Title :
Controllability and fraction of leaders in infinite networks
Author :
Enyioha, C. ; Rahimian, M.A. ; Pappas, G.J. ; Jadbabaie, A.
Author_Institution :
Dept. of Electr. & Syst. Eng., Univ. of Pennsylvania, Philadelphia, PA, USA
Abstract :
In this paper, we study controllability of a network of linear single-integrator agents when the network size goes to infinity. We first investigate the effect of increasing size by injecting an input at every node and requiring that network controllability Gramian remain well-conditioned with the increasing dimension. We provide theoretical justification to the intuition that high degree nodes pose a challenge to network controllability. In particular, the controllability Gramian for the networks with bounded maximum degrees is shown to remain well-conditioned even as the network size goes to infinity. In the canonical cases of star, chain and ring networks, we also provide closed-form expressions which bound the condition number of the controllability Gramian in terms of the network size. We next consider the effect of the choice and number of leader nodes by actuating only a subset of nodes and considering the least eigenvalue of the Gramian as the network size increases. Accordingly, while a directed star topology can never be made controllable for all sizes by injecting an input just at a fraction f <; 1 of nodes; for path or cycle networks, the designer can actuate a non-zero fraction of nodes and spread them throughout the network in such way that the least eigenvalue of the Gramians remain bounded away from zero with the increasing size. The results offer interesting insights on the challenges of control in large networks and with high-degree nodes.
Keywords :
controllability; eigenvalues and eigenfunctions; multi-robot systems; network theory (graphs); Gramian eigenvalue; bounded maximum degrees; chain network; cycle network; high degree nodes; infinite networks; leader fraction; leader nodes; linear single-integrator agent network; network controllability Gramian; path network; ring network; star network; Controllability; Eigenvalues and eigenfunctions; Network topology; Structural rings; Symmetric matrices; Topology; Upper bound;
Conference_Titel :
Decision and Control (CDC), 2014 IEEE 53rd Annual Conference on
Conference_Location :
Los Angeles, CA
Print_ISBN :
978-1-4799-7746-8
DOI :
10.1109/CDC.2014.7039571