通用伪谱优化软件(GPOPS)在高约束多相弹道生成中的研究进展

Shawn Rexius, Tiffany Rexius, T. R. Jorris, A.V.Nageswara varaha Rao
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引用次数: 8

摘要

摘要:高超声速滑翔飞行器项目中最近发生的事件需要一种新的方法来检查可能的飞行试验轨迹,以包括对最优轨迹生成的新约束。飞机稳定性、复合热结构载荷和飞行器烧蚀都是高超声速飞行器飞行的重要考虑因素;最优轨迹生成应该考虑到这些复杂的约束。空军研究实验室航空航天系统理事会和爱德华兹空军基地的第412测试联队进行了一项合作,以分析满足这些约束条件的可能的最佳控制解决方案。在通用伪谱优化软件(GPOPS)中实现了三级助推器气动推进模型和高超声速滑翔飞行器气动烧蚀模型。所得到的最优控制问题模拟了助推器在再入飞行器撞击下的发射,并纳入了包括滞胀加热、烧蚀、无y区、飞行器稳定性、动压力、航迹角时间变化率、载荷和末段目标等多个复杂约束条件。此外,最优控制问题使用导出的事件作为制导模式或助推器级连杆;包括距离目标、距离发射场、载具载荷、高度、动压力和时间高度变化率。将最优控制变量指定为引导变量的导数;这允许在平移(质点)问题中约束姿态率。研究表明,gpop能够使用复杂的车辆模型分析高度约束的多阶段最优控制问题,并且足够灵活,可以快速纳入新的约束,从而探索新的制导方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Advances in Highly Constrained Multi-Phase Trajectory Generation using the General Pseudospectral Optimization Software (GPOPS)
Abstract : Recent events in hypersonic glide vehicle programs have necessitated a new approach to examine possible flight test trajectories to include new constraints on optimal trajectory generation. Aircraft stability, combined thermo-structural loading, and vehicle ablation are all important considerations for hypersonic vehicle flight; optimal trajectory generation should account for these complex constraints. A collaborative effort was undertaken by the Air Force Research Laboratory Aerospace Systems Directorate and the 412th Test Wing at Edwards Air Force Base to analyze possible optimal control solutions that satisfy these constraints. A three-stage booster aerodynamic and propulsion model and a hypersonic glide vehicle aerodynamic and ablation model were implemented in the General Pseudospectral Optimization Software (GPOPS). The resulting optimal control problem models booster launch through re-entry vehicle impact and incorporates multiple complex constraints including stagnation heating, ablation, no-y zones, aircraft stability, dynamic pressure, time-rate of change of flight path angle, loads and a terminal phase target. Furthermore, the optimal control problem uses derived events as guidance mode or booster stage linkages; including range to target, range from launch site, vehicle loads, altitudes, dynamic pressure and time rate of change of altitude. The optimal control variables are specified to be the guidance variable derivatives; this allows for constraining attitude rates in a translational (point mass) problem. GPOPS is shown to be capable of analyzing highly constrained, multiple-phase optimal control problems using complex vehicle models and flexible enough to incorporate new constraints quickly allowing for exploration of new guidance methodologies.
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