Improved predictor-corrector algorithm of reentry gliding vehicle based on adaptive cross-range corridor

被引：0
|
作者：
He Y. [1 ]
Li J. [2 ]
Shao L. [2 ]
Zhou C. [2 ]
Lei H. [2 ]
机构：
[1] Graduate College, Air Force Engineering University, Xi'an
[2] Air and Missile Defense College, Air Force Engineering University, Xi'an
来源：
Xi Tong Gong Cheng Yu Dian Zi Ji Shu/Systems Engineering and Electronics | 2024年 / 46卷 / 02期
关键词：
adaptive cross-range corridor; effective mapping cross range of no-fly zone; predictor-corrector algorithm;
D O I：
10.12305/j.issn.1001-506X.2024.02.33
中图分类号：
学科分类号：
摘要：
In view of the problem of the separation of avoidance logic and guidance logic in predictor-corrector guidance algorithm for reentry gliding vehicle (RGV), a fusion algorithm based on adaptive cross-range corridor is proposed. Firstly, the avoidance logic is dynamically introduced, through the intersection relationship between the lateral motion trajectory of the aircraft and the no-fly zone. At the same time, the effective mapping range of the no-fly zone is proposed to quantify the no-fly zone area that affects the flight path. Finally, the adaptive cross-range corridor is designed to dynamically adjust the corridor boundary, control the overturn of the pitch angle, realizing the integration of the avoidance logic and the lateral guidance logic. Simulation results show that the aircraft can achieve effective guidance for different no-fly zones under the method, with certain robustness to reentry disturbance, and have less times of roll angle turnover while ensuring guidance accuracy than the algorithm designed by the separation of guidance logic and avoidance logic. © 2024 Chinese Institute of Electronics. All rights reserved.
引用
收藏
页码：692 / 702
页数：10
相关论文
共 32 条
  • [1] ZHANG K, XIONG J J, FUTT, Coupled dynamic model of state estimation for hypersonic glide vehicle, Journal of Systems Engineering and Electronics, 29, 6, pp. 1284-1292, (2018)
  • [2] YU X, LIU L II, TANG G J, Et al., A reentry trajectory planning approach satisfying waypoint and no-fly zone constraints [ C], Proc. of the IEEE 5 th International Conference on Recent Advances in Space Technologies, pp. 241-246, (2011)
  • [3] LUO C X, LEI II M, LI J, Et al., A new adaptive neural control scheme for hypersonic vehicle with actuators multiple constraints, Nonlinear Dynamics, 100, 4, pp. 3529-3553, (2020)
  • [4] WANG L, XING II, MAO Y F., Reentry trajectory rapid optimization for hypersonic vehicle satisfying waypoint and no-fly zone constraints [J], Journal of Systems Engineering and Electronics, 26, 6, pp. 1277-1290, (2015)
  • [5] WANG Z, GRANT M J., Constrained trajectory optimization for planetary entry via sequential convex programming, Journal of Guidance Control & Dynamics, 40, 10, pp. 2603-2615, (2017)
  • [6] ZHOU X, ZHANG II B, HE R Z, Et al., A three-dimensional reentry trajectory profile planning method based on convex opti-mization[J], Journal of Aeronautics, 41, 11, pp. 66-82, (2020)
  • [7] ZHOU X, HE R Z, ZHANG II B, Et al., Sequential convex programming method using adaptive mesh refinement for entry tra- jectory planning problem[J], Aerospace Science and Technology, 109, (2020)
  • [8] ZHANG J L, LIU K, FAN Y Z, Et al., A piecewise predictor-corrector reentry guidance algorithm with no-fly zone avoidance[J], Journal of Astronautics, 42, 1, pp. 122-131, (2021)
  • [9] DOU Y L, LIU W, TANG M M, Et al., Robust predictor-corrector guidance with multiple constrains for reusable launch vehi-cles, Systems Engineering and Electronics, 43, 5, pp. 1316-1325, (2021)
  • [10] LI M J, ZHOU C J, SIIAO L, Et al., An improved predictor-corrector guidance algorithm for reentry glide vehicle based on intelligent flight range prediction and adaptive crossrange corri-dor[J], International Journal of Aerospace Engineering, 2022, (2022)
1234