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Distributed Robust Fault Estimation Using Relative Measurements for Leader-Follower Multiagent Systems.

Distributed Robust Fault Estimation Using Relative Measurements for Leader-Follower Multiagent... In this article, the problem of distributed robust fault estimation (FE) for leader-follower multiagent systems using relative measurements is considered. A distributed intermediate-based fault estimator is constructed using the local relative measurements and the state estimation from neighbors. The gain matrices of the fault estimator are calculated based on H∞ performance in terms of linear matrix inequality (LMI) to improve the robustness of the estimator. Then, the LMI is separated and simplified by spectral decomposition, and its equivalent condition is proposed based on the maximum and minimum eigenvalue. A distributed eigenvalue estimation algorithm based on the power method is presented to fully distribute the proposed FE scheme. Finally, the numerical simulations are provided to verify the effectiveness of the proposed scheme. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png IEEE transactions on cybernetics Pubmed

Distributed Robust Fault Estimation Using Relative Measurements for Leader-Follower Multiagent Systems.

IEEE transactions on cybernetics , Volume 51 (9): 9 – Sep 16, 2021

Distributed Robust Fault Estimation Using Relative Measurements for Leader-Follower Multiagent Systems.


Abstract

In this article, the problem of distributed robust fault estimation (FE) for leader-follower multiagent systems using relative measurements is considered. A distributed intermediate-based fault estimator is constructed using the local relative measurements and the state estimation from neighbors. The gain matrices of the fault estimator are calculated based on H∞ performance in terms of linear matrix inequality (LMI) to improve the robustness of the estimator. Then, the LMI is separated and simplified by spectral decomposition, and its equivalent condition is proposed based on the maximum and minimum eigenvalue. A distributed eigenvalue estimation algorithm based on the power method is presented to fully distribute the proposed FE scheme. Finally, the numerical simulations are provided to verify the effectiveness of the proposed scheme.

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ISSN
2168-2267
eISSN
2168-2275
DOI
10.1109/TCYB.2019.2943522
pmid
31794408

Abstract

In this article, the problem of distributed robust fault estimation (FE) for leader-follower multiagent systems using relative measurements is considered. A distributed intermediate-based fault estimator is constructed using the local relative measurements and the state estimation from neighbors. The gain matrices of the fault estimator are calculated based on H∞ performance in terms of linear matrix inequality (LMI) to improve the robustness of the estimator. Then, the LMI is separated and simplified by spectral decomposition, and its equivalent condition is proposed based on the maximum and minimum eigenvalue. A distributed eigenvalue estimation algorithm based on the power method is presented to fully distribute the proposed FE scheme. Finally, the numerical simulations are provided to verify the effectiveness of the proposed scheme.

Journal

IEEE transactions on cyberneticsPubmed

Published: Sep 16, 2021

There are no references for this article.