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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| Vydáno v: | Journal of systems science and complexity Ročník 37; číslo 6; s. 2451 - 2465 |
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| Hlavní autoři: | , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
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Berlin/Heidelberg
Springer Berlin Heidelberg
01.12.2024
Springer Nature B.V |
| Témata: | |
| ISSN: | 1009-6124, 1559-7067 |
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| Abstract | 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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| AbstractList | 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. |
| Author | Chen, Qijun Yang, Chen Li, Yan |
| Author_xml | – sequence: 1 givenname: Chen surname: Yang fullname: Yang, Chen organization: School of Electronics and Information Engineering, Tongji University – sequence: 2 givenname: Yan surname: Li fullname: Li, Yan email: liyan_tongji@tongji.edu.cn organization: School of Electronics and Information Engineering, Tongji University – sequence: 3 givenname: Qijun surname: Chen fullname: Chen, Qijun organization: School of Electronics and Information Engineering, Tongji University |
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| Cites_doi | 10.1080/00207721.2021.1995527 10.1109/TCSI.2021.3058216 10.1016/j.automatica.2017.09.002 10.1016/j.jfranklin.2021.02.009 10.1007/s11424-017-6181-x 10.1016/j.jfranklin.2021.01.035 10.1016/j.ins.2021.02.029 10.1016/j.automatica.2020.108898 10.1007/s10462-020-09934-2 10.1109/TAC.2022.3148384 10.1016/j.automatica.2021.109797 10.1109/TCNS.2018.2878500 10.1016/j.jfranklin.2021.01.042 10.1109/TAC.2017.2694556 10.1109/TAC.2022.3184388 10.1016/j.automatica.2015.12.027 10.1016/j.cosrev.2019.08.002 10.1016/j.automatica.2015.01.042 10.1007/s11424-020-8212-2 10.1016/j.isatra.2018.11.017 10.1109/TIE.2017.2786235 10.1109/TAC.2016.2539326 |
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| Keywords | maximum likelihood estimation multi-agent systems Cooperative fault detection |
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| SubjectTerms | Algorithms Complex Systems Control Cooperation Euclidean space Fault detection Kalman filters Mathematics Mathematics and Statistics Mathematics of Computing Maximum likelihood estimation Multiagent systems Operations Research/Decision Theory Probabilistic models Statistics Systems Theory Uncertainty |
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| Title | A Cooperative Fault Detection Approach for Stochastic Multi-Agent Systems Using Maximum Likelihood Estimation Method |
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