Centrality measures and the role of non-normality for network control energy reduction

Abstract

Combinations of Gramian-based centrality measures are used for driver node selection in complex networks in order to simultaneously take into account conflicting control energy requirements, like minimizing the average energy needed to steer the state in any direction and the energy needed for the worst direction. The selection strategies that we propose are based on a characterization of the network non-normality, a concept we show is related to the idea of balanced realization.

6 pages

References in corpus (1)

• Minimum energy control for complex networks

Cited by in corpus (8)

• Network structural origin of instabilities in large complex systems
• Turing patterns on discrete topologies: from networks to higher-order structures
• The Efficiency of Synchronization Dynamics and the Role of Network Syncreactivity
• Broken detailed balance and entropy production in directed networks
• Controllability scores for selecting control nodes of large-scale network systems
• Uniqueness Analysis of Controllability Scores and Their Application to Brain Networks
• Input design for the optimal control of networked moments
• Controlling symmetries and clustered dynamics of complex networks