基于干扰观测器的四旋翼无人机离散时间容错控制

为了飞行控制方案便于在计算机上实现，针对具有外部干扰和执行器加性故障的四旋翼无人机（UAV）角度运动方程，给出一种基于干扰观测器的离散时间跟踪控制方案。通过设计离散时间干扰观测器抑制外部干扰和执行器故障的不利影响，并结合干扰观测器设计离散时间控制器。通过数值仿真验证了基于干扰观测器的离散时间容错控制方案的有效性。仿真结果表明，设计的离散控制器能够保证外部干扰和执行器故障综合作用下的四旋翼UAV系统跟踪控制性能。     

规则回转体自动铺丝轨迹规划与丝束增减

为满足自动铺丝轨迹的满铺覆性要求，针对现阶段自动铺丝轨迹规划存在的不足，提出了不同的丝束增减算法。首先讨论纤维铺放方向的确定和中心轨迹数量的计算，设计不同铺放方向轨迹的生成算法。然后以丝束重叠系数为重要参数，对于纤维局部堆积和空缺问题提出单侧纤维裁剪算法和双侧纤维裁剪算法，并对裁剪后的重叠区域和间隙区域进行面积求解，使得纤维丝束均匀覆于芯模表面。最后基于CATIA CAA二次开发平台，将上述算法集成到纤维铺放CAD系统中，通过运动仿真系统验证算法的正确性。利用提出的丝束增减算法，实现了间隙/重叠区的均匀分布，尽量降低了富树脂区等相关缺陷的聚集对性能的不良影响。     

由感知到动作决策一体化的类脑导航技术研究现状与未来发展

随着脑与神经科学以及人工智能技术的持续发展，昆虫和哺乳动物大脑导航机理启发下的感知/认知/路径规划/动作决策一体化类脑导航技术得到了较大发展，可以实现由原始感知信息输入到导航动作决策的直接输出，呈现出接近动物端到端面向目标导航的智能行为，具有提高密集型无人机集群导航鲁棒性、准确性、实时响应动作、自主智能性以及计算效率的潜力。阐述了昆虫和哺乳动物大脑导航机理及其互补对称关系，以及昆虫和哺乳动物大脑导航机理启发的端到端类脑导航技术内涵；论述了类脑导航技术研究进展，包括类脑环境感知、类脑空间认知、面向目标类脑导航；分析了类脑导航向智能化、神经形态系统以及群体导航发展的新趋势；最后讨论了类脑导航技术应用于无人机密集集群系统时存在的挑战。     

Determination of optimal samples for robot calibration based on error similarity

Industrial robots are used for automatic drilling and riveting.The absolute position accuracy of an industrial robot is one of the key performance indexes in aircraft assembly,and can be improved through error compensation to meet aircraft assembly requirements.The achievable accuracy and the difficulty of accuracy compensation implementation are closely related to the choice of sampling points.Therefore,based on the error similarity error compensation method,a method for choosing sampling points on a uniform grid is proposed.A simulation is conducted to analyze the influence of the sample point locations on error compensation.In addition,the grid steps of the sampling points are optimized using a statistical analysis method.The method is used to generate grids and optimize the grid steps of a Kuka KR-210 robot.The experimental results show that the method for planning sampling data can be used to effectively optimize the sampling grid.After error compensation,the position accuracy of the robot meets the position accuracy requirements.     

某圆周缝型救生伞的充气性能研究

为获得新型圆周缝结构救生伞的充气性能,文章采用任意拉格朗日欧拉流固耦合方法对该救生伞进行了充气过程的数值模拟,用空投试验结果验证了该数值方法的可行性。数值结果得到了绕伞衣流场、伞衣外形、运动的动态信息,对数值结果的分析发现初始充气阶段后期流场对上部伞衣影响很大,为充气过程中上部伞衣的控制提供了依据,但是初始充气期救生伞的摆动角度小于充满期。对于结构透气量不对称设计的伞衣,不对称充气是绝对的,圆周缝会首先在结构透气量少的部位张开。结果表明,对不同的圆周缝节点设计不同的开缝力将有助于保持良好的对称充气状态,改变开缝力的设计参数将会改变圆周缝的开缝时间及圆周缝完全张开所需的时长,将达到更好的减载效果。研究结果对圆周缝型降落伞的优化设计有一定的参考作用。     

基于Hashin准则的直升机复合材料波纹梁耐撞性分析

对低速冲击作用下直升机复合材料波纹梁的吸能能力进行数值模拟分析。在分析中摒弃了在已有分析中将层合板复合材料简化成理想弹塑性材料的假设,建立了考虑实际铺层结构的复合材料波纹梁的有限元分析模型。采用Hashin失效准则对层合板单元的损伤进行判断,并按照相应的损伤形式对单元刚度进行了相应的折减。基于ABAQUS软件编写了VUMAT材料子程序,实现层合板单元的损伤判定和失效单元的刚度折减。计算结果和试验结果的对比分析结果表明,有限元模拟与试验结果有着良好的一致性,验证了分析方法的有效性。     

气膜孔内局部堵塞对气膜冷却特性的影响

在吹风比为0.3~1.5,堵塞比为0.1~0.5范围内,对平板上单排倾斜气膜孔内局部堵塞所引起的冷气射流流动和冷却特性变化进行了数值研究,分析了堵塞比、堵塞位置和吹风比对绝热气膜冷却效率的影响.在研究参数范围内的研究结果表明:气膜孔出口端前缘的局部堵塞有利于抑制肾形涡,对气膜孔下游的绝热气膜冷却效率有改善作用,并且随着堵塞比和吹风比的增加,对冷却效果的改善越为明显.而在气膜孔出口端尾缘或侧边的堵塞则在较大的堵塞比下削弱气膜冷却效果.相对于气膜孔出气端的局部堵塞,在气膜孔进气端和中部的堵塞对绝热气膜冷却效率的影响要微弱得多.     

A salient edges detection algorithm of multi-sensor images and its rapid calculation based on PFCM kernel clustering

Multi-sensor image matching based on salient edges has broad prospect in applications, but it is difficult to extract salient edges of real multi-sensor images with noises fast and accurately by using common algorithms. According to the analysis of the features of salient edges, a novel salient edges detection algorithm and its rapid calculation are proposed based on possibility fuzzy C-means （PFCM） kernel clustering using two-dimensional vectors composed of the values of gray and texture. PFCM clustering can overcome the shortcomings that fuzzy C-means （FCM） cluster- ing is sensitive to noises and possibility C-means （PCM） clustering tends to find identical clusters. On this basis, a method is proposed to improve real-time performance by compressing data sets based on the idea of data reduction in the field of mathematical analysis. In addition, the idea that kernel-space is linearly separable is used to enhance robustness further. Experimental results show that this method extracts salient edges for real multi-sensor images with noises more accurately than the algorithm based on force fields and the FCM algorithm; and the proposed method is on average about 56 times faster than the PFCM algorithm in real time and has better robustness.     

Optimization of beamforming and path planning for UAV-assisted wireless relay networks

Recently, unmanned aerial vehicles （UAVs） acting as relay platforms have attracted considerable attention due to the advantages of extending coverage and improving connectivity for long-range communications. Specifically, in the scenario where the access point （AP） is mobile, a UAV needs to find an efficient path to guarantee the connectivity of the relay link. Motivated by this fact, this paper proposes an optimal design for beamforming （BF） and UAV path planning. First of all, we study a dual-hop amplify-and-forward （AF） wireless relay network, in which a UAV is used as relay between a mobile AP and a fixed base station （BS）. In the network, both of the AP and the BS are equipped with multiple antennas, whereas the UAV has a single antenna. Then, we obtain the output signal~to-noise ratio （SNR） of the dual-hop relay network. Based on the criterion of maximizing the output SNR, we develop an optimal design to obtain the solution of the optimal BF weight vector and the UAV heading angle. Next, we derive the closed-form outage probability （OP） expression to investigate the performance of the dual-hop relay network conveniently. Finally, computer simulations show that the proposed approach can obtain nearly optimal flying path and OP performance, indicating the effectiveness of the proposed algorithm. Furthermore, we find that increasing the antenna number at the BS or the maximal heading angle can significantly improve the performance of the considered relay network.     

含噪信号经验模式分解虚假分量识别方法

针对含噪信号Hilbert-Huang变换存在虚假分量,提出改进的奇异值分解(SVD)方法进行降噪,改进包含两个部分:一是利用重构相空间代替传统矩阵如Hankel矩阵,以去掉信号冗余,再者提出奇异值能量熵分量差分法,更易于定出重构奇异值阶次;二是提出了频谱比值法对虚假分量进行辨识,更有效辨识出虚假分量.首先利用经验模式分解(EMD)得到本征模式分量(IMF),识别并剔除趋势项,重构信号,然后进行SVD,重构降噪后的信号,消除虚假分量,最后进行时频分析.联合方法应用于含噪仿真信号,信噪比(signal noise ratio,SNR)提高了5.5%,虚假分量辨识率提高至100%,用于双跨转子故障振动信号,得到正确的时频结果,表明了所提方法识别含噪信号虚假分量的有效性.