Title
Deducing complete selection rule set for driver nodes to guarantee networkʼ structural controllability
Abstract
Structural controllability is critical for operating and controlling large-scale complex networks. In real applications, for a given network, it is always desirable to have more selections for driver nodes which make the network structurally controllable. Different from the works in complex network field where structural controllability is often used to explore the emergence properties of complex networks at a macro level, in this paper, we investigate it for control design purpose at the application level and focus on describing and obtaining the solution space for all selections of driver nodes to guarantee structural controllability. In accord with practical applications, we define the complete selection rule set as the solution space which is composed of a series of selection rules expressed by intuitive algebraic forms. It explicitly indicates which nodes must be controlled and how many nodes need to be controlled in a node set and thus is particularly helpful for freely selecting driver nodes. Based on two algebraic criteria of structural controllability, we separately develop an input-connectivity algorithm and a relevancy algorithm to deduce selection rules for driver nodes. In order to reduce the computational complexity, we propose a pretreatment algorithm to reduce the scale of networkʼ structural matrix efficiently, and a rearrangement algorithm to partition the matrix into several smaller ones. A general procedure is proposed to get the complete selection rule set for driver nodes which guarantee networkʼ structural controllability. Simulation tests with efficiency analysis of the proposed algorithms are given and the result of applying the proposed procedure to some real networks is also shown, and these all indicate the validity of the proposed procedure.
Year
DOI
Venue
2019
10.1109/JAS.2017.7510724
IEEE/CAA Journal of Automatica Sinica
Keywords
DocType
Volume
Controllability,Complex networks,Algorithm design and analysis,Aerospace electronics,Tools,Partitioning algorithms,Computational complexity
Journal
6
Issue
ISSN
Citations 
5
2329-9266
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
Xichen Wang100.34
Yugeng Xi233545.74
Wenzhen Huang300.34
Shuai Jia4265.14