Unpowered approach and landing trajectory planning using second-order cone programming

Yan, Xiaodong; He, Lei

doi:10.1016/j.ast.2020.105841

Cited by 16 publications

(11 citation statements)

References 17 publications

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“…Eq. (19) shows that the lateral and longitudinal lift accelerations at and ac are established by nonlinear first-order Markov processes. The term S1 is determined by the vehicle's state and leads to the nonlinearity in the dynamic model of the lift accelerations.…”

Section: ) Components Of the Lift Acceleration Modelmentioning

confidence: 98%

“…In order to establish the dynamic models of the HGV, the earth is assumed as a homogeneous sphere. Considering the rotation of the earth, the three-dimensional point-mass dynamics of the HGV are constructed in a semi-speed coordinate frame (VTC) [19]. It should be indicated that the sideslip angle of the HGV is neglected in all calculations.…”

Section: Dynamic Models Of Hgvsmentioning

confidence: 99%

“…The magnitudes of the drag and lift accelerations (aD and aL) are related to aerodynamic coefficients, reference area, mass and dynamic pressure [19]. These parameters can be mathematically expressed as the following:…”

Section: Dynamic Models Of Hgvsmentioning

confidence: 99%

“…Furthermore, CD and CL are drag and lift coefficients of HGV, respectively. q=ρv 2 /2 is the dynamic pressure and ρ is the atmospheric density, which can be expressed as the exponential function of height, in the form below [19]:…”

Section: Dynamic Models Of Hgvsmentioning

confidence: 99%

“…It is worth noting that the sound velocity cs is a highly nonlinear function [19]. Drag coefficient can be described in the form of the drag pole curve [23]:…”

Section: A Dynamics Of Hgvsmentioning

confidence: 99%

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Aerodynamic Statistics-Based Trajectory Estimation of Hypersonic Maneuvering Target

et al. 2020

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Section: ) Components Of the Lift Acceleration Modelmentioning

confidence: 98%

Section: Dynamic Models Of Hgvsmentioning

confidence: 99%

Section: Dynamic Models Of Hgvsmentioning

confidence: 99%

Section: Dynamic Models Of Hgvsmentioning

confidence: 99%

“…It is worth noting that the sound velocity cs is a highly nonlinear function [19]. Drag coefficient can be described in the form of the drag pole curve [23]:…”

Section: A Dynamics Of Hgvsmentioning

confidence: 99%

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Aerodynamic Statistics-Based Trajectory Estimation of Hypersonic Maneuvering Target

et al. 2020

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Successive Chebyshev pseudospectral convex optimization method for nonlinear optimal control problems

Chen

Yang

2021

Intl J Robust & Nonlinear

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This article aims at proposing a successive Chebyshev pseudospectral convex optimization method for solving general nonlinear optimal control problems (OCPs). First, Chebyshev pseudospectral discrete scheme is used to discretize a general nonlinear OCP. At the same time, a convex subproblem is formulated by using the first‐order Taylor expansion to convexify the discretized nonlinear dynamic constraints. Second, a trust‐region penalty term is added to the performance index of the subproblem, and a successive convex optimization algorithm is proposed to solve the subproblem iteratively. Noted that the trust‐region penalty parameters can be adjusted according to the linearization error in iterative process, which improves convergence rate. Third, the Karush–Kuhn–Tucker conditions of the subproblem are derived, and furthermore, a proof is given to show that the algorithm will iteratively converge to the subproblem. Additionally, the global convergence of the algorithm is analyzed and proved, which is based on three key lemmas. Finally, the orbit transfer problem of spacecraft is used to test the performance of the proposed method. The simulation results demonstrate the optimal control is bang‐bang form, which is consistent with the result of theoretical proof. Also, the algorithm is of efficiency, fast convergence rate, and high accuracy. Therefore, the proposed method provides a new approach for solving nonlinear OCPs online and has great potential in engineering practice.

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Single segment approach and landing guidance and control for an unpowered reusable launch vehicle

Hameed¹,

R²

2021

Aerospace Science and Technology

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Unpowered approach and landing trajectory planning using second-order cone programming

Cited by 16 publications

References 17 publications

Aerodynamic Statistics-Based Trajectory Estimation of Hypersonic Maneuvering Target

Aerodynamic Statistics-Based Trajectory Estimation of Hypersonic Maneuvering Target

Successive Chebyshev pseudospectral convex optimization method for nonlinear optimal control problems

Single segment approach and landing guidance and control for an unpowered reusable launch vehicle

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