Reaching Non-Negative Edge Consensus of Networked Dynamical Systems

In this paper, the problem of non-negative edge consensus of undirected networked linear time-invariant systems is addressed by associating each edge of the network with a state variable, for which a distributed algorithm is constructed. Sufficient conditions referring only to the number of edges ar...

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Vydáno v:IEEE transactions on cybernetics Ročník 48; číslo 9; s. 2712 - 2722
Hlavní autoři: Xiao Ling Wang, Housheng Su, Chen, Michael Z. Q., Xiao Fan Wang, Guanrong Chen
Médium: Journal Article
Jazyk:angličtina
Vydáno: United States IEEE 01.09.2018
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
Automation
Computer simulation
Distributed algorithm
Economic models
Eigenvalues and eigenfunctions
Feedback
Internet
Laplace equations
line graph
Linear programming
low-gain feedback
networked system
non-negative edge consensus
Roads
State variable
Time invariant systems
Vehicle dynamics
ISSN:2168-2267, 2168-2275, 2168-2275
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Abstract In this paper, the problem of non-negative edge consensus of undirected networked linear time-invariant systems is addressed by associating each edge of the network with a state variable, for which a distributed algorithm is constructed. Sufficient conditions referring only to the number of edges are derived for non-negative edge consensus of the networked systems. Subsequently, the linear programming method and a low-gain feedback technique are introduced to simplify the design of the feedback gain matrix for achieving the non-negative edge consensus. It is found that the low-gain feedback technique has a good effect on the non-negative edge consensus of the networked systems subject to input saturation. Numerical simulations are presented to verify the effectiveness of the theoretical results.
AbstractList In this paper, the problem of non-negative edge consensus of undirected networked linear time-invariant systems is addressed by associating each edge of the network with a state variable, for which a distributed algorithm is constructed. Sufficient conditions referring only to the number of edges are derived for non-negative edge consensus of the networked systems. Subsequently, the linear programming method and a low-gain feedback technique are introduced to simplify the design of the feedback gain matrix for achieving the non-negative edge consensus. It is found that the low-gain feedback technique has a good effect on the non-negative edge consensus of the networked systems subject to input saturation. Numerical simulations are presented to verify the effectiveness of the theoretical results.
In this paper, the problem of non-negative edge consensus of undirected networked linear time-invariant systems is addressed by associating each edge of the network with a state variable, for which a distributed algorithm is constructed. Sufficient conditions referring only to the number of edges are derived for non-negative edge consensus of the networked systems. Subsequently, the linear programming method and a low-gain feedback technique are introduced to simplify the design of the feedback gain matrix for achieving the non-negative edge consensus. It is found that the low-gain feedback technique has a good effect on the non-negative edge consensus of the networked systems subject to input saturation. Numerical simulations are presented to verify the effectiveness of the theoretical results.In this paper, the problem of non-negative edge consensus of undirected networked linear time-invariant systems is addressed by associating each edge of the network with a state variable, for which a distributed algorithm is constructed. Sufficient conditions referring only to the number of edges are derived for non-negative edge consensus of the networked systems. Subsequently, the linear programming method and a low-gain feedback technique are introduced to simplify the design of the feedback gain matrix for achieving the non-negative edge consensus. It is found that the low-gain feedback technique has a good effect on the non-negative edge consensus of the networked systems subject to input saturation. Numerical simulations are presented to verify the effectiveness of the theoretical results.
Author Housheng Su
Guanrong Chen
Chen, Michael Z. Q.
Xiao Fan Wang
Xiao Ling Wang
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SubjectTerms Automation
Computer simulation
Distributed algorithm
Economic models
Eigenvalues and eigenfunctions
Feedback
Internet
Laplace equations
line graph
Linear programming
low-gain feedback
networked system
non-negative edge consensus
Roads
State variable
Time invariant systems
Vehicle dynamics
Title Reaching Non-Negative Edge Consensus of Networked Dynamical Systems
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https://www.ncbi.nlm.nih.gov/pubmed/28922136
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