Algorithm for Identifying Minimum Driver Nodes Based on Structural Controllability-Reference-Cited by-同舟云学术

Algorithm for Identifying Minimum Driver Nodes Based on Structural Controllability

Published:2015 Issue: Volume:2015 Page:1-9
ISSN:1024-123X
Container-title:Mathematical Problems in Engineering
language:en
Short-container-title:Mathematical Problems in Engineering

Author:

Haghighi Reza¹,Namazi HamidReza²

Affiliation:

1. Department of Electrical and Computer Engineering, National University of Singapore, Singapore 119077

2. Department of Mechanical Engineering, Faculty of Engineering, Universiti Malaysia Sarawak, 94300 Kuching, Malaysia

Abstract

Existing methods on structural controllability of networked systems are based on critical assumptions such as nodal dynamics with infinite time constants and availability of input signals to all nodes. In this paper, we relax these assumptions and examine the structural controllability for practical model of networked systems. We explore the relationship between structural controllability and graph reachability. Consequently, a simple graph-based algorithm is presented to obtain the minimum driver nodes. Finally, simulation results are presented to illustrate the performance of the proposed algorithm in dealing with large-scale networked systems.

Publisher

Hindawi Limited

Subject

General Engineering,General Mathematics

Link

http://downloads.hindawi.com/journals/mpe/2015/192307.pdf

Reference30 articles.

1. Maintaining Limited-Range Connectivity Among Second-Order Agents

2. Controllability of a Leader–Follower Dynamic Network With Switching Topology

3. Controllability of switching networks of multi-agent systems

4. Interconnection topologies for multi-agent coordination under leader–follower framework

5. Leader-following consensus problem with a varying-velocity leader and time-varying delays

Cited by 7 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Learning versus optimal intervention in random Boolean networks;Applied Network Science;2019-12

2. Analysis of a Network’s Emerging Behaviour via Its Structure Involving Its Strongly Connected Components;Network-Oriented Modeling for Adaptive Networks: Designing Higher-Order Adaptive Biological, Mental and Social Network Models;2019-11-02

3. Analysis of a network’s asymptotic behavior via its structure involving its strongly connected components;Network Science;2019-10-01

4. Deducing complete selection rule set for driver nodes to guarantee network structural controllability;IEEE/CAA Journal of Automatica Sinica;2019-09

5. Optimal Control Rules for Random Boolean Networks;Studies in Computational Intelligence;2018-12-02