Hierarchical Online Air Combat Maneuver Decision Making and Control Based on Surrogate-Assisted Differential Evolution Algorithm
One-to-one within-visual-range air combat of unmanned combat aerial vehicles (UCAVs) requires fast, continuous, and accurate decision-making to achieve air combat victory. In order to solve the current problems of insufficient real-time performance of traditional intelligent optimization algorithms...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-01-01
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| Series: | Drones |
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| Online Access: | https://www.mdpi.com/2504-446X/9/2/106 |
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| author | Mulai Tan Haocheng Sun Dali Ding Huan Zhou Tong Han Yuequn Luo |
| author_facet | Mulai Tan Haocheng Sun Dali Ding Huan Zhou Tong Han Yuequn Luo |
| author_sort | Mulai Tan |
| collection | DOAJ |
| description | One-to-one within-visual-range air combat of unmanned combat aerial vehicles (UCAVs) requires fast, continuous, and accurate decision-making to achieve air combat victory. In order to solve the current problems of insufficient real-time performance of traditional intelligent optimization algorithms for solving decision-making problems and the mismatch between the planning trajectory and the actual flight trajectory caused by the difference between the decision-making model and the actual aircraft model, this paper proposes a hierarchical on-line air combat maneuvering decision-making and control framework. Considering the real-time constraints, the maneuver decision problem is transformed into an expensive optimization problem at the decision planning layer. The surrogate-assisted differential evolution algorithm is proposed on the basis of the original differential evolution algorithm, and the planning trajectory is obtained through the 5 degrees of freedom (DOF) model. In the control execution layer, the planning trajectory is tracked through the nonlinear dynamic inverse tracking control method to realize the high-precision control of the 6DOF model. The simulation is carried out under four different initial situation scenarios, including head-on neutral, dominant, parallel neutral, and disadvantaged situations. The Monte Carlo simulation results show that the Surrogate-assisted differential evolution algorithm (SADE) can achieve a win rate of over 53% in all four initial scenarios. The proposed maneuver decision and control framework in this article achieves smooth flight trajectories and stable aircraft control, with each decision average taking 0.08 s, effectively solving the real-time problem of intelligent optimization algorithms in maneuver decision problems. |
| format | Article |
| id | doaj-art-49fa9cd8b1d248e2a1529174d43e96e5 |
| institution | DOAJ |
| issn | 2504-446X |
| language | English |
| publishDate | 2025-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Drones |
| spelling | doaj-art-49fa9cd8b1d248e2a1529174d43e96e52025-08-20T02:44:46ZengMDPI AGDrones2504-446X2025-01-019210610.3390/drones9020106Hierarchical Online Air Combat Maneuver Decision Making and Control Based on Surrogate-Assisted Differential Evolution AlgorithmMulai Tan0Haocheng Sun1Dali Ding2Huan Zhou3Tong Han4Yuequn Luo5Aviation Engineering School, Air Force Engineering University, Xi’an 710038, ChinaSchool of Computer Science, Beijing University of Posts and Telecommunications, Beijing 100876, ChinaAviation Engineering School, Air Force Engineering University, Xi’an 710038, ChinaAviation Engineering School, Air Force Engineering University, Xi’an 710038, ChinaAviation Engineering School, Air Force Engineering University, Xi’an 710038, ChinaAviation Engineering School, Air Force Engineering University, Xi’an 710038, ChinaOne-to-one within-visual-range air combat of unmanned combat aerial vehicles (UCAVs) requires fast, continuous, and accurate decision-making to achieve air combat victory. In order to solve the current problems of insufficient real-time performance of traditional intelligent optimization algorithms for solving decision-making problems and the mismatch between the planning trajectory and the actual flight trajectory caused by the difference between the decision-making model and the actual aircraft model, this paper proposes a hierarchical on-line air combat maneuvering decision-making and control framework. Considering the real-time constraints, the maneuver decision problem is transformed into an expensive optimization problem at the decision planning layer. The surrogate-assisted differential evolution algorithm is proposed on the basis of the original differential evolution algorithm, and the planning trajectory is obtained through the 5 degrees of freedom (DOF) model. In the control execution layer, the planning trajectory is tracked through the nonlinear dynamic inverse tracking control method to realize the high-precision control of the 6DOF model. The simulation is carried out under four different initial situation scenarios, including head-on neutral, dominant, parallel neutral, and disadvantaged situations. The Monte Carlo simulation results show that the Surrogate-assisted differential evolution algorithm (SADE) can achieve a win rate of over 53% in all four initial scenarios. The proposed maneuver decision and control framework in this article achieves smooth flight trajectories and stable aircraft control, with each decision average taking 0.08 s, effectively solving the real-time problem of intelligent optimization algorithms in maneuver decision problems.https://www.mdpi.com/2504-446X/9/2/106air combatunmanned combat aerial vehiclessurrogatedifferential evolutionary algorithmtrajectory tracking |
| spellingShingle | Mulai Tan Haocheng Sun Dali Ding Huan Zhou Tong Han Yuequn Luo Hierarchical Online Air Combat Maneuver Decision Making and Control Based on Surrogate-Assisted Differential Evolution Algorithm Drones air combat unmanned combat aerial vehicles surrogate differential evolutionary algorithm trajectory tracking |
| title | Hierarchical Online Air Combat Maneuver Decision Making and Control Based on Surrogate-Assisted Differential Evolution Algorithm |
| title_full | Hierarchical Online Air Combat Maneuver Decision Making and Control Based on Surrogate-Assisted Differential Evolution Algorithm |
| title_fullStr | Hierarchical Online Air Combat Maneuver Decision Making and Control Based on Surrogate-Assisted Differential Evolution Algorithm |
| title_full_unstemmed | Hierarchical Online Air Combat Maneuver Decision Making and Control Based on Surrogate-Assisted Differential Evolution Algorithm |
| title_short | Hierarchical Online Air Combat Maneuver Decision Making and Control Based on Surrogate-Assisted Differential Evolution Algorithm |
| title_sort | hierarchical online air combat maneuver decision making and control based on surrogate assisted differential evolution algorithm |
| topic | air combat unmanned combat aerial vehicles surrogate differential evolutionary algorithm trajectory tracking |
| url | https://www.mdpi.com/2504-446X/9/2/106 |
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