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Systems & Control Letters
Article . 2017 . Peer-reviewed
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Article . 2017
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https://dx.doi.org/10.48550/ar...
Article . 2015
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Article . 2017
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Modeling of physical network systems

Authors: Arjan van der Schaft;

Modeling of physical network systems

Abstract

Conservation laws and balance equations for physical network systems typically can be described with the aid of the incidence matrix of a directed graph, and an associated symmetric Laplacian matrix. Some basic examples are discussed, and the extension to $k$-complexes is indicated. Physical distribution networks often involve a non-symmetric Laplacian matrix. It is shown how, in case the connected components of the graph are strongly connected, such systems can be converted into a form with balanced Laplacian matrix by constructive use of Kirchhoff's Matrix Tree theorem, giving rise to a port-Hamiltonian description. Application to the dual case of asymmetric consensus algorithms is given. Finally it is shown how the minimal storage function for physical network systems with controlled flows can be explicitly computed.

20 pages

Country
Netherlands
Related Organizations
Keywords

Transformations, Available storage, Physical network, Directed graphs (digraphs), tournaments, Decentralized systems, GRAPHS, Applications of graph theory to circuits and networks, FOS: Mathematics, DISSIPATIVE DYNAMICAL-SYSTEMS, HAMILTONIAN-FORMULATION, Mathematics - Optimization and Control, port-Hamiltonian system, COMPLEX, Matrix Tree theorem, matrix tree theorem, Port-Hamiltonian system, physical network, available storage, PORTS, Optimization and Control (math.OC), CHEMICAL-REACTION NETWORKS, Laplacian matrix, Control/observation systems governed by ordinary differential equations

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
19
Top 10%
Top 10%
Top 10%
Green
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