A Cooperative Fault Detection Approach for Stochastic Multi-Agent Systems Using Maximum Likelihood Estimation Method

This study addresses the fault detection problem in multi-agent systems (MASs) with additive faults and stochastic uncertainties. The main focus is on enhancing the fault detection capability of each agent through a cooperative fault detection scheme, fostering cooperation between agents in two scen...

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Bibliographic Details
Published in:Journal of systems science and complexity Vol. 37; no. 6; pp. 2451 - 2465
Main Authors: Yang, Chen, Li, Yan, Chen, Qijun
Format: Journal Article
Language:English
Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.12.2024
Springer Nature B.V
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ISSN:1009-6124, 1559-7067
Online Access:Get full text
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Summary:This study addresses the fault detection problem in multi-agent systems (MASs) with additive faults and stochastic uncertainties. The main focus is on enhancing the fault detection capability of each agent through a cooperative fault detection scheme, fostering cooperation between agents in two scenarios. For Gaussian uncertainties, one scheme is developed using the maximum likelihood estimation (MLE) matching expectation maximization (EM) algorithm. Additionally, a novel cooperative fault detection scheme is introduced to handle non-Gaussian uncertainties, where the cooperation mechanism among agents is determined by approximating non-Gaussian uncertainties using the Gaussian mixture model (GMM). The effectiveness and improvements of the proposed cooperative fault detection method are validated through numerical simulations.
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ISSN:1009-6124
1559-7067
DOI:10.1007/s11424-024-3293-y