## Optimizing Dynamical Network Structure for Pinning Control

- Yasin Orouskhani, Mahdi Jalili, Xinghuo Yu
- Scientific reports
- 2016

- Published 2015 in Scientific reports

Controlling complex networks is of paramount importance in science and engineering. Despite recent efforts to improve controllability and synchronous strength, little attention has been paid to the speed of pinning synchronizability (rate of convergence in pinning control) and the corresponding pinning node selection. To address this issue, we propose a hypothesis to restrict the control cost, then build a linear matrix inequality related to the speed of pinning controllability. By solving the inequality, we obtain both the speed of pinning controllability and optimal control strength (feedback gains in pinning control) for all nodes. Interestingly, some low-degree nodes are able to achieve large feedback gains, which suggests that they have high influence on controlling system. In addition, when choosing nodes with high feedback gains as pinning nodes, the controlling speed of real systems is remarkably enhanced compared to that of traditional large-degree and large-betweenness selections. Thus, the proposed approach provides a novel way to investigate the speed of pinning controllability and can evoke other effective heuristic pinning node selections for large-scale systems.

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@inproceedings{Zhou2015EnhancingSO,
title={Enhancing speed of pinning synchronizability: low-degree nodes with high feedback gains},
author={Ming-Yang Zhou and Zhao Zhuo and Hao Liao and Zhong-Qian Fu and Shimin Cai},
booktitle={Scientific reports},
year={2015}
}