Quasi-synchronization of fractional-order complex networks with random coupling via quantized control

doi:10.1088/1674-1056/acedf4

中国物理B ›› 2023, Vol. 32 ›› Issue (11): 110501-110501.doi: 10.1088/1674-1056/acedf4

Quasi-synchronization of fractional-order complex networks with random coupling via quantized control

Hongwei Zhang(张红伟), Ran Cheng(程然), and Dawei Ding(丁大为)^†

School of Electronics and Information Engineering, Anhui University, Hefei 230601, China

收稿日期:2023-04-18 修回日期:2023-07-26 接受日期:2023-08-08 出版日期:2023-10-16 发布日期:2023-10-16
通讯作者: Dawei Ding E-mail:dwding@ahu.edu.cn
基金资助:
The work was supported by the Anhui Provincial Development and Reform Commission New Energy Vehicles and Intelligent Connected Automobile Industry Technology Innovation Project.

Quasi-synchronization of fractional-order complex networks with random coupling via quantized control

Hongwei Zhang(张红伟), Ran Cheng(程然), and Dawei Ding(丁大为)^†

School of Electronics and Information Engineering, Anhui University, Hefei 230601, China

Received:2023-04-18 Revised:2023-07-26 Accepted:2023-08-08 Online:2023-10-16 Published:2023-10-16
Contact: Dawei Ding E-mail:dwding@ahu.edu.cn
Supported by:
The work was supported by the Anhui Provincial Development and Reform Commission New Energy Vehicles and Intelligent Connected Automobile Industry Technology Innovation Project.

摘要/Abstract

摘要： We investigate the quasi-synchronization of fractional-order complex networks (FCNs) with random coupling via quantized control. Firstly, based on the logarithmic quantizer theory and the Lyapunov stability theory, a new quantized feedback controller, which can make all nodes of complex networks quasi-synchronization and eliminate the disturbance of random coupling in the system state, is designed under non-delay conditions. Secondly, we extend the theoretical results under non-delay conditions to time-varying delay conditions and design another form of quantization feedback controller to ensure that the network achieves quasi-synchronization. Furthermore, the error bound of quasi-synchronization is obtained. Finally, we verify the accuracy of our results using two numerical simulation examples.

关键词: complex network, fractional-order, random coupling, time-varying delay, quasi-synchronization, quantized control

Abstract: We investigate the quasi-synchronization of fractional-order complex networks (FCNs) with random coupling via quantized control. Firstly, based on the logarithmic quantizer theory and the Lyapunov stability theory, a new quantized feedback controller, which can make all nodes of complex networks quasi-synchronization and eliminate the disturbance of random coupling in the system state, is designed under non-delay conditions. Secondly, we extend the theoretical results under non-delay conditions to time-varying delay conditions and design another form of quantization feedback controller to ensure that the network achieves quasi-synchronization. Furthermore, the error bound of quasi-synchronization is obtained. Finally, we verify the accuracy of our results using two numerical simulation examples.

Key words: complex network, fractional-order, random coupling, time-varying delay, quasi-synchronization, quantized control

中图分类号: (Synchronization; coupled oscillators)

05.45.Xt

02.30.Yy (Control theory) 45.10.Hj (Perturbation and fractional calculus methods)

Hongwei Zhang(张红伟), Ran Cheng(程然), and Dawei Ding(丁大为). Quasi-synchronization of fractional-order complex networks with random coupling via quantized control[J]. 中国物理B, 2023, 32(11): 110501-110501.

Hongwei Zhang(张红伟), Ran Cheng(程然), and Dawei Ding(丁大为). Quasi-synchronization of fractional-order complex networks with random coupling via quantized control[J]. Chin. Phys. B, 2023, 32(11): 110501-110501.

参考文献

[1] Albert R and Barabasi A 2002 Rev. Mod. Phys. 74 47
[2] Philipp H, Aline V and Philipp L 2018 J. Nonlinear Sci. 30 2259
[3] Li X R, Liu J Q and Dong J C2021 IEEE Trans. Circuits Syst. I:Regular Papers 68 4268
[4] Huang L L, Zhang Y, Xiang J and Liu J 2022IEEE Trans. Circuits Syst. I!I:Express Briefs 69 4568
[5] Liu Y Y and Slotine J J 2011 Nature 473 167
[6] Rosvall M and Bergstrom C T 2008 Proc. Natl. Acad. Sci. USA 105 1118
[7] Wang L and Wang P 2015 Int. J. Mod. Phys. C 26 1550052
[8] Russo G 2018 Int. J. Robust Nonlinear Control 28 120
[9] Shakibian H and Charkari N M 2016 2016 24th Iranian Conference on Electrical Engineering (ICEE), May 10-12, 2016, Shiraz, Iran, pp. 682-686
[10] Huang L L, Li W Y, Xiang J H and Zhu G L 2022 Eur. Phys. J. Spec. Top. 231 3109
[11] Yang F, Li H, Guo C, Xia D and Qi H 2018 Neural Comput. Appl. 31 7945
[12] Ding X S, Cao J D and Alsaadi F E 2019 Int. J. Adaptive Control Signal Process. 33 1478
[13] Mwanandiye E S, Wu B and Jia Q 2020 Neural Comput. Appl. 32 11277
[14] Ding D W, Yan J, Wang N and Liang D 2017 Chaos, Solitons Fractals 104 41
[15] He W L, Qian F, Lam J, Chen G and Han Q L 2015 Automatica 62 249
[16] Xu L G, Chu X Y and Hu H X 2021 Math. Comput. Simul. 185 594
[17] Yang S A, Yu J, Cheng H and Jiang H J 2018 Neural Networks 104 104
[18] Machado J T, Kiryakova V and Mainardi F 2011Commun. Nonlinear Sci. Numerical Simul. 16 1140
[19] Aguila C and Duarte M A 2014 Commun. Nonlinear Sci. Numerical Simul. 19 2951
[20] Hartley T T, Lorenzo C F and Qammer H K 1995 IEEE Trans. Circuits Syst. I:Fundam. Theory Appl. 42 485
[21] Saadatmandi A and Dehghan M 2010 Comput. Math. Appl. 59 1326
[22] Sun H G, Zhang Y, Baleanu D, Chen W and Chen Y G 2018 Commun. Nonlinear Sci. Numerical Simul. 64 213
[23] Magin R L 2010 Comput. Math. Appl. 59 1586
[24] Ding D W, Yao X L and Zhang H W 2019 Mod. Phys. Lett. B 33 1950351
[25] Bao H B, Park J H and Cao J D 2021 IEEE Trans. Neural Networks Learning Syst. 32 3230
[26] Xu Y, Wang Q, Li W X and Feng J Q 2021 Math. Methods Appl. Sci. 69 1539
[27] He J J, Chen H, Ge M F and Ding T F 2021 Neurocomputing 431 90
[28] Hu J T, Sui G X and Li X D 2020 Chaos, Solitons Fractals 140 110216
[29] Li C G and Chen G R 2004 Physica A 343 263
[30] Wu Y Q and Liu L 2015 Entropy 17 3097
[31] Hang L H and Wu X R 2019 Neural Process. Lett. 50 2373
[32] Li W Y, Zhou J, Li J Q and Xie T 2021 IEEE Trans. Circuits Syst. I!$I:Express Briefs 68 1338
[33] Zhang L L, Zhong J and Lu J 2021 Neural Networks 144 11
[34] Zhang Q J, Luo J and Li W 2013 Nonlinear Dyn. 71 353
[35] Brockett R and Liberzon D 2000 IEEE Trans. Automat. Control 45 1279
[36] Niu Y G and Daniel W H 2014 Automatica 50 2665
[37] Shi Y J and Ma Y 2021 Electron. Res. Arch. 29 2047
[38] Xu C, Yang X S, Lu J Q and Feng J W 2018 IEEE Trans. Cybernet. 48 3021

Quasi-synchronization of fractional-order complex networks with random coupling via quantized control

Quasi-synchronization of fractional-order complex networks with random coupling via quantized control

RichHTML

PDF (PC)

赞

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

Metrics

本文评价

推荐阅读 0

[1]	Jia-Hui Song(宋家辉). Important edge identification in complex networks based on local and global features[J]. 中国物理B, 2023, 32(9): 98901-098901.
[2]	Dan Chen(陈单), Defu Cai(蔡德福), and Housheng Su(苏厚胜). Self-similarity of complex networks under centrality-based node removal strategy[J]. 中国物理B, 2023, 32(9): 98903-098903.
[3]	Duolan(朵兰), Linying Xiang(项林英), and Guanrong Chen(陈关荣). Synchronization of stochastic complex networks with time-delayed coupling[J]. 中国物理B, 2023, 32(6): 60502-060502.
[4]	Yun Zhai(翟云), Xuan Wang(王璇), Jinghua Xiao(肖井华), and Zhigang Zheng(郑志刚). Stability and multistability of synchronization in networks of coupled phase oscillators[J]. 中国物理B, 2023, 32(6): 60503-060503.
[5]	Zijian Yan(严子健), Yongxiang Xia(夏永祥), Lijun Guo(郭丽君), Lingzhe Zhu(祝令哲), Yuanyuan Liang(梁圆圆), and Haicheng Tu(涂海程). Identification of key recovering node for spatial networks[J]. 中国物理B, 2023, 32(6): 68901-068901.
[6]	Peishi Yang(杨培实), Pengli Lu(卢鹏丽), and Teng Zhang(张腾). AG-GATCN: A novel method for predicting essential proteins[J]. 中国物理B, 2023, 32(5): 58902-058902.
[7]	Jie Zhou(周洁), Cheng Yuan(袁诚), Zu-Yu Qian(钱祖燏), Bing-Hong Wang(汪秉宏), and Sen Nie(聂森). Analysis of cut vertex in the control of complex networks[J]. 中国物理B, 2023, 32(2): 28902-028902.
[8]	Da Ai(艾达), Xin-Long Liu(刘鑫龙), Wen-Zhe Kang(康文哲), Lin-Na Li(李琳娜), Shao-Qing Lü(吕少卿), and Ying Liu(刘颖). SLGC: Identifying influential nodes in complex networks from the perspectives of self-centrality, local centrality, and global centrality[J]. 中国物理B, 2023, 32(11): 118902-118902.
[9]	Lu Ma(马璐), Yan-Lin Ren(任彦霖), Ai-Jun He(何爱军), De-Qiang Cheng(程德强), and Xiao-Dong Yang(杨小冬). Detection of EEG signals in normal and epileptic seizures with multiscale multifractal analysis approach via weighted horizontal visibility graph[J]. 中国物理B, 2023, 32(11): 110506-110506.
[10]	Xianjia Wang(王先甲) and Tao Wang(王饕). Effect of conformity on evolution of cooperation in a coordination game[J]. 中国物理B, 2023, 32(10): 100202-100202.
[11]	Pengli Lu(卢鹏丽) and Wei Chen(陈玮). Vertex centrality of complex networks based on joint nonnegative matrix factorization and graph embedding[J]. 中国物理B, 2023, 32(1): 18903-018903.
[12]	Zhi-Jun Li(李志军), Wen-Qiang Xie(谢文强), Jin-Fang Zeng(曾金芳), and Yi-Cheng Zeng(曾以成). Firing activities in a fractional-order Hindmarsh-Rose neuron with multistable memristor as autapse[J]. 中国物理B, 2023, 32(1): 10503-010503.
[13]	Chaoyi Shi(史朝义), Qi Zhang(张琦), and Tianguang Chu(楚天广). Effect of observation time on source identification of diffusion in complex networks[J]. 中国物理B, 2022, 31(7): 70203-070203.
[14]	Yan-Mei Lu(卢艳梅), Chun-Hua Wang(王春华), Quan-Li Deng(邓全利), and Cong Xu(徐聪). The dynamics of a memristor-based Rulkov neuron with fractional-order difference[J]. 中国物理B, 2022, 31(6): 60502-060502.
[15]	Jing-Cheng Zhu(朱敬成) and Lun-Wen Wang(王伦文). An extended improved global structure model for influential node identification in complex networks[J]. 中国物理B, 2022, 31(6): 68904-068904.