A Hyperparameter-Based Approach for Consensus Under Uncertainties
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Author(s)
Fraser, Cameron S.
Bertuccelli, Luca F.
Choi, Han-Lim
How, Jonathan P.
Date Issued
July 2010
Journal
Proceedings of the American Control Conference, 2010
Publisher
Institute of Electrical and Electronics Engineers
Citation
Fraser, C.S.R. et al. “A hyperparameter-based approach for consensus under uncertainties.” American Control Conference (ACC), 2010. 2010. 3192-3197. ©2010 IEEE.
Version
Final published version
Abstract
This paper addresses the problem of information consensus in a team of networked agents with uncertain local estimates described by parameterized distributions in the exponential family. In particular, the method utilizes the concepts of pseudo-measurements and conjugacy of probability distributions to achieve a steady-state estimate consistent with a Bayesian fusion of each agent's local knowledge, without requiring complex channel filters or being limited to normally distributed uncertainties. It is shown that this algorithm, termed hyperparameter consensus, is adaptable to any local uncertainty distribution in the exponential family, and will converge to a Bayesian fusion of local estimates over arbitrary communication networks so long as they are known and strongly connected.
MIT Department
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
Massachusetts Institute of Technology. Humans and Automation Lab
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Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
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DOI of Published Version
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5530789&isnumber=5530425
