Abstract

In spite of the recent interest and advances in linear controllability of complex networks, controlling nonlinear network dynamics remains an outstanding problem. Here we develop an experimentally feasible control framework for nonlinear dynamical networks that exhibit multistability. The control objective is to apply parameter perturbation to drive the system from one attractor to another, assuming that the former is undesired and the latter is desired. To make our framework practically meaningful, we consider restricted parameter perturbation by imposing two constraints: it must be experimentally realizable and applied only temporarily. We introduce the concept of attractor network, which allows us to formulate a quantifiable controllability framework for nonlinear dynamical networks: a network is more controllable if the attractor network is more strongly connected. We test our control framework using examples from various models of experimental gene regulatory networks and demonstrate the beneficial role of noise in facilitating control.

Original languageEnglish (US)
Article number11323
JournalNature Communications
Volume7
DOIs
StatePublished - Apr 14 2016

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Nonlinear Dynamics
Gene Regulatory Networks
controllability
Controllability
Noise
Theoretical Models
Nonlinear networks
Complex networks
Genes
perturbation
genes

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)
  • Chemistry(all)
  • Physics and Astronomy(all)

Cite this

A geometrical approach to control and controllability of nonlinear dynamical networks. / Wang, Le Zhi; Su, Ri Qi; Huang, Zi Gang; Wang, Xiao; Wang, Wen Xu; Grebogi, Celso; Lai, Ying-Cheng.

In: Nature Communications, Vol. 7, 11323, 14.04.2016.

Research output: Contribution to journalArticle

Wang, Le Zhi ; Su, Ri Qi ; Huang, Zi Gang ; Wang, Xiao ; Wang, Wen Xu ; Grebogi, Celso ; Lai, Ying-Cheng. / A geometrical approach to control and controllability of nonlinear dynamical networks. In: Nature Communications. 2016 ; Vol. 7.
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AU - Lai, Ying-Cheng

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