A robust adaptive estimation algorithm for Hamiltonian multi-agent networks

Giv, H., Khalili, A., Rastegarnia, A. and Sanei, S. ORCID: 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

[img]
Preview
Text
1397265_a1399_Sanei.pdf - Post-print

Download (384kB) | Preview

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
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:
NumberType
10.1109/lcsys.2020.3029332DOI
1397265Other
Divisions: Schools > School of Science and Technology
Record created by: Jonathan Gallacher
Date Added: 05 Jan 2021 13:47
Last Modified: 19 Jan 2021 08:53
URI: http://irep.ntu.ac.uk/id/eprint/41947

Actions (login required)

Edit View Edit View

Views

Views per month over past year

Downloads

Downloads per month over past year