DocumentCode :
114373
Title :
A graph-theoretic classification for the controllability of the Laplacian leader-follower dynamics
Author :
Aguilar, Cesar O. ; Gharesifard, Bahman
Author_Institution :
Dept. of Math., California State Univ., Bakersfield, CA, USA
fYear :
2014
fDate :
15-17 Dec. 2014
Firstpage :
619
Lastpage :
624
Abstract :
In this paper, we revisit the controllability problem for the Laplacian based leader-follower dynamics with the aim of addressing some fundamental gaps within the existing literature. We introduce a notion of graph controllability classes for Laplacian based leader-follower control systems, namely, the classes of essentially controllable, completely uncontrollable, and conditionally controllable graphs. In addition to the topology of the underlying graph, our controllability classes rely on the richness of the set of control vectors. The particular focus in this paper is on the case where this set is chosen as the set of binary vectors, which captures the case when the control signal is broadcasted by the leader nodes. We first prove that the class of essentially controllable graphs is a strict subset of the class of asymmetric graphs. We provide a non-trivial class of completely uncontrollable asymmetric graphs, namely the class of large block graphs of Steiner triple systems. Several constructive examples demonstrate our results.
Keywords :
controllability; graph theory; pattern classification; vectors; Laplacian based leader-follower control systems; Laplacian leader-follower dynamics; Steiner triple systems; asymmetric graphs; binary vectors; completely uncontrollable graph; conditionally controllable graph; control signal; control vectors; controllability problem; essentially controllable graph; graph controllability classes; graph topology; graph-theoretic classification; Controllability; Eigenvalues and eigenfunctions; Laplace equations; Symmetric matrices; Vectors; Vehicle dynamics;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Decision and Control (CDC), 2014 IEEE 53rd Annual Conference on
Conference_Location :
Los Angeles, CA
Print_ISBN :
978-1-4799-7746-8
Type :
conf
DOI :
10.1109/CDC.2014.7039450
Filename :
7039450
Link To Document :
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