飞机纵向起飞着陆动态特性仿真研究

以刚体系动力学理论为依据,结合飞机起飞着陆运动学特征,建立了起落架-机身组合刚体6自由度全量飞机方程。文内建立的阶跃跟踪驾驶员时域数学模型,有助于评价起飞着落阶段人-机系统的飞行品质。根据该系统的数学模型编制了FORTRAN软件,并对起飞着陆动态特性作出了综合的全面的定量分析。     

面向飞机蒙皮对缝的移动机器人自主跟踪方法

提出一种面向飞机蒙皮对缝的移动机器人自主跟踪方法,用以解决大型蒙皮上表面装配对缝的自动化测量问题.移动机器人包括对缝测量模块和运动控制模块,对缝测量模块在测量对缝间隙阶差的同时得到机器人相对于对缝的位姿,运动控制模块控制机器人自主调姿.基于双线结构光与对缝的相对位置关系,提出机器人在不同情况下的自主调姿方法,解决了机器...     

一种面向弹道再入目标跟踪的HPD-SRCQSPF算法

针对弹道再入目标轨迹跟踪问题,提出基于混合建议分布的平方根容积求积采样粒子滤波（HPD-SRCQSPF）算法,该算法以混合建议分布为框架,由两个基本建议分布组成。其中一个基本建议分布为先验分布,另一个基本建议分布为平方根容积求积卡尔曼滤波估计后的值。该混合建议分布与真实的后验分布很接近,因此有着高效性、高精度等特点。仿真结果表明,对于弹道再入目标轨迹跟踪模型,相比于标准粒子滤波（SPF）算法和平方根容积求积粒子滤波（SRCQPF）算法,HPD-SRCQSPF算法可以在较低运算负载的情况下获得更好的跟踪性能。特别是在弹道目标变轨机动的情况时,所提出算法的性能增益更为显著。     

立方星电源系统最大功率点跟踪优化控制方法

针对立方星在能量来源严重受限条件下如何提高太阳能利用率的难题,提出一种适用于立方星的集中供电式空间微电源架构(EPS),并设计基于改进粒子群优化算法的最大功率点跟踪(MPPT)控制策略来提升能量转换效率。首先,推导太阳电池阵列的数学模型,并根据太阳电池阵列的工作特性,提出电源系统最大功率点跟踪控制的物理系统实现结构。其次,设计基于改进粒子群优化(PSO)的最大功率点跟踪控制算法,并进行了数学仿真校验。最后,对所设计的电源系统架构进行了硬件实现和试验验证。地面试验结果表明,电源系统的太阳能最大转换效率可达95.5%。该电源系统成功应用于世界首颗12U立方星“翱翔之星”的飞行试验,在轨数据表明电源系统工作状态良好,为微纳卫星电源系统的设计提供了有益参考。     

Kinematics-based four-state trajectory tracking control of a spherical mobile robot driven by a 2-DOF pendulum

Spherical mobile robot has compact structure, remarkable stability, and flexible motion,which make it have many advantages over traditional mobile robots when applied in those unmanned environments, such as outer planets. However, spherical mobile robot is a special highly under-actuated nonholonomic system, which cannot be transformed to the classic chained form. At present, there has not been a kinematics-based trajectory tracking controller which could track both the position states and the attitude states of a spherical mobile robot. In this paper, the four-state(two position states and two attitude states) trajectory tracking control of a type of spherical mobile robot driven by a 2-DOF pendulum was studied. A controller based on the shunting model of neurodynamics and the kinematic model was deduced, and its stability was demonstrated with Lyapunov's direct method. The control priorities of the four states were allocated according to the magnification of each state tracking error in order to firstly ensure the correct tracking of the position states. The outputs(motor speeds) of the controller were regulated according to the maximum speeds and the maximum accelerations of the actuation motors in order to solve the speed jump problem caused by initial state errors, and continuous and bounded outputs were obtained. The effectiveness including the anti-interference ability of the proposed trajectory tracking controller was verified through MATLAB simulations.     

Event-triggered adaptive control for attitude tracking of spacecraft

Plug-and-play technology is an important direction for future development of spacecraft and how to design controllers with less communication burden and satisfactory performance is of great importance for plug-and-play spacecraft. Considering attitude tracking of such spacecraft with unknown inertial parameters and unknown disturbances, an event-triggered adaptive backstepping controller is designed in this paper. Particularly, a switching threshold strategy is employed to design the event-triggering mechanism. By introducing a new linear time-varying model, a smooth function, an integrable auxiliary signal and a bound estimation approach, the impacts of the network-induced error and the disturbances are effectively compensated for and Zeno phenomenon is successfully avoided. It is shown that all signals of the closed-loop system are globally uniformly bounded and both the attitude tracking error and the angular velocity tracking error converge to zero. Compared with conventional control schemes, the proposed scheme significantly reduces the communication burden while providing stable and accurate response for attitude maneuvers. Simulation results are presented to illustrate the effectiveness of the proposed scheme.     

融合背景图像信息和多特征压缩的相关滤波跟踪算法

针对相关滤波类跟踪算法目标背景图像信息利用率较低、目标特征表达能力较弱的问题,提出了一种融合背景图像信息的多特征压缩跟踪算法。首先,在上下文感知滤波器的基础上,将背景图像信息加入位置滤波器。其次,提取颜色名(Color Name, CN)特征与梯度直方图(Histogram of Oriented Gradient, HOG)特征,使用最大响应因子及平均峰相关能量(Average Peak-to-Correlation Energy, APCE)评估跟踪结果的可信度,实现两种特征的自适应融合。最后,利用特征降维简化模型的复杂度,实现算法运行速度的提升。实验结果表明,改进后的算法在遮挡、形变、尺度变化等复杂环境下均具有较高的鲁棒性,其跟踪精度和成功率指标均优于DSST及其他主流的跟踪算法,并且仍保持了实时性。     

基于人工神经网络的多模型目标跟踪算法

针对在目标跟踪中单模型跟踪算法难以应对目标运动形式的变化,而多模型跟踪算法存在结构固定、跟踪精度被非匹配模型削弱且模型切换缓慢的矛盾,文章提出了一种基于人工神经网络的多模型目标跟踪算法。通过分析目标几种基本运动模式的轨迹特点,归纳出目标运动轨迹的特征向量。利用训练好的BP神经网络对滑窗里的轨迹段进行运动模型识别,按结果进行跟踪模型切换,达到使跟踪算法实时适应目标运动状态的目的。仿真结果证明了该算法的有效性,且与传统的多模型算法相比,具有结构更加简单、更强的灵活性和拓展性的特点。     

太阳跟踪定位技术及其应用研究

太阳跟踪定位技术广泛应用于能源、气象和航天等领域,系统全面地对相关方法进行分类和阐述,并对多孔复用、太阳光纤导入等较新应用进行了分析,最后总结了该领域内相关技术发展的瓶颈问题,展望了未来的研究方向.