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Finite-time synchronization of uncertain fractional-order multi-weighted complex networks with external disturbances via adaptive 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 |
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Abstract The finite-time synchronization of fractional-order multi-weighted complex networks (FMCNs) with uncertain parameters and external disturbances is studied. Firstly, based on fractional calculus characteristics and Lyapunov stability theory, quantized controllers are designed to guarantee that FMCNs can achieve synchronization in a limited time with and without coupling delay, respectively. Then, appropriate parameter update laws are obtained to identify the uncertain parameters in FMCNs. Finally, numerical simulation examples are given to validate the correctness of the theoretical results.
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Received: 07 March 2022
Revised: 05 April 2022
Accepted manuscript online:
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PACS:
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05.45.-a
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(Nonlinear dynamics and chaos)
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05.45.Xt
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(Synchronization; coupled oscillators)
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02.30.Yy
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(Control theory)
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Corresponding Authors:
Dawei Ding
E-mail: dwding@ahu.edu.cn
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Cite this article:
Hongwei Zhang(张红伟), Ran Cheng(程然), and Dawei Ding(丁大为) Finite-time synchronization of uncertain fractional-order multi-weighted complex networks with external disturbances via adaptive quantized control 2022 Chin. Phys. B 31 100504
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[1] Boccaletti S, Latora V, Moreno Y, Chavez M and Hwang H U 2006 Phys. Rep. 424 175
[2] Rosvall M and Bergstrom C T 2008 Proc. Natl. Acad. Sci. USA 105 4
[3] Wang L and Wang P 2015 Int. J. Modern Phys. C 26 1550052
[4] Johnsen T E, Mikkelsen O S and Wong C Y 2019 Supp. Chain Manag. 24 872
[5] Zhai S and Yang X S 2014 IET Control Theory Appl. 8 61
[6] Zhang C and Shi L 2019 J. Franklin Instit. 356 4106
[7] Zhang C and Chen T 2018 Physica A 496 602
[8] Zhang C and Han B S 2020 Physica A 538 122827
[9] Xu Y, Li Y Z and Li W X 2020 Commun. Nonlinear Sci. Numer. Simulat. 85 105239
[10] Yao X, Xia D and Zhang C M 2021 Math. Methods Appl. Sci. 44 1570
[11] Ding D W, Yan J, Wang N and Liang D 2017 Chaos, Solitons and Fractals 104 41
[12] Hu C, He H B and Jiang H J 2020 Automatica 112 108675
[13] Zhang C, Wang X Y, Ye X, Zhou S and Feng L 2020 ISA Transact. 101 42
[14] Jin Y G, Zhong S M and An N 2014 Chin. Phys. B 24 049202
[15] Wang Q, Wang J L, Huang Y L and Ren S Y 2018 J. Franklin Instit. 355 6597
[16] Zhao L H, Wang J L and Zhang Y 2020 J. Franklin Instit. 357 414
[17] Yang Q J, Wu H Q and Cao J D 2021 Neurocomput. 428 182
[18] Liu L, Ding X W and Zhou W N 2021 Neurocomputing 419 136
[19] Shi L, Zhu H and Zhong S M 2017 Nonlinear Dyn. 88 859
[20] Chu X Y, Xu L G and Hu H X 2020 Chaos, Solitons and Fractals 140 110268
[21] Chen X Y, Huang T W, Cao J D, Park J H and Qiu J H 2019 IET Control Theory Appl. 13 1246
[22] Chen X, Yang X S, Lu J Q, Feng J W, Alsaadi F E and Hayat T 2018 IEEE Transact. Cybernet. 48 3021
[23] Guo Y, Chen B D and Wu Y B 2020 J. Franklin Instit. 357 359
[24] He S H, Wu Y Q and Li Y Z 2020 J. Franklin Instit. 357 11645
[25] Zhang W L, Li C D, He X and Li H F 2018 Modern Phys. Lett. B 32 1850002
[26] Huang D B 2004 Phys. Rev. E 69 067201
[27] Mei J, Jiang M H and Wang J 2013 Commun. Nonlinear Sci. Numer. Simulat. 18 999
[28] Liu L F and Miao S X 2018 Physica A 512 890
[29] Zhao H, Li L, Xiao J, Yang Y and Zheng M 2017 Chaos, Solitons and Fractals 104 268
[30] Kilbas A, Srivastava H and Trujillo J 2006 Theory and Application of Fractional Differential Equations (New York: Elsevier) p. 80
[31] Podlubny I 1999 Fractional Differential Equations (San Diego: Academic) p. 141
[32] Kaslik E and Sivasundaram S 2012 Neural Networks 32 245
[33] Jia J, Huang X, Li Y, Cao J D and Alsaedi A 2020 IEEE Transact. Neural Networks Learning Sys. 31 997
[34] Alkahtani B S T 2016 Chaos, Solitons and Fractals 89 547
[35] Petras I 2010 IEEE Transact. Circuits Systems II: Exp. Briefs 57 975
[36] Li H L, Cao J D, Jiang H J and Alsaedi A 2018 J. Franklin Instit. 355 5771
[37] Li H L, Cao J D, Jiang H J and Alsaedi A 2019 Physica A 533 122027
[38] Lu J Y, Guo Y P, Ji Y D and Fan S S 2020 Chaos, Solitons and Fractals 130 109433
[39] Wang J A, Nie R X and Sun Z Y 2014 Chin. Phys. B 23 050509
[40] Gan L Y N, Wu Z Y and Gong X L 2015 Chin. Phys. B 24 040503
[41] Dong H L, Luo M and Xiao M Q 2021 Neural Networks 141 40
[42] Niu Y G and Daniel W C H 2014 Automatica 50 2665
[43] Fu M Y and Xie L H 2005 IEEE Transact. Automatic Control 50 1698
[44] He J J, Chen H, Ge M F, Ding T F, Wang L M and Liang C D 2021 Neurocomput. 431 90
[45] Bao H B, Park J H and Cao J D 2021 IEEE Transact. Neural Networks Learning Sys. 32 3230
[46] Fan Y J, Huang X, Wang Z, Xia J W and Shen H 2020 Neural Proc. Lett. 52 403
[47] Camacho N A, Mermoud M A D and Gallegos J A 2014 Commun. Nonlinear Sci. Numer. Simulat. 19 2951
[48] Ding D W, Yao X L and Zhang H W 2019 Neural Proc. Lett. 51 325
[49] Qian C J and Li J 2021 IEEE Transact. Automatic Control 50 885
[50] Filippov A F 1988 1988 Differential equations with discontinuous right hand sides (Norwell: Kluwer Academic Publishers) pp. 377—390 |
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