166 Citations (Scopus)

Abstract

To drive a large, complex, networked dynamical system toward some desired state using as few external signals as possible is a fundamental issue in the emerging field of controlling complex networks. Optimal control is referred to the situation where such a network can be fully controlled using only one driving signal. We propose a general approach to optimizing the controllability of complex networks by judiciously perturbing the network structure. The principle of our perturbation method is validated theoretically and demonstrated numerically for homogeneous and heterogeneous random networks and for different types of real networks as well. The applicability of our method is discussed in terms of the relative costs of establishing links and imposing external controllers. Besides the practical usage of our approach, its implementation elucidates, interestingly, the intricate relationship between certain structural properties of the network and its controllability.

Original languageEnglish (US)
Article number026115
JournalPhysical Review E - Statistical, Nonlinear, and Soft Matter Physics
Volume85
Issue number2
DOIs
StatePublished - Feb 22 2012

Fingerprint

controllability
Controllability
Complex Networks
Perturbation
perturbation
Heterogeneous Networks
Random Networks
Perturbation Method
Network Structure
Structural Properties
Optimal Control
Dynamical system
Controller
Costs
optimal control
dynamical systems
emerging
controllers
costs

ASJC Scopus subject areas

  • Condensed Matter Physics
  • Statistical and Nonlinear Physics
  • Statistics and Probability

Cite this

Optimizing controllability of complex networks by minimum structural perturbations. / Wang, Wen Xu; Ni, Xuan; Lai, Ying-Cheng; Grebogi, Celso.

In: Physical Review E - Statistical, Nonlinear, and Soft Matter Physics, Vol. 85, No. 2, 026115, 22.02.2012.

Research output: Contribution to journalArticle

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