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Author Simonetto, Andrea ♦ Keviczky, Tamas ♦ Johansson, Mikael
Source IEEE Xplore Digital Library
Content type Text
Publisher Institute of Electrical and Electronics Engineers, Inc. (IEEE)
File Format PDF
Copyright Year ©2012
Language English
Subject Domain (in DDC) Technology ♦ Engineering & allied operations ♦ Other branches of engineering
Subject Keyword Portable document format ♦ IEEE Xplore
Abstract We propose a regularized saddle-point algorithm for convex networked optimization problems with resource allocation constraints. Standard distributed gradient methods suffer from slow convergence and require excessive communication when applied to problems of this type. Our approach offers an alternative way to address these problems, and ensures that each iterative update step satisfies the resource allocation constraints. We derive step-size conditions under which the distributed algorithm converges geometrically to the regularized optimal value, and show how these conditions are affected by the underlying network topology. We illustrate our method on a robotic network application example where a group of mobile agents strive to maintain a moving target in the barycenter of their positions.
Description Author affiliation: Delft Center for Systems and Control, Delft University of Technology, Mekelweg 2, 2628 CD, The Netherlands (Simonetto, Andrea; Keviczky, Tamas) || ACCESS Linnaeus Centre, School of Electrical Engineering, Royal Institute of Technology (KTH), 100 44 Stockholm, Sweden (Johansson, Mikael)
ISBN 9781467320658
ISSN 07431546
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research ♦ Reading
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2012-12-10
Publisher Place USA
Rights Holder Institute of Electrical and Electronics Engineers, Inc. (IEEE)
e-ISBN 9781467320665
Size (in Bytes) 284.28 kB
Page Count 6
Starting Page 7476
Ending Page 7481


Source: IEEE Xplore Digital Library