Analytic Time Reentry Cooperative Guidance for Multi-Hypersonic Glide Vehicles

Aiming at the cooperative guidance problem of multi-hypersonic glide vehicles, a cooperative guidance method based on a parametric design and an analytical solution of time-to-go is proposed. First, the hypersonic reentry trajectory optimization problem was transformed into a parameter optimization...

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Bibliographic Details
Published in:Applied sciences Vol. 13; no. 8; p. 4987
Main Authors: Xu, Hui, Cai, Guangbin, Fan, Yonghua, Wei, Hao, Li, Xin, Wang, Yongchao
Format: Journal Article
Language:English
Published: Basel MDPI AG 01.04.2023
Subjects:
Aircraft
Algorithms
analytic guidance
Convex analysis
Design
Equilibrium
Mathematical optimization
Monte Carlo method
Monte Carlo simulation
multi-hypersonic glide vehicle
Optimization algorithms
parametric design
Parametric statistics
reentry cooperative guidance
Swarm intelligence
Vehicles
Velocity
ISSN:2076-3417, 2076-3417
Online Access:Get full text
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Summary:Aiming at the cooperative guidance problem of multi-hypersonic glide vehicles, a cooperative guidance method based on a parametric design and an analytical solution of time-to-go is proposed. First, the hypersonic reentry trajectory optimization problem was transformed into a parameter optimization problem. The parameters were optimized to determine the angle of attack profile and the time to enter the altitude velocity reentry corridor. Then, using the quasi-equilibrium glide condition, the estimation form of the remaining flight time was analytically derived to satisfy accurately the cooperative time constraint. Using the remaining time-to-go and range-to-go, combined with the heading angle deviation corridor, the bank angle command was further calculated. Finally, the swarm intelligence optimization algorithm was used to optimize the design parameters to obtain the cooperative guidance trajectory satisfying the time constraint. Simulations showed that the analytical time reentry cooperative guidance algorithm proposed in this paper can accurately meet the time constraints and cooperative flight accuracy. Monte Carlo simulation experiments verified that the proposed algorithm demonstrates a robust performance.
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ISSN:2076-3417
2076-3417
DOI:10.3390/app13084987