Robust Trajectory Planning for Hypersonic Glide Vehicle with Parametric Uncertainties

Dong, Chunyun; Guo, Zhi; Chen, Xiaolong

doi:10.1155/2021/3676810

Cited by 5 publications

(2 citation statements)

References 37 publications

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“…However, the literature [9][10][11][12][13][14] highlights that the shape-changing process of morphing flight vehicles alters the aerodynamic characteristics and attitude control response, which affects the flight dynamics process. This change increases the control requirements and introduces additional constraints.…”

Section: Introductionmentioning

confidence: 99%

An Intelligent Autonomous Morphing Decision Approach for Hypersonic Boost-Glide Vehicles Based on DNNs

Hou,

Liu,

Yang

et al. 2023

Aerospace

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In addressing the morphing problem in vehicle flight, some scholars have primarily employed reinforcement learning methods to make morphing decisions based on task. However, they have not considered the constraints associated with the task process. The innovation of this article is that it proposes an intelligent morphing decision method based on deep neural networks (DNNs) for the autonomous morphing decision problem of hypersonic boost-glide morphing vehicles under process constraints. Firstly, we established a dynamic model of a hypersonic boost-glide morphing vehicle with a continuously variable sweep angle. Then, in order to address the decision optimality problem considering errors and the heat flux density constraint problem during the gliding process, interference was introduced to the datum trajectory in segments. Subsequently, re-optimization was performed to generate a trajectory sample library, which was used to train an intelligent decision-maker using a DNN. The simulation results demonstrated that, compared with the conventional programmatic morphing approach, the intelligent morphing decision maker could dynamically determine the sweep angle based on the current flight state, leading to improved range while still adhering to the heat flux density constraint. This validates the effectiveness and robustness of the proposed intelligent decision-maker.

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Section: Introductionmentioning

confidence: 99%

An Intelligent Autonomous Morphing Decision Approach for Hypersonic Boost-Glide Vehicles Based on DNNs

Hou,

Liu,

Yang

et al. 2023

Aerospace

View full text Add to dashboard Cite

show abstract

“…Considering the need to generate trajectories quickly in some tasks, we proposed an algorithm based on geometric stitching. 9 As an application of heuristics algorithm, particle swarm optimization 10 and gravitational search algorithm 11 can also give appropriate solutions. Furthermore, with the development of machine learning, deep neural networks have been used in HGV's trajectory planning.…”

Section: Introductionmentioning

confidence: 99%

Air-breathing hypersonic vehicle trajectory optimization with uncertain no-fly zones

Tian

Shen

2022

Advances in Mechanical Engineering

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The air-breathing hypersonic planes are considered to be the future of commercial airlines, which can fly from NYC to London in under an hour. For air-breathing vehicles, 3D trajectory planning will become extremely important due to its significant impact on flight performance. Past research on this issue was not comprehensive enough. Thus, we proposed a hybrid method for generating the optimal trajectories efficiently. No-fly zones are specified for geopolitical restrictions in air-breathing hypersonic vehicle missions. However, previous studies focused on no-fly zone constraints with fixed locations and boundaries. For robust execution, we must take into account no-fly zones’ uncertainties, which arise due to uncertain localization, measurement errors, and no-fly zones’ movement. A chance-constrained approach is presented here to deal with such uncertainties. The key idea of this method is controlling risk when the flight path is close to the uncertain no-fly zones. First, the trajectory planning of air-breathing hypersonic vehicles is modeled as a chance-constrained optimization (CCOPT) problem. With the help of the convexification and linearization techniques, we can approximate the non 3.2.2 CCOPT problem as a convex second-order cone programing under the Gaussian distribution assumption. It can be solved to global optimality by the interior point method. Finally, we give numerical simulation results to prove the effectiveness of this method.

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Correlation between waverider shock waves and aerodynamic forces in supersonic rarefied flow, experimental investigation in the wind tunnel MARHy

Hugo

Lago

2022

Acta Astronautica

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Robust Trajectory Planning for Hypersonic Glide Vehicle with Parametric Uncertainties

Cited by 5 publications

References 37 publications

An Intelligent Autonomous Morphing Decision Approach for Hypersonic Boost-Glide Vehicles Based on DNNs

An Intelligent Autonomous Morphing Decision Approach for Hypersonic Boost-Glide Vehicles Based on DNNs

Air-breathing hypersonic vehicle trajectory optimization with uncertain no-fly zones

Correlation between waverider shock waves and aerodynamic forces in supersonic rarefied flow, experimental investigation in the wind tunnel MARHy

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