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Recent works revealed that the energy required to control a complex network depends on the number of driving signals and the energy distribution follows an algebraic scaling law. If one implements control using a small number of drivers, e.g. as

Recent works revealed that the energy required to control a complex network depends on the number of driving signals and the energy distribution follows an algebraic scaling law. If one implements control using a small number of drivers, e.g. as determined by the structural controllability theory, there is a high probability that the energy will diverge. We develop a physical theory to explain the scaling behaviour through identification of the fundamental structural elements, the longest control chains (LCCs), that dominate the control energy. Based on the LCCs, we articulate a strategy to drastically reduce the control energy (e.g. in a large number of real-world networks). Owing to their structural nature, the LCCs may shed light on energy issues associated with control of nonlinear dynamical networks.

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    Title
    • Energy Scaling and Reduction in Controlling Complex Networks
    Contributors
    Date Created
    2016-04-20
    Resource Type
  • Text
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    Identifier
    • Digital object identifier: 10.1098/rsos.160064
    • Identifier Type
      International standard serial number
      Identifier Value
      2054-5703
    Note
    • The final version of this article, as published in Royal Society Open Science, can be viewed online at: http://rsos.royalsocietypublishing.org/content/3/4/160064

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    This is a suggested citation. Consult the appropriate style guide for specific citation guidelines.

    Chen, Y., Wang, L., Wang, W., & Lai, Y. (2016). Energy scaling and reduction in controlling complex networks. Royal Society Open Science, 3(4), 160064. doi:10.1098/rsos.160064

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