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Journal ArticleDOI

Autonomous Entry Guidance for Hypersonic Vehicles by Convex Optimization

Zhenbo Wang, +1 more
- 03 Apr 2018 - 
- Vol. 55, Iss: 4, pp 993-1006
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TLDR
Advanced entry guidance systems could potentially enable future vehicles to generate feasible/optimal flight trajectories onboard for the latest mission requirements and track the new trajectories as well as generate feasible and optimal trajectories for new missions.
Abstract
Advanced entry guidance systems could potentially enable future vehicles to generate feasible/optimal flight trajectories onboard for the latest mission requirements and track the new trajectories ...

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Citations
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Journal ArticleDOI

Real-Time Optimal Control for Spacecraft Orbit Transfer via Multiscale Deep Neural Networks

TL;DR: A real-time optimal control approach is proposed using deep learning technologies to obtain minimum-time trajectories of solar sail spacecraft for orbit transfer missions and three deep neural networks are designed and trained offline by the obtained optimal solutions to generate the guidance commands in real time during flight.
Journal ArticleDOI

Optimal trajectories and normal load analysis of hypersonic glide vehicles via convex optimization

TL;DR: Both the maximum and minimum peak-normal-load entry trajectories are explored using convex optimization and the convergence and accuracy of the proposed methodologies are demonstrated by numerical simulations, and the feasibility of the converged solutions is discussed based on an entry-corridor approach.
Journal ArticleDOI

Fast Generation of Optimal Asteroid Landing Trajectories Using Deep Neural Networks

TL;DR: A systematical solution for asteroid landing trajectory optimization is developed, wherein the DNNs provide good initial solutions, and the accurate solutions for landings are obtained through a solution continuation process.
Journal ArticleDOI

Improved Sequential Convex Programming Algorithms for Entry Trajectory Optimization

TL;DR: Entry trajectory optimization for hypersonic vehicles has been formulated as constrained optimal control problems, which are difficult to solve because of the existing high nonlinearity and nonconviction problems.
References
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Journal ArticleDOI

On the implementation of an interior-point filter line-search algorithm for large-scale nonlinear programming

TL;DR: A comprehensive description of the primal-dual interior-point algorithm with a filter line-search method for nonlinear programming is provided, including the feasibility restoration phase for the filter method, second-order corrections, and inertia correction of the KKT matrix.
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Interior-Point Polynomial Algorithms in Convex Programming

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Primal-Dual Interior-Point Methods

TL;DR: This chapter discusses Primal Method Primal-Dual Methods, Path-Following Algorithm, and Infeasible-Interior-Point Algorithms, and their applications to Linear Programming and Interior-Point Methods.
Journal ArticleDOI

GPOPS-II: A MATLAB Software for Solving Multiple-Phase Optimal Control Problems Using hp-Adaptive Gaussian Quadrature Collocation Methods and Sparse Nonlinear Programming

TL;DR: A general-purpose MATLAB software program called GPOPS--II is described for solving multiple-phase optimal control problems using variable-order Gaussian quadrature collocation methods.
Journal ArticleDOI

Convex programming approach to powered descent guidance for mars landing

TL;DR: This work presents a convex programming algorithm for the numerical solution of the minimum fuel powered descent guidance problem associated with Mars pinpoint landing as a finite-dimensional convex optimization problem as a second-order cone programming problem.
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