TY - JOUR
T1 - Tutorial on Dynamic Average Consensus
T2 - The Problem, Its Applications, and the Algorithms
AU - Kia, Solmaz S.
AU - Van Scoy, Bryan
AU - Cortes, Jorge
AU - Freeman, Randy A.
AU - Lynch, Kevin M.
AU - Martinez, Sonia
N1 - Funding Information:
The work of S.S. Kia was supported by National Science Foundation awards ECCS-1653838 and IIS-SAS-1724331.
Funding Information:
The work of J. Cortés was supported by NSF award CNS-1446891 and Air Force Office of Scientific Research award FA9550-15-1-0108. The work of S. Martinez was supported by the Air Force Office of Scientific Research award FA9550-18-1-0158 and Defense Advanced Research Projects Agency (Lagrange) award N66001-18-2-4027.
Publisher Copyright:
© 1991-2012 IEEE.
PY - 2019/6
Y1 - 2019/6
N2 - Technological advances in ad hoc networking and the availability of low-cost reliable computing, data storage, and sensing devices have made scenarios possible where the coordination of many subsystems extends the range of human capabilities. Smart grid operations, smart transportation, smart health care, and sensing networks for environmental monitoring and exploration in hazardous situations are just a few examples of such network operations. In these applications, the ability of a network system to (in a decentralized fashion) fuse information, compute common estimates of unknown quantities, and agree on a common view of the world is critical. These problems can be formulated as agreement problems on linear combinations of dynamically changing reference signals or local parameters. This dynamic agreement problem corresponds to dynamic average consensus, which, as discussed in "Summary," is the problem of interest of this article. The dynamic average consensus problem is for a group of agents to cooperate to track the average of locally available time-varying reference signals, where each agent is capable only of local computations and communicating with local neighbors.
AB - Technological advances in ad hoc networking and the availability of low-cost reliable computing, data storage, and sensing devices have made scenarios possible where the coordination of many subsystems extends the range of human capabilities. Smart grid operations, smart transportation, smart health care, and sensing networks for environmental monitoring and exploration in hazardous situations are just a few examples of such network operations. In these applications, the ability of a network system to (in a decentralized fashion) fuse information, compute common estimates of unknown quantities, and agree on a common view of the world is critical. These problems can be formulated as agreement problems on linear combinations of dynamically changing reference signals or local parameters. This dynamic agreement problem corresponds to dynamic average consensus, which, as discussed in "Summary," is the problem of interest of this article. The dynamic average consensus problem is for a group of agents to cooperate to track the average of locally available time-varying reference signals, where each agent is capable only of local computations and communicating with local neighbors.
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U2 - 10.1109/MCS.2019.2900783
DO - 10.1109/MCS.2019.2900783
M3 - Article
AN - SCOPUS:85065960791
SN - 1066-033X
VL - 39
SP - 40
EP - 72
JO - IEEE Control Systems
JF - IEEE Control Systems
IS - 3
M1 - 8716798
ER -