Hierarchical game theoretical distributed adaptive control for large scale multi‐group multi‐agent system
Abstract This paper introduces a distributed adaptive formation control for large‐scale multi‐agent systems (LS‐MAS) that addresses the heavy computational complexity and communication traffic challenges while directly extending conventional distributed control from small scale to large scale. Speci...
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| Format: | Article |
| Language: | English |
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Wiley
2023-11-01
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| Series: | IET Control Theory & Applications |
| Subjects: | |
| Online Access: | https://doi.org/10.1049/cth2.12506 |
| _version_ | 1797626714044497920 |
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| author | Shawon Dey Hao Xu |
| author_facet | Shawon Dey Hao Xu |
| author_sort | Shawon Dey |
| collection | DOAJ |
| description | Abstract This paper introduces a distributed adaptive formation control for large‐scale multi‐agent systems (LS‐MAS) that addresses the heavy computational complexity and communication traffic challenges while directly extending conventional distributed control from small scale to large scale. Specifically, a novel hierarchical game theoretic algorithm is developed to provide a feasible theory foundation for solving LS‐MAS distributed optimal formation problem by effectively integrating the mean‐field game (MFG), the Stackelberg game, and the cooperative game. In particular, LS‐MAS is divided into multiple groups geographically with each having one group leader and a significant amount of followers. Then, a cooperative game is used among multi‐group leaders to formulate distributed inter‐group formation control for leaders. Meanwhile, an MFG is adopted for a large number of intra‐group followers to achieve the collective intra‐group formation while a Stackelberg game is connecting the followers with their corresponding leader within the same group to achieve the overall LS‐MAS multi‐group formation behavior. Moreover, a hybrid actor–critic‐based reinforcement learning algorithm is constructed to learn the solution of the hierarchical game‐based optimal distributed formation control. Finally, to show the effectiveness of the presented schemes, numerical simulations and Lyapunov analysis is performed. |
| first_indexed | 2024-03-11T10:14:07Z |
| format | Article |
| id | doaj.art-ca2d01acb00748cf8aac5d8ce9921c52 |
| institution | Directory Open Access Journal |
| issn | 1751-8644 1751-8652 |
| language | English |
| last_indexed | 2024-03-11T10:14:07Z |
| publishDate | 2023-11-01 |
| publisher | Wiley |
| record_format | Article |
| series | IET Control Theory & Applications |
| spelling | doaj.art-ca2d01acb00748cf8aac5d8ce9921c522023-11-16T11:09:24ZengWileyIET Control Theory & Applications1751-86441751-86522023-11-0117172332235210.1049/cth2.12506Hierarchical game theoretical distributed adaptive control for large scale multi‐group multi‐agent systemShawon Dey0Hao Xu1Electrical and Biomedical Engineering University of Nevada RenoNevadaUSAElectrical and Biomedical Engineering University of Nevada RenoNevadaUSAAbstract This paper introduces a distributed adaptive formation control for large‐scale multi‐agent systems (LS‐MAS) that addresses the heavy computational complexity and communication traffic challenges while directly extending conventional distributed control from small scale to large scale. Specifically, a novel hierarchical game theoretic algorithm is developed to provide a feasible theory foundation for solving LS‐MAS distributed optimal formation problem by effectively integrating the mean‐field game (MFG), the Stackelberg game, and the cooperative game. In particular, LS‐MAS is divided into multiple groups geographically with each having one group leader and a significant amount of followers. Then, a cooperative game is used among multi‐group leaders to formulate distributed inter‐group formation control for leaders. Meanwhile, an MFG is adopted for a large number of intra‐group followers to achieve the collective intra‐group formation while a Stackelberg game is connecting the followers with their corresponding leader within the same group to achieve the overall LS‐MAS multi‐group formation behavior. Moreover, a hybrid actor–critic‐based reinforcement learning algorithm is constructed to learn the solution of the hierarchical game‐based optimal distributed formation control. Finally, to show the effectiveness of the presented schemes, numerical simulations and Lyapunov analysis is performed.https://doi.org/10.1049/cth2.12506Formation controlGame theoryLarge‐scale systemsMulti‐agent systemsNeural netsOptimal control |
| spellingShingle | Shawon Dey Hao Xu Hierarchical game theoretical distributed adaptive control for large scale multi‐group multi‐agent system IET Control Theory & Applications Formation control Game theory Large‐scale systems Multi‐agent systems Neural nets Optimal control |
| title | Hierarchical game theoretical distributed adaptive control for large scale multi‐group multi‐agent system |
| title_full | Hierarchical game theoretical distributed adaptive control for large scale multi‐group multi‐agent system |
| title_fullStr | Hierarchical game theoretical distributed adaptive control for large scale multi‐group multi‐agent system |
| title_full_unstemmed | Hierarchical game theoretical distributed adaptive control for large scale multi‐group multi‐agent system |
| title_short | Hierarchical game theoretical distributed adaptive control for large scale multi‐group multi‐agent system |
| title_sort | hierarchical game theoretical distributed adaptive control for large scale multi group multi agent system |
| topic | Formation control Game theory Large‐scale systems Multi‐agent systems Neural nets Optimal control |
| url | https://doi.org/10.1049/cth2.12506 |
| work_keys_str_mv | AT shawondey hierarchicalgametheoreticaldistributedadaptivecontrolforlargescalemultigroupmultiagentsystem AT haoxu hierarchicalgametheoreticaldistributedadaptivecontrolforlargescalemultigroupmultiagentsystem |