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基于改进分段Gauss伪谱法的带推力高超声速飞行器再入轨迹规划 被引量:11

Powered hypersonic vehicle reentry trajectory optimization based on improved multi-phase Gauss spectral method
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摘要 再入轨迹规划是高超声速飞行器领域的热点问题,已吸引了众多国内外专家的关注. Gauss伪谱法以及分段Gauss伪谱法是解决含有多约束轨迹规划问题的一类有效工具.然而,发动机多次点火熄火导致推力不连续以及点火时刻控制输入的连续性要求是带推力高超声速飞行器再入轨迹优化面临的新挑战.本文将问题简化为多脉冲再入轨迹规划问题,基于改进分段Gauss伪谱法生成满足多条件约束的最优再入轨迹.通过设置分段Gauss伪谱法连续性条件,确保飞行器状态与控制输入在分段点处连续衔接.通过无动力自由再入与带推力再入算例对改进分段Gauss伪谱法进行说明,仿真结果也表明,改进分段Gauss伪谱法可有效求解带推力高超声速飞行器再入轨迹规划. Reentry trajectory optimization is a hot topic of hypersonic vehicle, and has gained more and more attentions of the expert. Gauss pseudospectral method (GPM) and multi-phase Gauss pseudospectral method (MGPM) have been demonstrated as effective tools to solve the trajectory optimization with multi-constraints. However, thrust discontinuity caused by multiple ignition on and off and the requirement of control input continuity at ignition time are new challenges to powered hypersonic vehicle reentry trajectory optimization. In this paper, the problem is simplified to a multi-impulse reentry trajectory optimization problem, and a multi-condition constraint reentry trajectory is generated based on improved multi-phase Gauss pseudospectral method. The continuity conditions of MGPM are set to ensure the continuous connection of the states and control between each pair of phases. Numerical examples for reentry trajectory optimization in free flight and powered are used to demonstrate the proposed technique. Simulation results also show the feasible application of improved MGPM in powered reentry trajectory optimization.
作者 蔺君 何英姿 黄盘兴 LIN Jun;HE Ying-zi;HUANG Pan-xing(Beijing Institute of Control Engineering, Beijing 100190, China;Science and Technology on Space Intelligent Control Laboratory, Beijing 100190, China)
出处 《控制理论与应用》 EI CAS CSCD 北大核心 2019年第10期1662-1671,共10页 Control Theory & Applications
基金 国家自然科学基金项目(61873029)资助~~
关键词 高超声速飞行器 再入轨迹优化 分段Gauss伪谱法 多脉冲轨迹规划 推力 hypersonic vehicles reentry trajectory optimization multi-phase Gauss peudospectral method multiimpulse trajectory optimization thrust
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