fractional-order Hopfield neural networks (FOHNNs) with external disturbances is addressed in this paper. For the unknown parameters and external disturbances of the delayed FOHNNs, some adaptive estimations are designed. Firstly, a fractional-order switched sliding surface is proposed for the delayed FOHNNs. Then, according to the fractional-order extension of the Lyapunov stability criterion, a fractional-order sliding mode controller is constructed to guarantee that the synchronization error of the two uncertain delayed FOHNNs converges to an arbitrary small region of the origin. Finally, a numerical example of two-dimensional uncertain delayed FOHNNs is given to verify the effectiveness of the proposed method.
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页数：8
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