Consensus Tracking of Multi-Agent Systems in Presence of Uncertain Dynamics and Communications Faults
In this paper, the problem of consensus tracking of uncertain multi-agent systems (MAS) with communication faults is addressed. The communication is assumed to be undirected. A reinforced unscented Kalman filter (RUKF) is employed to adapt the noise covariance matrices and to estimate the uncertain...
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| Format: | Article |
| Language: | English |
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IEEE
2023-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/10265009/ |
| _version_ | 1797635451891220480 |
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| author | Kaustav Jyoti Borah Krishna Dev Kumar |
| author_facet | Kaustav Jyoti Borah Krishna Dev Kumar |
| author_sort | Kaustav Jyoti Borah |
| collection | DOAJ |
| description | In this paper, the problem of consensus tracking of uncertain multi-agent systems (MAS) with communication faults is addressed. The communication is assumed to be undirected. A reinforced unscented Kalman filter (RUKF) is employed to adapt the noise covariance matrices and to estimate the uncertain states of MAS as well as to train neural network internal parameters by providing a set of prior measurements. A Chebyshev neural network (CNN) is incorporated to learn the uncertain plant. To avert the neural network approximation errors a hyperbolic tangent function based robust control term is applied. The stability of the RUKF which is running simultaneously with the robust control term has been proven using Lyapunov stability approach. Numerical simulations are presented under different fault conditions to show the effectiveness of the proposed RUKF with 5% less computation power compared to adaptive unscented Kalman filter (AUKF). |
| first_indexed | 2024-03-11T12:21:11Z |
| format | Article |
| id | doaj.art-d8449298f0b54079b29afe952e3fb8df |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-03-11T12:21:11Z |
| publishDate | 2023-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-d8449298f0b54079b29afe952e3fb8df2023-11-07T00:01:31ZengIEEEIEEE Access2169-35362023-01-011112030412031810.1109/ACCESS.2023.332006310265009Consensus Tracking of Multi-Agent Systems in Presence of Uncertain Dynamics and Communications FaultsKaustav Jyoti Borah0https://orcid.org/0000-0001-6195-1908Krishna Dev Kumar1Department of Aerospace Engineering, Toronto Metropolitan University, Toronto, CanadaDepartment of Aerospace Engineering, Toronto Metropolitan University, Toronto, CanadaIn this paper, the problem of consensus tracking of uncertain multi-agent systems (MAS) with communication faults is addressed. The communication is assumed to be undirected. A reinforced unscented Kalman filter (RUKF) is employed to adapt the noise covariance matrices and to estimate the uncertain states of MAS as well as to train neural network internal parameters by providing a set of prior measurements. A Chebyshev neural network (CNN) is incorporated to learn the uncertain plant. To avert the neural network approximation errors a hyperbolic tangent function based robust control term is applied. The stability of the RUKF which is running simultaneously with the robust control term has been proven using Lyapunov stability approach. Numerical simulations are presented under different fault conditions to show the effectiveness of the proposed RUKF with 5% less computation power compared to adaptive unscented Kalman filter (AUKF).https://ieeexplore.ieee.org/document/10265009/Multi-agent systemsuncertain dynamicsreinforcement learning and non-linear filteringChebyshev neural networkscontrolcommunication faults |
| spellingShingle | Kaustav Jyoti Borah Krishna Dev Kumar Consensus Tracking of Multi-Agent Systems in Presence of Uncertain Dynamics and Communications Faults IEEE Access Multi-agent systems uncertain dynamics reinforcement learning and non-linear filtering Chebyshev neural networks control communication faults |
| title | Consensus Tracking of Multi-Agent Systems in Presence of Uncertain Dynamics and Communications Faults |
| title_full | Consensus Tracking of Multi-Agent Systems in Presence of Uncertain Dynamics and Communications Faults |
| title_fullStr | Consensus Tracking of Multi-Agent Systems in Presence of Uncertain Dynamics and Communications Faults |
| title_full_unstemmed | Consensus Tracking of Multi-Agent Systems in Presence of Uncertain Dynamics and Communications Faults |
| title_short | Consensus Tracking of Multi-Agent Systems in Presence of Uncertain Dynamics and Communications Faults |
| title_sort | consensus tracking of multi agent systems in presence of uncertain dynamics and communications faults |
| topic | Multi-agent systems uncertain dynamics reinforcement learning and non-linear filtering Chebyshev neural networks control communication faults |
| url | https://ieeexplore.ieee.org/document/10265009/ |
| work_keys_str_mv | AT kaustavjyotiborah consensustrackingofmultiagentsystemsinpresenceofuncertaindynamicsandcommunicationsfaults AT krishnadevkumar consensustrackingofmultiagentsystemsinpresenceofuncertaindynamicsandcommunicationsfaults |