DocumentCode :
794207
Title :
On maximizing the second smallest eigenvalue of a state-dependent graph Laplacian
Author :
Kim, Yoonsoo ; Mesbahi, Mehran
Author_Institution :
Dept. of Eng., Univ. of Leicester, Leiceister, UK
Volume :
51
Issue :
1
fYear :
2006
Firstpage :
116
Lastpage :
120
Abstract :
We consider the set G consisting of graphs of fixed order and weighted edges. The vertex set of graphs in G will correspond to point masses and the weight for an edge between two vertices is a functional of the distance between them. We pose the problem of finding the best vertex positional configuration in the presence of an additional proximity constraint, in the sense that, the second smallest eigenvalue of the corresponding graph Laplacian is maximized. In many recent applications of algebraic graph theory in systems and control, the second smallest eigenvalue of Laplacian has emerged as a critical parameter that influences the stability and robustness properties of dynamic systems that operate over an information network. Our motivation in the present work is to "assign" this Laplacian eigenvalue when relative positions of various elements dictate the interconnection of the underlying weighted graph. In this venue, one would then be able to "synthesize" information graphs that have desirable system theoretic properties.
Keywords :
eigenvalues and eigenfunctions; graph theory; stability; time-varying systems; Laplacian eigenvalue; additional proximity constraint; algebraic graph theory; dynamic system stability; graphs vertex set; state-dependent graph Laplacian; Constraint theory; Control systems; Dynamic programming; Eigenvalues and eigenfunctions; Graph theory; Laplace equations; Robust control; Robust stability; Wireless networks; Euclidean distance matrix; graph Laplacian; networked dynamic systems; semidefinite programming;
fLanguage :
English
Journal_Title :
Automatic Control, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9286
Type :
jour
DOI :
10.1109/TAC.2005.861710
Filename :
1576862
Link To Document :
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