Name
Abstract | ||
|---|---|---|
Exploring how connection strengths between nodes affect the cost in controlling complex networks with fixed topological structure is an important issue both in theory and applications. In this paper, by considering optimal control of the networks, a matrix function optimization model is proposed to address such an issue. With pre-given input matrix, a normalized gradient descent method (NPGM) is developed to solve the optimization problem, so as to obtain the optimal connection strength matrix. With proposed NPGM, we find that a network adaptively changes its connection strength such that several control-flow subnetworks are self-formed. Moreover, we further point out that the control cost with optimal weight matrix is smallest when pre-located controller sources distribute evenly. These findings provide a comprehensive understanding of the impact of connection link weight on control cost for complex networks. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/ISIE.2017.8001300 | 2017 IEEE 26th International Symposium on Industrial Electronics (ISIE) |
Keywords | Field | DocType |
Complex networks,optimal control,connection strength | Mathematical optimization,Control theory,Gradient descent,Optimal control,Normalization (statistics),Matrix (mathematics),Control theory,Matrix function,Complex network,Optimization problem,Mathematics | Conference |
ISSN | ISBN | Citations |
2163-5137 | 978-1-5090-1413-2 | 0 |
PageRank | References | Authors |
0.34 | 6 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jie Ding | 1 | 10 | 3.56 |
| Changyun Wen | 2 | 3686 | 284.86 |
| Guoqi Li | 3 | 387 | 46.18 |