Motion-planning and pose-tracking based rendezvous and docking with a tumbling target

Rendezvous and docking (RVD) with a tumbling target is challenging. In this paper, a novel control scheme based on motion planning and pose (position and attitude) tracking is proposed to solve the pose control of a chaser docking with a tumbling target in the phase of close range rendezvous. Firstly, the current desired motion of the chaser is planned according to the motion of the target. In planning the desired motion, the “approach path constraint” is considered to avoid collisions between the chaser and the target, and the “field-of-view constraint” is considered to make sure the vision sensors on the chaser to obtain tight relative pose knowledge of the target with respect to the chaser. Then, the difference between the chaser’s motion and the desired motion is gradually reduced by a pose tracking controller. This controller is based on the non-singular terminal sliding mode (NTSM) method to make the tracking error converge to zero in finite time. Since the chaser nearly moves along the desired motion and the motion is reasonable, (1) it could safely arrive at the docking port of the target with a suitable relative attitude, (2) it will be always suitably oriented to observe the target well, and (3) the magnitude of the needed control inputs are less than that in existing literatures. The numerical results demonstrate the above three advantages of the proposed method.     

星间相对测量自主导航的改进容积卡尔曼滤波

针对仅利用星间相对位置测量的双星自主导航系统，提出一种基于可观度的改进容积卡尔曼滤波算法。该算法从系统可观度的物理意义出发，通过对预测协方差阵进行在线调整改善标准容积卡尔曼滤波算法对系统可观度敏感和不满足滤波拟一致性等问题。对具体算例进行数值仿真，校验了该改进容积卡尔曼滤波算法在基于星间相对位置测量的双星自主导航系统中的有效性，与标准容积卡尔曼滤波相比趋稳更快，精度更高。     

双T型量子线的电子自旋极化输运性质

文章研究了一个由两个T型异质结串联耦合量子结构的自旋输运性质。该结构中含有Rashba自旋轨道耦合相互作用。在工作中,计算了电子在自旋极化入射和自旋非极化入射两种情况下,电子在出射端的自旋极化率随体系结构的变化。发现通过适当的设计结构,当电子自旋非极化入射时,在出射端可以得到高达0.9的自旋极化率。其物理机制来源于体系结构引起的电子干涉使自旋向上的电子和自旋向下的电子有不同的透射率。     

Modified unscented Kalman filtering and its application in autonomous satellite navigation

In this paper, a modified unscented Kalman filter (UKF) for nonlinear stochastic systems is proposed, and it is applied to autonomous orbit determination for Earth satellites. Based on some standard results about the boundedness of stochastic processes and a new formulation of the unscented transformation (UT), it is demonstrated that the design of the noise covariance matrix plays an important role in enhancing the filter stability. Furthermore, a particular design of the noise covariance matrix is proposed as a modification of the UKF. The modified UKF is less sensitive to the initial error than the usual one. High performance of the modified UKF is illustrated in comparison with the usual one by using the real data obtained from an Earth sensor.     

Model-free adaptive optimal design for trajectory tracking control of rocket-powered vehicle

An adaptive optimal trajectory tracking controller is presented for the Solid-Rocket-Powered Vehicle (SRPV) with uncertain nonlinear non-affine dynamics in the framework of adaptive dynamic programming. First, considering that the ascent model of the SRPV is non-affine, a model-free Single Network Adaptive Critic (SNAC) method is developed based on the dynamic neural network and the traditional SNAC method. This developed model-free SNAC method overcomes the limitation of the traditional SNAC method that can only be applied to affine systems. Then, a closed-form adaptive optimal controller is designed for the non-affine dynamics of SRPVs. This controller can adjust its parameters under different flight conditions and converge to the approximate optimal controller through online self-learning. Finally, the convergence to the approximate optimal controller is proved. The theoretical analysis of the uniformly ultimate boundedness of the tracking error is also presented. Simulation results demonstrate the effectiveness of the proposed controller.     

Central difference predictive filter for attitude determination with low precision sensors and model errors

Attitude determination is one of the key technologies for Attitude Determination and Control System (ADCS) of a satellite. However, serious model errors may exist which will affect the estimation accuracy of ACDS, especially for a small satellite with low precision sensors. In this paper, a central difference predictive filter (CDPF) is proposed for attitude determination of small satellites with model errors and low precision sensors. The new filter is proposed by introducing the Stirling’s polynomial interpolation formula to extend the traditional predictive filter (PF). It is shown that the proposed filter has higher accuracy for the estimation of system states than the traditional PF. It is known that the unscented Kalman filter (UKF) has also been used in the ADCS of small satellites with low precision sensors. In order to evaluate the performance of the proposed filter, the UKF is also employed to compare it with the CDPF. Numerical simulations show that the proposed CDPF is more effective and robust in dealing with model errors and low precision sensors compared with the UKF or traditional PF.     

串联型MPPT空间电源系统稳定性技术

串联型最大功率点跟踪(MPPT)空间电源系统存在母线电压振荡或跌落等不稳定现象,文章以MPPT不调节母线电源拓扑为研究对象,建立了系统等效电路模型,通过小信号等效分析、状态空间方程特征根求解等手段,分别对MPPT控制域及电压控制域下电源系统的稳定性进行了分析.结果表明,在太阳电池阵及阵列功率调节器特性曲线一定的条件下,通过对二者间电感、电容参数合理配置,可以保证系统稳定.在MATLAB/SIMULINK中搭建了串联型MPPT不调节母线电源系统仿真模型并进行实例仿真,仿真结果验证了理论分析的正确性.     

用于微机械捷联式航姿系统的四元素算法卡尔曼滤波器

介绍了一种卡尔曼滤波器 ,它适用于由微机械惯性传感器构成的捷联式航姿系统。文中阐述了系统构成和原理 ,基于四元素算法公式推导了姿态算法和系统误差模型 ,并设计了实时卡尔曼滤波器。仿真结果表明 ,当没有横向加速度干扰时系统精度优于 0 .0 4度 ,当出现 0 .1g/1Hz的横向交变加速度干扰时 ,精度降为 0 .4 4度。初步测试结果表明系统的静态精度为 :俯仰和横滚 /-0 .2度 ,航向 /- 0 .3度。     

地磁辅助的无缝INS/GPS组合导航研究

INS/GPS组合导航已经成为当前无人机导航系统的主要实现形式,由于GPS信号容易受到干扰,在恶劣的电磁环境下信号易丢失,从而导致GPS卫星信号失锁而无法使用。地磁导航作为一种无源导航方法,其难以受到外界干扰且具有较强的自主性,从而为克服GPS在干扰情况下无法对INS误差实现持续无缝修正的不足提供了很好的途径。针对INS/GPS组合导航中GPS卫星信号失锁的情况,设计提出了使用地磁匹配导航进行辅助实现无人机无缝导航的实现方案,设计了基于地磁特征的地磁匹配算法和地磁匹配辅助的INS/GPS组合无缝自主导航算法,并通过仿真验证了采用地磁匹配辅助导航方法,可以在GPS无效的情况下,实现对INS导航误差的持续无缝修正,从而提高导航系统性能。     

连续变速颤振试验的自适应粒子滤波算法

连续变速颤振试验的采集信号通常为非平稳信号,其频率和幅值随时间变化,尤其在亚临界状态下, 变化程度十分剧烈。常用的非平稳信号时变参数建模分析方法,在信号非平稳程度较高的情况下难以对信号 的模态进行准确地分析和跟踪。为了解决这一问题,结合信号非平稳度量计算方法,提出一种改进的自适应粒 子滤波算法,并通过仿真实验数据对所提算法在高非平稳度情况下的跟踪性能进行验证。结果表明:与一般粒 子滤波算法相比,本文方法在高非平稳度情况下具有更高的跟踪精度。