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Volume 11 Issue 12
Dec.  2024

IEEE/CAA Journal of Automatica Sinica

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Article Navigation >  IEEE/CAA Journal of Automatica Sinica  > 2024  >  11(12): 2476-2486
L. Wang, Z. Li, L. Cao, G. Guo, and  Z. Kong,  “Controllability of multi-relational networks with heterogeneous dynamical nodes,” IEEE/CAA J. Autom. Sinica, vol. 11, no. 12, pp. 2476–2486, Dec. 2024. doi: 10.1109/JAS.2024.124404
Citation: L. Wang, Z. Li, L. Cao, G. Guo, and  Z. Kong,  “Controllability of multi-relational networks with heterogeneous dynamical nodes,” IEEE/CAA J. Autom. Sinica, vol. 11, no. 12, pp. 2476–2486, Dec. 2024. doi: 10.1109/JAS.2024.124404
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Controllability of Multi-Relational Networks With Heterogeneous Dynamical Nodes

doi: 10.1109/JAS.2024.124404
Funds:  This work was supported by the National Natural Science Foundation of China (61573077, U1808205), China Scholarship Council (202308130119), and Natural Science Foundation of Hebei Province (F2022501005)
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    Abstract
  • This paper studies the controllability of networked systems, in which the nodes are heterogeneous high-dimensional dynamical systems, and the links between nodes are multi-relational. Our aim is to find controllability criteria for heterogeneous networks with multi-relational links beyond those only applicable to networks with single-relational links. It is found a network with multi-relational links can be controllable even if each single-relational network topology is uncontrollable, and vice versa. Some sufficient and necessary conditions are derived for the controllability of multi-relational networks with heterogeneous dynamical nodes. For two typical multi-relational networks with star-chain topology and star-circle topology, some easily verified conditions are presented. For illustration and verification, several examples are presented. These findings provide practical insights for the analysis and control of multi-relational complex systems.

     

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  • [1]
    J. Lu, G. Wen, R. Lu, Y. Wang, and S. Zhang, “Networked knowledge and complex networks: An engineering view,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 8, pp. 1366–1383, Aug. 2022. doi: 10.1109/JAS.2022.105737
    [2]
    S. Chang, E. Pierson, P. W. Koh, J. Gerardin, B. Redbird, D. Grusky, and J. Leskovec, “Mobility network models of COVID-19 explain inequities and inform reopening,” Nature, vol. 589, no. 7840, pp. 82–U54, Jan. 2021. doi: 10.1038/s41586-020-2923-3
    [3]
    M. Feng, Y. Li, F. Chen, and J. Kurths, “Heritable deleting strategies for birth and death evolving networks from a queueing system perspective,” IEEE Trans. Syst., Man, Cybern., Syst., vol. 52, no. 10, pp. 6662–6673, Oct. 2022. doi: 10.1109/TSMC.2022.3149596
    [4]
    L. Wang, Z. Li, G. Zhao, G. Guo, and Z. Kong, “Input structure design for structural controllability of complex networks,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 7, pp. 1571–1581, Jul. 2023. doi: 10.1109/JAS.2023.123504
    [5]
    D. Siudak, “The effect of self-organizing map architecture based on the value migration network centrality measures on stock return. Evidence from the US market,” PLoS one, vol. 17, no. 11, Nov. 2022.
    [6]
    M. Rinaldi, “Controllability of transportation networks,” Transp. Res. B, Methodol., vol. 118, pp. 381–406, Dec. 2018. doi: 10.1016/j.trb.2018.11.005
    [7]
    A. Louni and K. P. Subbalakshmi, “Who spread that rumor: Finding the source of information in large online social networks with probabilistically varying internode relationship strengths,” IEEE Trans. Comput. Social. Syst., vol. 5, no. 2, pp. 335–343, Jun. 2018. doi: 10.1109/TCSS.2018.2801310
    [8]
    L. Xiang, F. Chen, W. Ren, and G. Chen, “Advances in network controllability,” IEEE Circuits Syst. Mag., vol. 19, no. 2, pp. 8–32, 2019. doi: 10.1109/MCAS.2019.2909446
    [9]
    B. She, S. Mehta, C. Ton, and Z. Kan, “Energy-related controllability of signed complex networks with Laplacian dynamics,” IEEE Trans. Autom. Control, vol. 66, no. 7, pp. 3325–3330, Jul. 2021. doi: 10.1109/TAC.2020.3017739
    [10]
    B. She, S. S. Mehta, E. Doucette, C. Ton, and Z. Kan, “Characterizing energy-related controllability of composite complex networks via graph product,” IEEE Trans. Autom. Control, vol. 66, no. 7, pp. 3205–3212, Jul. 2021. doi: 10.1109/TAC.2020.3028840
    [11]
    M. V. Srighakollapu, R. K. Kalaimani, and R. Pasumarthy, “Optimizing driver nodes for structural controllability of temporal networks,” IEEE Trans. Control Netw. Syst., vol. 9, no. 1, pp. 380–389, Mar. 2022. doi: 10.1109/TCNS.2021.3106454
    [12]
    F. D. Rossa and P. DeLellis, “Stochastic pinning controllability of noisy complex networks,” IEEE Trans. Control Netw. Syst., vol. 7, no. 4, pp. 1678–1687, Dec. 2020. doi: 10.1109/TCNS.2020.2995818
    [13]
    P. Arebi, A. Fatemi, and R. Ramezani, “Event stream controllability on event-based complex networks,” Expert Syst. Appl., vol. 213, Mar. 2023.
    [14]
    Y. Y. Liu, J. J. Slotine, and A. L. Barabasi, “Controllability of complex networks,” Nature, vol. 473, no. 7346, pp. 167–173, 2011. doi: 10.1038/nature10011
    [15]
    Z. Yuan, C. Zhao, Z. Di, W. Wang, and Y. Lai, “Exact controllability of complex networks,” Nat. Commun., vol. 4, no. 1, pp. 24–47, Sept. 2013.
    [16]
    L. Wang, G. Chen, X. Wang, and W. K. S. Tang, “Controllability of networked MIMO systems,” Automatica, vol. 69, pp. 405–409, Jul. 2016. doi: 10.1016/j.automatica.2016.03.013
    [17]
    Y. Hao, Z. Duan, and G. Chen, “Further on the controllability of networked MIMO LTI systems,” Int. J. Robust Nonlinear Control, vol. 28, no. 5, pp. 1778–1788, Mar. 2018. doi: 10.1002/rnc.3986
    [18]
    Y. Hao, Z. Duan, G. Chen, and F. Wu, “New controllability conditions for networked identical LTI systems,” IEEE Trans. Autom. Control, vol. 64, no. 10, pp. 4223–4228, Oct. 2019. doi: 10.1109/TAC.2019.2893899
    [19]
    J. Wu, X. Li, and G. Chen, “Controllability of deep-coupling dynamical networks,” IEEE Trans. Circuits Syst. I, Reg. Papers, vol. 67, no. 12, pp. 5211–5222, Dec. 2020. doi: 10.1109/TCSI.2020.2999451
    [20]
    K. Song, G. Li, X. Chen, L. Deng, G. Xiao, F. Zeng, and J. Pei, “Target controllability of two-layer multiplex networks based on network flow theory,” IEEE Trans. Cybern., vol. 51, no. 5, pp. 2699–2711, May 2021. doi: 10.1109/TCYB.2019.2906700
    [21]
    J. Ding, C. Wen, G. Li, P. Tu, D. Ji, Y. Zou, and J. Huang, “Target controllability in multilayer networks via minimum-cost maximum-flow method,” IEEE Trans. Neural Netw. Learn. Syst., vol. 32, no. 5, pp. 1949–1962, May 2021. doi: 10.1109/TNNLS.2020.2995596
    [22]
    T. Zhou, “On the controllability and observability of networked dynamic systems,” Automatica, vol. 52, no. 1, pp. 63–75, 2015.
    [23]
    L. Xiang, P. Wang, F. Chen, and G. Chen, “Controllability of directed networked MIMO systems with heterogeneous dynamics,” IEEE Trans. Control Netw. Syst., vol. 7, no. 2, pp. 807–817, Jun. 2020. doi: 10.1109/TCNS.2019.2948994
    [24]
    Z. Kong, L. Cao, L. Wang, and G. Guo, “Controllability of heterogeneous networked systems with nonidentical inner-coupling matrices,” IEEE Trans. Control Netw. Syst., vol. 9, no. 2, pp. 867–878, Jun. 2022. doi: 10.1109/TCNS.2021.3124907
    [25]
    J. Mu, J. Wu, N. Li, X. Zhang, and S. Li, “Structural controllability of networked systems with general heterogeneous subsystems,” Asian J. Control, vol. 24, no. 3, pp. 1321–1332, May 2022. doi: 10.1002/asjc.2528
    [26]
    D. Delpini, S. Battiston, M. Riccaboni, G. Gabbi, F. Pammoli, and G. Caldarelli, “Evolution of controllability in interbank networks,” Sci. Rep., vol. 3, no. 1, p. 1626, Apr. 2013. doi: 10.1038/srep01626
    [27]
    S. Battiston, M. Puliga, R. Kaushik, P. Tasca, and G. Caldarelli, “DebtRank: Too central to fail? Financial networks, the FED and systemic risk,” Sci. Rep., vol. 2, no. 541, pp. 1–6, Aug. 2012.
    [28]
    N. N. Chung and L. Y. Chew, “Modelling Singapore COVID-19 pandemic with a SEIR multiplex network model,” Sci. Rep., vol. 11, no. 1, May 2021.
    [29]
    X. Zhao, Q. Zhou, A. Wang, F. Zhu, Z. Meng, and C. Zuo, “The impact of awareness diffusion on the spread of COVID-19 based on a two-layer SEIR/V-UA epidemic model,” J. Med. Virol., vol. 93, no. 7, pp. 4342–4350, Jul. 2021. doi: 10.1002/jmv.26945
    [30]
    L. He and L. Zhu, “Modeling the COVID-19 epidemic and awareness diffusion on multiplex networks,” Commun. Theor. Phys., vol. 73, no. 3, May 2021.
    [31]
    M. Roman, Advanced Linear Algebra, New York: Springer, 2005.
    [32]
    C. T. Chen, Linear System Theory and Design, Oxford University Press, 1999.
    [33]
    S. H. Belkacem, Linear Algebra, Birkhauser Cham, 2017.
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    Highlights

    • Explores controllability in heterogeneous multi-relational networks
    • Derives controllability criteria for heterogeneous networks with multi-relational links
    • Several criteria for typical network structures are proposed
    • Provides practical insights for controlling complex systems

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