Master stability equations of complex dynamical networks with general topology

Hongfei Sun, David J. Hill

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

7 Citations (Scopus)

Abstract

The master stability equations for a complex dynamical network with general topology are obtained. Compared to prior work, we remove almost all the restrictions on the graph of the network. The coupling configuration matrix is not necessarily diagonalizable, the coupling coefficients are not necessarily nonnegative, and the graph of the network can be directed. These new master stability equations as for those in the previous studies are still very effective in analyzing the stability of complex dynamical networks in terms of synchronization to a manifold. We present some new observations on stability. A new concept heavily connected, which can be regarded as the generalization of both connected for an undirected graph and strong connected for a directed graph, is proposed. The proofs of the two main theorems are very short but can substitute many of those in the literature.

Original languageEnglish
Title of host publicationProceedings of the 17th World Congress, International Federation of Automatic Control, IFAC
PublisherElsevier - International Federation of Automatic Control (IFAC)
Edition1 PART 1
ISBN (Print)9783902661005
DOIs
Publication statusPublished - 2008
Externally publishedYes
EventInternational Federation of Automatic Control World Congress 2008 - Convention and Exhibition Center, Seoul, Korea, South
Duration: 6 Jul 200811 Jul 2008
Conference number: 17th
https://web.archive.org/web/20080609024600/http://www.ifac2008.org/

Publication series

NameIFAC Proceedings Volumes (IFAC-PapersOnline)
Number1 PART 1
Volume17
ISSN (Print)1474-6670

Conference

ConferenceInternational Federation of Automatic Control World Congress 2008
Abbreviated titleIFAC 2008
Country/TerritoryKorea, South
CitySeoul
Period6/07/0811/07/08
Internet address

Keywords

  • Control of networks
  • Cooperative systems
  • Nonlinear systems

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