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Volume 11 Issue 12
Dec.  2024

IEEE/CAA Journal of Automatica Sinica

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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

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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  • 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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    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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