Algorithms for leader selection in large dynamical networks: Noise-corrupted leaders

Fu Lin, Makan Fardad, Mihailo R. Jovanovic

Research output: Chapter in Book/Report/Conference proceedingConference contribution

46 Scopus citations

Abstract

We examine the leader selection problem in multi-agent dynamical networks where leaders, in addition to relative information from their neighbors, also have access to their own states. We are interested in selecting an a priori specified number of agents as leaders in order to minimize the total variance of the stochastically forced network. Combinatorial nature of this optimal control problem makes computation of the global minimum difficult. We propose a convex relaxation to obtain a lower bound on the global optimal value, and use simple but efficient greedy algorithms to obtain an upper bound. Furthermore, we employ the alternating direction method of multipliers to search for a local minimum. Two examples are provided to illustrate the effectiveness of the developed methods.

Original languageEnglish (US)
Title of host publication2011 50th IEEE Conference on Decision and Control and European Control Conference, CDC-ECC 2011
Pages2932-2937
Number of pages6
DOIs
StatePublished - 2011
Event2011 50th IEEE Conference on Decision and Control and European Control Conference, CDC-ECC 2011 - Orlando, FL, United States
Duration: Dec 12 2011Dec 15 2011

Publication series

NameProceedings of the IEEE Conference on Decision and Control
ISSN (Print)0191-2216

Other

Other2011 50th IEEE Conference on Decision and Control and European Control Conference, CDC-ECC 2011
CountryUnited States
CityOrlando, FL
Period12/12/1112/15/11

Keywords

  • Alternating direction method of multipliers
  • consensus
  • convex optimization/relaxation
  • greedy algorithm
  • leader selection
  • performance bounds
  • variance amplification

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Modeling and Simulation
  • Control and Optimization

Fingerprint Dive into the research topics of 'Algorithms for leader selection in large dynamical networks: Noise-corrupted leaders'. Together they form a unique fingerprint.

Cite this