Control Principles of Complex Networks

  title={Control Principles of Complex Networks},
  author={Yang-Yu Liu and A L Barabasi},
A reflection of our ultimate understanding of a complex system is our ability to control its behavior. Typically, control has multiple prerequisites: It requires an accurate map of the network that governs the interactions between the system's components, a quantitative description of the dynamical laws that govern the temporal behavior of each component, and an ability to influence the state and temporal behavior of a selected subset of the components. With deep roots in nonlinear dynamics and… 

Structure-based control of complex networks with nonlinear dynamics

A feedback-based framework for control of networks governed by a broad class of nonlinear dynamics that includes the major dynamic models of biological, technological, and social processes is adapted and provides realizable node overrides that steer a system toward any of its natural long-term dynamic behaviors.

Control energy of complex networks towards distinct mixture states

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Control principles for complex biological networks

The structural controllability of complex networks is introduced and its advantages and disadvantages are discussed and the existing methods for finding the unique minimum set of driver nodes via the optimal control for complex networks are summarized.

Data-driven control of complex networks

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Domain control of nonlinear networked systems and applications to complex disease networks

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Correlations in the degeneracy of structurally controllable topologies for networks

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Controlling edge dynamics in multilayer networks

Target control of edge dynamics in complex networks

Fundamental building blocks of controlling complex networks: A universal controllability framework

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Controllability limit of edge dynamics in complex networks.

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Controllability of complex networks

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Emergence of bimodality in controlling complex networks

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The paradox of controlling complex networks: control inputs versus energy requirement

The fundamental structures embedded in the network, the longest control chains, which determine the control energy and give rise to the power-scaling behavior are identified and the issue of control precision is addressed.

Intrinsic dynamics induce global symmetry in network controllability

Interestingly, a global symmetry accounting for the invariance of controllability with respect to exchanging the densities of any two different types of dynamic units, irrespective of the network topology is found.

Structural permeability of complex networks to control signals

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Controlling complex, non-linear dynamical networks

An outstanding problem in the field of complex dynamical systems is to control non-linear dynamics on complex networks and the coupling between non- linear dynamics and complex network structures presents tremendous challenges to the ability to formulate effective control methodologies.

Optimizing controllability of complex networks by minimum structural perturbations.

This work proposes a general approach to optimizing the controllability of complex networks by judiciously perturbing the network structure by validated theoretically and demonstrated numerically for homogeneous and heterogeneous random networks and for different types of real networks as well.

Pinning a complex dynamical network to its equilibrium

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