| 引用本文: | 马广富,孙延超,凌惠祥,李传江.近距离跟踪指向空间非合作目标有限时间控制[J].哈尔滨工业大学学报,2017,49(4):8.DOI:10.11918/j.issn.0367-6234.201511076 |
| MA Guangfu,SUN Yanchao,LING Huixiang,LI Chuanjiang.Finite-time control of spacecraft closely tracking and pointing non-cooperative space target[J].Journal of Harbin Institute of Technology,2017,49(4):8.DOI:10.11918/j.issn.0367-6234.201511076 |
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| 摘要: |
| 追踪航天器在对空间非合作目标进行近距离跟踪与监视时，需要接近非合作目标并从特定方位保持对目标的指向与观测.针对非合作目标存在姿态翻滚以及未知轨道机动时追踪航天器保持近距离跟踪与指向的问题，在视线坐标系和体坐标系下分别建立了相对轨道和姿态的动力学方程，并构建了对轨道与姿态同步控制的六自由度模型，利用RBF神经网络对系统不确定性及未知的目标运动参数进行自适应估计和补偿，采用反步法思想设计控制器使追踪航天器在有限时间内收敛到期望的相对轨道和姿态并维持保持状态.进一步考虑控制输入饱和、死区等非线性特性，对控制律进行改进.改进后的控制算法可以有效地提高控制精度, 仿真结果验证了控制对象模型和控制算法的有效性.
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| 关键词: 空间非合作目标 视线坐标系 有限时间控制 RBF神经网络 反步法 输入受限 |
| DOI：10.11918/j.issn.0367-6234.201511076 |
| 分类号:V448.2 |
| 文献标识码:A |
| 基金项目:国家自然科学基金(5,0);高等学校博士学科点专项科研基金 (20102302110031) |
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| Finite-time control of spacecraft closely tracking and pointing non-cooperative space target |
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MA Guangfu,SUN Yanchao,LING Huixiang,LI Chuanjiang
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（School of Astronautics, Harbin Institute of Technology, Harbin 150001, China）
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| Abstract: |
| When the chaser spacecraft closely tracks and observes the non-cooperative target in space, it should approach to and keep pointing to the non-cooperative target from the particular direction. For the problem that the chaser spacecraft keeps closely tracking and pointing to the non-cooperative target, in the case of the target with the attitude motion and the unknown orbit maneuver, based on the relative orbit dynamics and the attitude dynamics which are described in the line-of-sight coordinate frame and the body coordinate frame, respectively, the six-degree-of-freedom model of orbit and attitude simultaneously control is proposed. The RBF neural network is employed to adaptively estimate and compensate the system uncertainties and the unknown motion parameters of the target. Using the backstepping method, a controller which can control the chaser spacecraft to converge to the desired relative orbit and attitude in finite time is proposed. Considering the nonlinearity of the control input, such as saturation and dead zone, an improved control algorithm is developed. The simulation results are provided to show the effectiveness of the control model and the control algorithms. Moreover, the improved control method has higher control accuracy.
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| Key words: non-cooperative target line-of-sight coordinate frame finite-time control RBF neural network backstepping input constraint |
