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

Hypersonic trajectory optimization has been intensively investigated through different approaches; however, the normal-load-optimal entry problems were barely studied and reported in the literature. Finding the optimal trajectories with maximum or minimum peak normal load is essential to evaluate th...

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Veröffentlicht in:Aerospace science and technology Jg. 87; S. 357 - 368
1. Verfasser: Wang, Zhenbo
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Elsevier Masson SAS 01.04.2019
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ISSN:1270-9638, 1626-3219
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Zusammenfassung:Hypersonic trajectory optimization has been intensively investigated through different approaches; however, the normal-load-optimal entry problems were barely studied and reported in the literature. Finding the optimal trajectories with maximum or minimum peak normal load is essential to evaluate the maneuverability and structural strength of the vehicle. In this paper, both the maximum and minimum peak-normal-load entry trajectories are explored using convex optimization. Based on the previous work, the maximum-peak-normal-load entry problem is firstly addressed by a Big-M method and a line-search approach. Through successive relaxations, the nonconvex discrete-event optimal control problem associated with maximum-peak-normal-load entry is transformed into a sequence of mixed-integer convex optimization problems. Then, a line-search technique is introduced to improve the convergence of the proposed method. Additionally, a sequential convex programming method is designed to solve the minimum-peak-normal-load entry problem to comprehensively analyze the normal load during the entry flight. There are efficient solvers that can solve each relaxed convex subproblem with a global optimum if the feasible set of the subproblem is nonempty. 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.
ISSN:1270-9638
1626-3219
DOI:10.1016/j.ast.2019.03.002