Adaptive dynamic programming optimal tracking control of multi-UAVs based on zero-sum game
This paper investigates an adaptive dynamic programming (ADP) optimal tracking control algorithm for multi-UAV systems based on zero-sum game theory, addressing external disturbances during flight. By formulating the bounded [Formula: see text] gain problem as a two-person zero-sum game between cont...
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2025-07-01
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| Series: | Automatika |
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| Online Access: | https://www.tandfonline.com/doi/10.1080/00051144.2025.2497616 |
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| author | Shuaibin Guan Xingjian Fu |
| author_facet | Shuaibin Guan Xingjian Fu |
| author_sort | Shuaibin Guan |
| collection | DOAJ |
| description | This paper investigates an adaptive dynamic programming (ADP) optimal tracking control algorithm for multi-UAV systems based on zero-sum game theory, addressing external disturbances during flight. By formulating the bounded [Formula: see text] gain problem as a two-person zero-sum game between control strategies and external disturbances, the Hamilton-Jacobi-Isaacs (HJI) equation is constructed to derive the Nash equilibrium solution. To overcome the computational challenges of solving the HJI equation, a three-layer neural network structure comprising evaluation, execution, and disturbance networks is employed, integrated with the ADP algorithm to approximate the value function and optimize the control strategy iteratively. Comprehensive simulations demonstrate the proposed method's superior trajectory tracking performance and robustness compared to Sliding Mode Control (SMC). The results confirm the effectiveness of the ADP-based approach in achieving real-time, adaptive control in complex and dynamic multi-UAV environments. |
| format | Article |
| id | doaj-art-7c099400bb254ccca045c4126ab62b87 |
| institution | Kabale University |
| issn | 0005-1144 1848-3380 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Automatika |
| spelling | doaj-art-7c099400bb254ccca045c4126ab62b872025-08-20T03:33:11ZengTaylor & Francis GroupAutomatika0005-11441848-33802025-07-0166349150210.1080/00051144.2025.2497616Adaptive dynamic programming optimal tracking control of multi-UAVs based on zero-sum gameShuaibin Guan0Xingjian Fu1School of Automation, Beijing Information Science and Technology University, Beijing, People's Republic of ChinaSchool of Automation, Beijing Information Science and Technology University, Beijing, People's Republic of ChinaThis paper investigates an adaptive dynamic programming (ADP) optimal tracking control algorithm for multi-UAV systems based on zero-sum game theory, addressing external disturbances during flight. By formulating the bounded [Formula: see text] gain problem as a two-person zero-sum game between control strategies and external disturbances, the Hamilton-Jacobi-Isaacs (HJI) equation is constructed to derive the Nash equilibrium solution. To overcome the computational challenges of solving the HJI equation, a three-layer neural network structure comprising evaluation, execution, and disturbance networks is employed, integrated with the ADP algorithm to approximate the value function and optimize the control strategy iteratively. Comprehensive simulations demonstrate the proposed method's superior trajectory tracking performance and robustness compared to Sliding Mode Control (SMC). The results confirm the effectiveness of the ADP-based approach in achieving real-time, adaptive control in complex and dynamic multi-UAV environments.https://www.tandfonline.com/doi/10.1080/00051144.2025.2497616Multi-UAVszero-sum gameadaptive dynamic programmingneural networks |
| spellingShingle | Shuaibin Guan Xingjian Fu Adaptive dynamic programming optimal tracking control of multi-UAVs based on zero-sum game Automatika Multi-UAVs zero-sum game adaptive dynamic programming neural networks |
| title | Adaptive dynamic programming optimal tracking control of multi-UAVs based on zero-sum game |
| title_full | Adaptive dynamic programming optimal tracking control of multi-UAVs based on zero-sum game |
| title_fullStr | Adaptive dynamic programming optimal tracking control of multi-UAVs based on zero-sum game |
| title_full_unstemmed | Adaptive dynamic programming optimal tracking control of multi-UAVs based on zero-sum game |
| title_short | Adaptive dynamic programming optimal tracking control of multi-UAVs based on zero-sum game |
| title_sort | adaptive dynamic programming optimal tracking control of multi uavs based on zero sum game |
| topic | Multi-UAVs zero-sum game adaptive dynamic programming neural networks |
| url | https://www.tandfonline.com/doi/10.1080/00051144.2025.2497616 |
| work_keys_str_mv | AT shuaibinguan adaptivedynamicprogrammingoptimaltrackingcontrolofmultiuavsbasedonzerosumgame AT xingjianfu adaptivedynamicprogrammingoptimaltrackingcontrolofmultiuavsbasedonzerosumgame |