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作 者:宋雨 张伟 苗新元 张志国 龚胜平[1] SONG Yu;ZHANG Wei;MIAO Xinyuan;ZHANG Zhiguo;GONG Shengping(School of Aerospace Engineering,Tsinghua University,Beijing 100084,China;Beijing Institute of Aerospace System Engineering,Beijing 100076,China)
机构地区:[1]清华大学航天航空学院,北京100084 [2]北京宇航系统工程研究所,北京100076
出 处:《清华大学学报(自然科学版)》2021年第3期230-239,共10页Journal of Tsinghua University(Science and Technology)
基 金:国家自然科学基金资助项目(11772167,11822205)。
摘 要:针对火箭垂直回收精确着陆问题,该文研究了基于凸优化的在线制导算法,提出了一种制导、导航与控制一体化闭环数值仿真方法。通过无损凸化和逐次凸化方法,将火箭回收段制导问题转化为二阶锥优化问题,并结合内点法将该特定问题进行定制求解。研究了在随机大气扰动、发动机节流特性、导航系统随机偏差以及系统整体时延等多重不确定因素作用下算法的鲁棒性。通过对问题进行定制化求解,该算法具备毫秒级的收敛特性,且具有较高的算法鲁棒性。在动力学环境扰动、控制和导航系统偏差以及系统整体延时等不同扰动的组合作用下,该算法的仿真结果满足火箭回收精确软着陆的要求。Precise soft rocket recovery landings require precise guidance, navigation, and control. A convex optimization guidance algorithm was developed for soft vertical rocket recovery landings and tested in a closed-loop simulation system. A lossless convex model was combined with successive convex iterations to transform the rocket recovery stage guidance problem into a convex optimization problem using the interior point method. The algorithm robustness was evaluated for various factors including random atmospheric disturbances, engine throttling characteristics, random navigation system deviations, and system delays. The simulations show that the onboard guidance algorithm has millisecond convergence and is very robust. Various simulations show that the closed-loop simulation results can provide precise soft landings for rocket recovery even with the combined effects of various disturbances including dynamic environments, control and navigation system deviations, and system delays.
关 键 词:可回收火箭 精确软着陆 在线制导 凸优化 闭环数值仿真
分 类 号:TP311.51[自动化与计算机技术—计算机软件与理论]
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