Estimate scheme for fractional order-dependent fixed-time synchronization on Caputo quaternion-valued BAM network systems with time-varying delays

被引:19
作者
Cheng, Yuhong [1 ]
Zhang, Hai [1 ]
Stamova, Ivanka [2 ]
Cao, Jinde [3 ,4 ]
机构
[1] Anqing Normal Univ, Sch Math & Phys, Anqing 246133, Peoples R China
[2] Univ Texas San Antonio, Dept Math, San Antonio, TX 78249 USA
[3] Southeast Univ, Sch Math, Nanjing 211189, Peoples R China
[4] Yonsei Univ, Yonsei Frontier Lab, Seoul 03722, South Korea
来源
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS | 2023年 / 360卷 / 03期
基金
中国国家自然科学基金;
关键词
NEURAL-NETWORKS; FINITE-TIME; MIXED DELAYS; STABILITY; DESIGN;
D O I
10.1016/j.jfranklin.2022.10.055
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In this paper, an estimate scheme for derivative order-dependent fixed-time synchronization (F-TS) on Caputo quaternion-valued BAM neural networks (QVBAMNNs) with time-varying delays is imple-mented. A novel fractional-order (FO) F-T stability lemma is established by the synthetic properties of fractional calculus. The appropriate feedback controllers are designed to realize the F-TS between the master-slave systems. Based on the Lyapunov functional method and multiple inequality techniques, the F-TS criterion of FOQVBAMNNs is obtained. Furthermore, the upper bound of settling time is predicted and controlled by the Caputo derivative order and system parameters, which is independent of the initial state. Finally, two simulation examples manifest the feasibility and validity of the results on F-TS and the control strategies.(c) 2022 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.
引用
收藏
页码:2379 / 2403
页数:25
相关论文
共 48 条
[1]   Global Mittag-Leffler stability analysis of impulsive fractional-order complex-valued BAM neural networks with time varying delays [J].
Ali, M. Syed ;
Narayanan, G. ;
Shekher, Vineet ;
Alsaedi, Ahmed ;
Ahmad, Bashir .
COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION, 2020, 83
[2]   Dynamic stability analysis of stochastic fractional-order memristor fuzzy BAM neural networks with delay and leakage terms [J].
Ali, M. Syed ;
Narayanan, Govindasamy ;
Shekher, Vineet ;
Alsulami, Hamed ;
Saeed, Tareq .
APPLIED MATHEMATICS AND COMPUTATION, 2020, 369
[3]   Quaternion nonlinear Lu model and its novel quaternion complete synchronization [J].
Alyami, Maryam Ahmed ;
Mahmoud, Emad E. .
ALEXANDRIA ENGINEERING JOURNAL, 2020, 59 (03) :1391-1403
[4]   Controller design for finite-time and fixed-time stabilization of fractional-order memristive complex-valued BAM neural networks with uncertain parameters and time-varying delays [J].
Arslan, Emel ;
Narayanan, G. ;
Ali, M. Syed ;
Arik, Sabri ;
Saroha, Sumit .
NEURAL NETWORKS, 2020, 130 :60-74
[5]   Adaptive Synchronization of Fractional-Order Output-Coupling Neural Networks via Quantized Output Control [J].
Bao, Haibo ;
Park, Ju H. ;
Cao, Jinde .
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2021, 32 (07) :3230-3239
[6]   A new fixed-time stability theorem and its application to the fixed-time synchronization of neural networks [J].
Chen, Chuan ;
Li, Lixiang ;
Peng, Haipeng ;
Yang, Yixian ;
Mi, Ling ;
Zhao, Hui .
NEURAL NETWORKS, 2020, 123 :412-419
[7]   Finite-time stabilization of fractional-order fuzzy quaternion-valued BAM neural networks via direct quaternion approach [J].
Chen, Shenglong ;
Li, Hong-Li ;
Kao, Yonggui ;
Zhang, Long ;
Hu, Cheng .
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS, 2021, 358 (15) :7650-7673
[8]   A new fixed-time stability criterion for fractional-order systems [J].
Ding, Yucai ;
Liu, Hui .
AIMS MATHEMATICS, 2022, 7 (04) :6173-6181
[9]   Finite-/fixed-time anti-synchronization of neural networks with leakage delays under discontinuous disturbances [J].
Duan, Lian ;
Liu, Jinzhi ;
Huang, Chuangxia ;
Wang, Zengyun .
CHAOS SOLITONS & FRACTALS, 2022, 155
[10]   Fixed-time synchronization of fuzzy neutral-type BAM memristive inertial neural networks with proportional delays [J].
Duan, Liyan ;
Li, Junmin .
INFORMATION SCIENCES, 2021, 576 :522-541