引用本文: | 武海雷,韩飞,贺亮,孙玥,刘超镇.翻滚目标逼近的虚拟域逆动力学轨迹规划[J].控制理论与应用,2018,35(10):1464~1472.[点击复制] |
WU Hai-lei,HAN Fei,HE Liang,SUN Yue,LIU Chao-zhen.Trajectory planning based on inverse dynamics in virtual domain for approaching tumbling target[J].Control Theory and Technology,2018,35(10):1464~1472.[点击复制] |
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翻滚目标逼近的虚拟域逆动力学轨迹规划 |
Trajectory planning based on inverse dynamics in virtual domain for approaching tumbling target |
摘要点击 2833 全文点击 1196 投稿时间:2017-11-30 修订日期:2018-09-18 |
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DOI编号 10.7641/CTA.2018.70892 |
2018,35(10):1464-1472 |
中文关键词 翻滚目标 相对动力学 逆动力学 轨迹规划 |
英文关键词 target relative dynamics inverse dynamic trajectory planning |
基金项目 国家自然科学基金重大项目(61690214), 国家自然科学基金面上项目(61374162)资助 |
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中文摘要 |
针对追踪星自主逼近和跟踪翻滚目标特定部位的最优规划问题, 提出了一种基于虚拟域逆动力学的多约束最
优逼近轨迹规划方法.首先, 在翻滚目标本体系下建立追踪星相对于翻滚目标特定部位的相对轨道动力学方程, 并建立
追踪星本体系相对于翻滚目标期望固连坐标系的相对姿态动力学方程; 其次, 考虑目标星外形、敏感器视场和执行机构
控制能力等约束条件, 建立时间/能量最优规划模型; 然后, 采用序列二次规划(sequential quadratic programming,
SQP)方法求解时间/能量最优规划问题; 最后, 数值仿真验证了该方法在满足多约束条件下, 可实现对翻滚目标自主逼
近与跟踪的最优轨迹规划, 同时与高斯伪谱法进行了对比, 验证了本方法在计算效率方面的优势. |
英文摘要 |
In order to solve the optimal trajectory planning for approaching and tracking the specific position of the tumbling
target , a multi-constrained optimal trajectory planning method based on inverse dynamics in the virtual domain (IDVD)
is proposed. Firstly, the relative orbital dynamics equation of the chaser relative to the specific position of the target is
established in the target body coordinate system and the relative attitude kinetics equation of the chaser relative to the
desired attached-target coordinate system is also established. Secondly, the time/energy optimal programming model is
established based on the inverse dynamic method considering the constraints of target shape, actuator size and sensor field;
Then, the sequential quadratic programming (SQP) method is used to solve the planning problem. Lastly, the numerical
simulations show that the chaser can arrive the expected states under the multi-constraint condition and verify the advantages
in terms of computational efficiency compared with the Gauss pseudospectral (PS) method. |
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