Energy scaling and reduction in controlling complex networks
Abstract
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.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Apr 01, 2016
- Source ID
- 10.1098/rsos.160064
Entities
People
- Le-zhi Wang
- Wen-Xu Wang
- Ying-Cheng Lai
- Yu-zhong Chen
Organizations
- Arizona State University
- Army Research Office
- Beijing Normal University