卫星动量轮灵敏性变异分析

夏新涛; 常振; 叶亮; 李云飞; 邱明

doi:10.13224/j.cnki.jasp.2017.03.024

卫星动量轮灵敏性变异分析

doi: 10.13224/j.cnki.jasp.2017.03.024

河南科技大学机电工程学院,河南洛阳 471003

基金项目: 国家自然科学基金（51475144, 51075123）; 河南省高校科技创新团队支持计划（13IRTSTHN025）

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出版历程
- 收稿日期: 2016-05-20
- 刊出日期: 2017-03-28

Variation analysis of sensitivity for satellite momentum wheel

摘要

摘要: 基于模糊理论提出一种非线性卫星动量轮灵敏性变异分析的数值方法,以工程实际中的模糊相似关系转化为空间向量的模糊等价关系,来评估稳定系统的总体变异本质特征.并通过仿真均匀分布、线性分布以及周期分布的时间数据序列验证了该模型的可行性；以3套卫星动量轮实际稳态运转实验见证了该方法的实用性和有效性.其中动量轮A的最小灵敏系数为0.678，大于0.5阈值,表明其运转期间灵敏性十分良好；动量轮B的最小灵敏系数为0.439，小于0.5阈值,其运转期间灵敏性有所变异；动量轮C的最小灵敏系数等于0.5阈值,其关系最为模糊并介于稳定与变异之间.该模型实时预测并描述了动量轮灵敏性变异过程,且适用于诸多航天领域的非线性乏信息问题.
- 动量轮 /
- 灵敏性 /
- 时间序列 /
- 模糊关系 /
- 变异
Abstract: A numerical method for nonlinear sensitivity variation analysis of satellite momentum wheel was proposed based on the fuzzy theory, so as to evaluate the overall variation characteristics of stability system by changing the fuzzy similarity relation of engineering practice into the fuzzy equivalence relation of space vector. Through simulating the time data sequence of the uniform distribution, linear distribution and period distribution, the feasibility of model was verified; according to the actual steady-state running test for the three sets of satellite momentum wheels, this method was practical and effective. Among them, the minimum sensitivity coefficient of momentum wheel A was 0.678,greater than the 0.5 threshold, showing that its sensitivity was very good during the operation; however, the minimum sensitivity coefficient of momentum wheel B was 0.439, less than the 0.5 threshold, so its sensitivity produced a variation; and the minimum sensitivity coefficient of momentum wheel C was equal to the 0.5 threshold, showing the momentum wheel C had the most fuzzy relation between stability and variation. The variation process of sensitivity of the momentum wheel was forecasted and described in time. This model is also suitable for many nonlinear poor information problems in the field of space.
- momentum wheel /
- sensitivity /
- time series /
- fuzzy relation /
- variation

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