Rapid Planning of Longitudinal-lateral Comprehensive Control Reentry Gliding Trajectory Considering Time Constraints

doi:10.12382/bgxb.2024.0154

Abstract

Abstract:

A rapid longitudinal-lateral comprehensive control trajectory planning method is proposed for the trajectory planning of reentry gliding vehicles under flight time constraints,which is based on the analytical prediction-correction of drag acceleration profile and the iteration of banked reversal points.In this method,the gliding trajectory planning issue is divided into longitudinal and lateral trajectory planning.In the longitudinal trajectory planning,a single-parameter drag acceleration profile corresponding to the flight time is designed.Furthermore,the profile parameter is corrected based on the time-of-flight analytical prediction,so as to complete the design of the reference drag acceleration profile to meet the terminal altitude,velocity and time-of-flight constraints simultaneously.In the lateral planning,a lateral planning method based on the iteration of the double bank reversal points is designed by analyzing the trajectory length and terminal position control mechanism.The longitude and latitude of target point are introduced to iteratively solve the bank reversal times,which can realize the effective control of the flight time by adjusting the trajectory length while satisfying the terminal position constraints.On this basis,a trajectory iterative correction strategy based on time error is introduced to complete the generation of a time-controllable high-precision three-degree-of-freedom reentry trajectory.Finally,CAV-H reentry gliding is simulated as an example to verify the effectiveness,rapidity and adaptability of the proposed method.Compared with the existing time-controllable reentry trajectory planning methods,the proposed method can comprehensively exert the longitudinal and lateral time control ability in the same computational efficiency and accuracy.Moreover,it boasts a wider range of time adjustability and minimizes the number of bank reversal instances.Additionally,it enables the rapid prediction of the time-adjustable range and the boundaries of reachable domain.

Key words: reentry trajectory planning, time constraint, longitudinal-lateral comprehensive control, analytical profile prediction correction, spatiotemporal boundary rapid prediction

NAN Wenjiang, YAN Xunliang, YANG Yuxuan, WANG Peichen. Rapid Planning of Longitudinal-lateral Comprehensive Control Reentry Gliding Trajectory Considering Time Constraints[J]. Acta Armamentarii, 2025, 46(3): 240154-.

Figures/Tables 15

Fig.1 Schematic diagram of drag acceleration profile

Fig.2 The ground trajectory corresponding to two bank reversals

Fig.3 Flowchart of 3-DOF trajectory generation algorithm

Fig.4 Trajectory length and flight time adjustable range

Fig.5 Reachable area at a given flight time

Fig.6 Length and time adjustable range for fixed target point

Table 1 Comparison of the proportions of adjustable time range in different methods

时间调控方法	时间可调范围占比/%
本文方法	15.4
文献[7]方法	13.5
文献[10]方法	8.5
文献[14]方法	5.8
文献[15]方法	5.4
文献[16]方法	5.0

Table 2 Simulation conditions for trajectory planning algorithm

算例	λ₀/ (°)	σ₀/ (°)	$λ f *$ / (°)	$ϕ f *$ / (°)	$t f *$ /s
1	0	50	50	10	1190
2	0	50	50	10	1390
3	3	60	45	45	1410
4	0	50	50	40	1520

Table 2 Simulation conditions for trajectory planning algorithm

算例	λ₀/ (°)	σ₀/ (°)	$λ f *$ / (°)	$ϕ f *$ / (°)	$t f *$ /s
1	0	50	50	10	1190
2	0	50	50	10	1390
3	3	60	45	45	1410
4	0	50	50	40	1520

Table 3 Terminal errors corresponding to different simulation conditions

算法性能参数	算例1	算例2	算例3	算例4
Δh_f/m	0.7921	0.7922	0.7923	0.8062
Δv_f/(m·s^-1)	0.1778	0.1712	0.1839	0.1721
Δs/m	254.88	142.83	454.27	318.71
Δt_f/s	0.1681	0.1382	0.1329	0.1187
计算耗时/s	1.52	1.56	1.57	1.63

Fig.7 Simulation results of multi-task trajectory planning

Table 4 Perturbation settings of initial state and aerodynamic parameters

不确定参数	3σ	不确定参数	3σ
h₀/km	3	σ₀/(°)	0.5
λ₀/(°)	0.5°	ρ/%	10
ϕ₀/(°)	0.5°	C_L/%	10
v₀/(m·s^-1)	100	C_D/%	10
θ₀/(°)	0.5°

Table 5 Terminal errors of Monte Carlo simulation

终端参数	Δh_f/m	Δv_f/(m·s^-1)	Δs/m	Δt_f/s
平均值	0.7946	0.1797	284.48	0.0027
标准差	0.0153	0.0084	114.51	0.0633

Fig.8 Monte Carlo simulated results

Table 6 Comparison of simulated results for different trajectory planning methods

算法性能参数	本文方法	文献[14]方法
Δh_f/m	0.8062	3.201
Δv_f/(m·s^-1)	0.1721	0.2960
Δs/m	318.71	403.90
Δt_f/s	0.1187	0.1371
轨迹迭代次数	3	5
计算耗时/s	1.63	1.28

Fig.9 Simulated results for different trajectory planning methods under the same reentry mission

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