Multitask-constrained reentry trajectory planning for hypersonic gliding vehicle
This paper studies the reentry trajectory planning problems for hypersonic gliding vehicle under multiple tasks. Different from the former achievements, this paper takes into account the practical tasks involved in the reentry phase, including penetration of interceptors, evasion of the no-fly zones...
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| Vydané v: | Aerospace science and technology Ročník 155; s. 109636 |
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| Hlavní autori: | , , , , , |
| Médium: | Journal Article |
| Jazyk: | English |
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Elsevier Masson SAS
01.12.2024
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| ISSN: | 1270-9638 |
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| Abstract | This paper studies the reentry trajectory planning problems for hypersonic gliding vehicle under multiple tasks. Different from the former achievements, this paper takes into account the practical tasks involved in the reentry phase, including penetration of interceptors, evasion of the no-fly zones, and the arrival of the waypoints. Firstly, the constraints during the reentry phase are analyzed in detail, and the original trajectory planning problem is formulated. Secondly, the hp-adaptive pseudospectral discretization method is proposed to effectively reduce the discretization error. Relevant variables are introduced to relax and transform severe intractable constraints of multiple nonconvex forms, thus enhancing the robustness of the planning process. Thirdly, the improved sequential convex programming with decision variables algorithm is proposed to ensure the converged trajectory satisfies complicated tasks. The theoretical analysis is also presented to demonstrate that the converged trajectory is the approximate stationary solution of the discrete form of the original problem. Finally, the effectiveness of the proposed algorithms is validated through numerical simulation.
•Three types of reentry tasks related to the interceptors, the waypoints, and the no-fly zones are considered in this paper.•Exponential function penalty terms and logical variables are introduced to relax the constraints of no-fly zones and waypoints.•The ISCPWDV algorithm is proposed to handle the trajectory planning problem where multiple slack variables coexist. The convergence of the algorithm is also analyzed. |
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| AbstractList | This paper studies the reentry trajectory planning problems for hypersonic gliding vehicle under multiple tasks. Different from the former achievements, this paper takes into account the practical tasks involved in the reentry phase, including penetration of interceptors, evasion of the no-fly zones, and the arrival of the waypoints. Firstly, the constraints during the reentry phase are analyzed in detail, and the original trajectory planning problem is formulated. Secondly, the hp-adaptive pseudospectral discretization method is proposed to effectively reduce the discretization error. Relevant variables are introduced to relax and transform severe intractable constraints of multiple nonconvex forms, thus enhancing the robustness of the planning process. Thirdly, the improved sequential convex programming with decision variables algorithm is proposed to ensure the converged trajectory satisfies complicated tasks. The theoretical analysis is also presented to demonstrate that the converged trajectory is the approximate stationary solution of the discrete form of the original problem. Finally, the effectiveness of the proposed algorithms is validated through numerical simulation.
•Three types of reentry tasks related to the interceptors, the waypoints, and the no-fly zones are considered in this paper.•Exponential function penalty terms and logical variables are introduced to relax the constraints of no-fly zones and waypoints.•The ISCPWDV algorithm is proposed to handle the trajectory planning problem where multiple slack variables coexist. The convergence of the algorithm is also analyzed. |
| ArticleNumber | 109636 |
| Author | Liu, Yumeng Dong, Xiwang Yu, Jianglong Ren, Zhang Huang, Ang Hua, Yongzhao |
| Author_xml | – sequence: 1 givenname: Ang surname: Huang fullname: Huang, Ang email: huangang@buaa.edu.cn organization: Institute of Artificial Intelligence, Beihang University, Beijing, 100191, PR China – sequence: 2 givenname: Jianglong surname: Yu fullname: Yu, Jianglong email: sdjxyjl@buaa.edu.cn organization: School of Automation Science and Electrical Engineering, Beihang University, Beijing, 100191, PR China – sequence: 3 givenname: Yumeng orcidid: 0000-0003-0927-9039 surname: Liu fullname: Liu, Yumeng email: yumeng@iscas.ac.cn organization: Institute of Software, Chinese Academy of Sciences, Beijing, 100190, PR China – sequence: 4 givenname: Yongzhao surname: Hua fullname: Hua, Yongzhao email: yongzhaohua@buaa.edu.cn organization: Institute of Artificial Intelligence, Beihang University, Beijing, 100191, PR China – sequence: 5 givenname: Xiwang surname: Dong fullname: Dong, Xiwang email: xwdong@buaa.edu.cn organization: Institute of Artificial Intelligence, Beihang University, Beijing, 100191, PR China – sequence: 6 givenname: Zhang surname: Ren fullname: Ren, Zhang email: renzhang@buaa.edu.cn organization: School of Automation Science and Electrical Engineering, Beihang University, Beijing, 100191, PR China |
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