Giv, H, Khalili, A, Rastegarnia, A and Sanei, S ORCID: https://orcid.org/0000-0002-3437-2801, 2021. A robust adaptive estimation algorithm for Hamiltonian multi-agent networks. IEEE Control Systems Letters, 5 (4), pp. 1243-1248. ISSN 2475-1456
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Abstract
In this letter a robust incremental adaptation algorithm is presented to solve distributed estimation for a Hamiltonian network, where the measurements at each node may be corrupted by heavy-tailed impulsive noise. In the proposed algorithm, each node employs an error-nonlinearity into the update equation to mitigate the detrimental effects of impulsive noise. Moreover, the algorithm estimates both the optimal error non-linearity and the unknown parameter together, which in turn, obviates the requirement of prior knowledge about the statistical characteristics of measurement noise. In addition to algorithm development, its steady-state performance as well as convergence analysis have been provided. Simulation results validate the correctness of the analysis and reveal the superiority of the proposed algorithm over some existing algorithms.
Item Type: | Journal article |
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Publication Title: | IEEE Control Systems Letters |
Creators: | Giv, H., Khalili, A., Rastegarnia, A. and Sanei, S. |
Publisher: | Institute of Electrical and Electronics Engineers |
Date: | October 2021 |
Volume: | 5 |
Number: | 4 |
ISSN: | 2475-1456 |
Identifiers: | Number Type 10.1109/lcsys.2020.3029332 DOI 1397265 Other |
Divisions: | Schools > School of Science and Technology |
Record created by: | Jonathan Gallacher |
Date Added: | 05 Jan 2021 13:47 |
Last Modified: | 31 May 2021 15:07 |
URI: | https://irep.ntu.ac.uk/id/eprint/41947 |
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