Synchronization for fractional-order neural networks with full/under-actuation using fractional-order sliding mode control

被引：3

作者：

Liu, Heng ^{[1
,2
]}

Pan, Yongping ^{[3
]}

Li, Shenggang ^{[1
]}

Chen, Ye ^{[1
]}

机构：

[1] Shaanxi Normal Univ, Coll Math & Informat Sci, Xian 710119, Shaanxi, Peoples R China

[2] Huainan Normal Univ, Dept Appl Math, Huainan 232038, Peoples R China

[3] Natl Univ Singapore, Dept Biomed Engn, Singapore 117583, Singapore

来源：

INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS | 2018年 / 9卷 / 07期

基金：

中国国家自然科学基金;

关键词：

Fractional-order neural network; Fractional-order sliding mode control; Fractional-order adaptation law; PROJECTIVE SYNCHRONIZATION; LYAPUNOV FUNCTIONS; STABILITY ANALYSIS; UNIFORM STABILITY; SYSTEMS; SURFACE;

D O I：

10.1007/s13042-017-0646-z

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper considers synchronization between two fractional-order neural networks (FONNs). To handle the case of full/under-actuation, i.e. the dimension of the synchronization controller is equal to or less than that of the FONNs, a novel fractional-order integral sliding surface is designed, and the feasibility of the proposed approach is shown by solving two linear matrix inequalities. Then, based on the fractional Lyapunov stability criterion, a fractional-order sliding mode controller equipped with fractional-order adaptation laws is constructed to guarantee the synchronization error converging to an arbitrary small region of the origin. The effectiveness of the proposed control method is verified by two simulation examples.

引用

页码：1219 / 1232

页数：14

共 65 条

[1] A fractional sliding mode for finite-time control scheme with application to stabilization of electrostatic and electromechanical transducers [J].

Aghababa, Mohammad Pourmahmood .

APPLIED MATHEMATICAL MODELLING, 2015, 39 (20) :6103-6113

[2] Finite-time chaos control and synchronization of fractional-order nonautonomous chaotic (hyperchaotic) systems using fractional nonsingular terminal sliding mode technique [J].

Aghababa, Mohammad Pourmahmood .

NONLINEAR DYNAMICS, 2012, 69 (1-2) :247-261

[3] Lyapunov functions for fractional order systems [J].

Aguila-Camacho, Norelys ;

Duarte-Mermoud, Manuel A. ;

Gallegos, Javier A. .

COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION, 2014, 19 (09) :2951-2957

[4]

[Anonymous], 1998, Fractional differential equations: an introduction to fractional derivatives, fractional differential equations, to methods of their solution and some of their applications

[5] Theoretical and practical applications of fuzzy fractional integral sliding mode control for fractional-order dynamical system [J].

Balasubramaniam, P. ;

Muthukumar, P. ;

Ratnavelu, K. .

NONLINEAR DYNAMICS, 2015, 80 (1-2) :249-267

[6] Projective synchronization of fractional-order memristor-based neural networks [J].

Bao, Hai-Bo ;

Cao, Jin-De .

NEURAL NETWORKS, 2015, 63 :1-9

[7] Adaptive synchronization of fractional-order memristor-based neural networks with time delay [J].

Bao, Haibo ;

Park, Ju H. ;

Cao, Jinde .

NONLINEAR DYNAMICS, 2015, 82 (03) :1343-1354

[8] Output tracking of uncertain fractional-order nonlinear systems via a novel fractional-order sliding mode approach [J].

Binazadeh, T. ;

Shafiei, M. H. .

MECHATRONICS, 2013, 23 (07) :888-892

[9] Fuzzy adaptive synchronization of uncertain fractional-order chaotic systems [J].

Bouzeriba, A. ;

Boulkroune, A. ;

Bouden, T. .

INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS, 2016, 7 (05) :893-908

[10] Global Mittag-Leffler stability and synchronization of memristor-based fractional-order neural networks [J].

Chen, Jiejie ;

Zeng, Zhigang ;

Jiang, Ping .

NEURAL NETWORKS, 2014, 51 :1-8

← 1 2 3 4 5 6 7 →