首页 | 本学科首页   官方微博 | 高级检索  
     

空间绳系机器人的多次推力逼近策略研究
引用本文:阳应权,黄攀峰,孟中杰,王明. 空间绳系机器人的多次推力逼近策略研究[J]. 计算机仿真, 2012, 0(8): 64-67,158
作者姓名:阳应权  黄攀峰  孟中杰  王明
作者单位:西北工业大学航天飞行动力学技术重点实验室
基金项目:国家自然基金资助项目(60805034,61005062);中国博士后基金(2010471640)
摘    要:针对空间绳系机器人近距离逼近问题,提出了基于时间最优的一般N次推力机动策略及算法,由演化得到的等时间N次机动模式和等速度增量N次推力机动模式,能够将多次推力机动策略中复杂的多时间变量求值问题转化为有非线性约束的最小机动时间问题,并利用基于罚函数法的遗传算法进行求解,对空间绳系机器人的近距离逼近问题进行了仿真。仿真表明:一般N次推力机动策略及算法能够很好解决此类多时间变量求值问题;且不需要进行初始速度脉冲修正,相对于基于"时间倒流法"的N次推力策略和连续推力具有较小的机动时间,并在某些情形下相较于后两者以及双冲量机动具有较少的能耗或者较小的最大视界角,为绳系机器人推动逼近设计提供了依据。

关 键 词:时间最优  有约束非线性最优化  遗传算法

Multi-thrust Approach Strategy for Space Tethered Robot
YANG Ying-quan,HUANG Pan-feng,Meng Zhong-jie,WANG Ming. Multi-thrust Approach Strategy for Space Tethered Robot[J]. Computer Simulation, 2012, 0(8): 64-67,158
Authors:YANG Ying-quan  HUANG Pan-feng  Meng Zhong-jie  WANG Ming
Affiliation:(National Key Laboratory of Aerospace Flight Dynamics,Northwestern Polytechnical University, Xi’an Shanxi 710072,China)
Abstract:Dealing with the multi-thrust approach maneuvers for space tethered robot.Firstly,a strategy of general N-thrust maneuvers based on time optimization was presented in this paper,which was handled by the genetic algorithm with penalty function and can be used to allow the issue for solving complicated multiple time variables to transform into the one for constrained nonlinear optimization.Then based on this strategy,two models of N-thrust maneuvers for equal time interval and equal velocity increment can be established,meanwhile two cases of multi-thrust approach maneuvers for space tethered robot were simulated in this paper.Simulation results show that: this strategy,which is no need for impulse correction of the initial velocity,can deal with the issue for solving multiple time variables very well and has several advantages compared with the other strategies of N-thrust maneuvers from the method of "time back" and the continuous-thrust maneuvers even the double impulsive maneuvers,such as smaller maneuvering time and less energy consumption under some situations.
Keywords:Time optimization  Constrained nonlinear optimization  Genetic algorithm
本文献已被 CNKI 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号