Entry Guidance for Hypersonic Glide Vehicles via Two-Phase hp-Adaptive Sequential Convex Programming

This paper addresses the real-time trajectory generation problem for hypersonic glide vehicles (HGVs) during atmospheric entry, subject to complex constraints including aerothermal limits, actuator bounds, and no-fly zones (NFZs). To achieve efficient and reliable trajectory planning, a two-phase hp...

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Veröffentlicht in:Aerospace Jg. 12; H. 6; S. 539
Hauptverfasser: Liu, Xu, Li, Xiang, Zhang, Houjun, Huang, Hao, Wu, Yonghui
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Basel MDPI AG 01.06.2025
Schlagworte:
Accuracy
Actuators
adaptive mesh refinement
Algorithms
Approximation
Atmospheric entry
Collocation methods
Convex analysis
Convexity
Design and construction
Efficiency
entry guidance
Error reduction
Geometric constraints
Gliding and soaring
Grid refinement (mathematics)
hypersonic glide vehicle
Hypersonic planes
Linear quadratic regulator
Objective function
Optimization
Real time
real-time trajectory optimization
sequential convex programming
Trajectory planning
Vehicles
China
ISSN:2226-4310, 2226-4310
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Zusammenfassung:This paper addresses the real-time trajectory generation problem for hypersonic glide vehicles (HGVs) during atmospheric entry, subject to complex constraints including aerothermal limits, actuator bounds, and no-fly zones (NFZs). To achieve efficient and reliable trajectory planning, a two-phase hp-adaptive sequential convex programming (SCP) framework is proposed. NFZ avoidance is reformulated as a soft objective to enhance feasibility under tight geometric constraints. In Phase I, a shrinking-trust-region strategy progressively tightens the soft trust-region radius by increasing the penalty weight, effectively suppressing linearization errors. A sensitivity-driven mesh refinement method then allocates collocation points based on their contribution to the objective function. Phase II applies residual-based refinement to reduce discretization errors. The resulting reference trajectory is tracked using a linear quadratic regulator (LQR) within a reference-trajectory-tracking guidance (RTTG) architecture. Simulation results demonstrate that the proposed method achieves convergence in only a few iterations, generating high-fidelity trajectories within 2–3 s. Compared to pseudospectral solvers, the method achieves over 12× computational speed-up while maintaining kilometer-level accuracy. Monte Carlo tests under uncertainties confirm a 100% success rate, with all constraints satisfied. These results validate the proposed method’s robustness, efficiency, and suitability for onboard real-time entry guidance in dynamic mission environments.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
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ISSN:2226-4310
2226-4310
DOI:10.3390/aerospace12060539