Reliable flight performance assessment of multirotor based on interacting multiple model particle filter and health degree

Multirotor has been applied to many military and civilian mission scenarios. From the perspective of reliability, it is difficult to ensure that multirotors do not generate hardware and software failures or performance anomalies during the flight process. These failures and anomalies may result in mission interruptions, crashes, and even threats to the lives and property of human beings. Thus, the study of flight reliability problems of multirotors is conductive to the development of the drone industry and has theoretical significance and engineering value. This paper proposes a reliable flight performance assessment method of multirotors based on an Interacting Multiple Model Particle Filter (IMMPF) algorithm and health degree as the performance indicator. First, the multirotor is modeled by the Stochastic Hybrid System (SHS) model, and the problem of reliable flight performance assessment is formulated. In order to solve the problem, the IMMPF algorithm is presented to estimate the real-time probability distribution of hybrid state of the established SHS-based multirotor model, since it can decrease estimation errors compared with the standard interacting multiple model algorithm based on extended Kalman filter. Then, the reliable flight performance is assessed with health degree based on the estimation result. Finally, a case study of a multirotor suffering from sensor anomalies is presented to validate the effectiveness of the proposed method.     

Vision-based bio-inspired guidance law for small aerial vehicle

During predation, a flying insect can form a stealth flight path. This behavior is called motion camouflage. Based on the study results of this behavior, the perception and neurology of flying insects, a novel bio-inspired guidance law is proposed for the terminal guidance for small aerial vehicle with charge-coupled device imaging seekers. The kinematics relationship between a small aerial vehicle and target is analyzed, and a two-dimensional guidance law model is established by using artificial neural networks. To compare with the proportional guidance law, the numerical simulations are carried out in the vertical plane and in the horizontal plane respectively. The simulation results show that the ballistic of the small aerial vehicle is straighter and the normal acceleration is smaller by using the bio-inspired guidance law than by using the proportional guidance law. That is to say, the bio-inspired guidance law just uses the information of the target from the imaging seeker,but the performance of it can be better than that of the proportional guidance law.     

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.     

基于ANSYS的机翼动力学分析

针对无人机在挂载导弹飞行和发射导弹时,无人机机翼由于受到多种载荷影响所产生的应力应变,应用ANSYS软件动力学分析,计算模拟了机翼在受到多种载荷影响时所产生的应力分布和应变量。分析结果表明,由于外挂物重量和机翼周围气动流场的影响,机翼会产生不同程度的颤振和扭转,其研究结果对合理设计机翼结构具有一定的参考意义。     

硬质合金电火花加工工艺实验研究

针对硬质合金模具的加工表面精度要求,进行了高速钢与硬质合金两种材料的电火花加工工艺对照实验。为获得较低的表面粗糙度,选取了较小的电加工参数。实验结果表明,在该实验条件下,电火花加工的表面粗糙度不再满足常规条件下的经验公式,而与工件材料的再凝结特征、成分及电蚀产物的排出条件有关。     

高速飞行器热结构工作时变模态参数辨识

高速飞行器由于其很高的飞行速度而无可避免地受到气动加热作用的影响,进而引起结构特性的时变。采用理论或有限元方法(FEM)进行数值分析,难以获取反映结构在飞行(工作)状态下的真实模态参数。通过辨识获取高速飞行器热环境下的时变结构模态参数是一项十分具有挑战性的任务。针对此问题,引入参数化时频域的最大似然方法,对气动加热作用下的高速飞行器升力面结构的时变模态参数进行了辨识。通过模拟真实飞行状态的数值算例研究,说明参数化时频域的最大似然方法能够很好地辨识出低信噪比(SNR)情况下的模态频率和模态振型,验证了参数化时频域最大似然方法适用于具有显著时变特征的高速飞行器热结构的时变结构模态参数辨识,可为将来相关的工程研究和应用提供良好的理论支持。     

CamShift在加油锥套识别跟踪中的应用

针对插头锥套式自主空中加油过程中加油锥套的识别跟踪问题,提出了一种基于Cam Shift的视觉识别跟踪算法。选取加油锥套跟踪视觉特征,将RGB空间图像转换到HSV色彩空间,并采用自适应阈值算法分割图像。运用最小二乘椭圆拟合算法解算锥套在图像中的中心点坐标;根据目标像素位置变换速度,对Mean Shift算法的目标搜索窗宽进行自适应修正;定义基于巴氏系数的阈值函数,处理锥套被遮挡的情况;将VC与Open CV相结合,设计了加油锥套视觉跟踪软件,对锥套位置进行实时解算和显示。试验结果表明,该算法可达到毫米级精度,满足自主空中加油视觉导航的技术要求。     

用凝固模拟方法预测铝合金铸件缩松的形成

用有限元法和六节点等参数单元对铝合金金属型铸造过程进行了温度场的数值模拟，对铸件不同典型部位进行了金相分析，结果表明，参数Ｇ／可有效地预测铝合金缩松形成倾向的大小，计算值与实测值基本一致。     

Pro／ENGINEER在模具设计中的使用技巧

分析了Pro／ENGINEER进行模具设计的使用技巧，阐明了并行工程技术与Pro／ENGINEER软件相结合的重要性。     

A new modeling scheme for powered parafoil unmanned aerial vehicle platforms: Theory and experiments

A novel framework is established for accurate modeling of Powered Parafoil Unmanned Aerial Vehicle (PPUAV). The model is developed in the following three steps: obtaining a linear dynamic model, simplifying the model structure, and estimating the model mismatch due to model variance and external disturbance factors. First, a six degree-of-freedom linear model, or the structured model, is obtained through dynamic establishment and linearization. Second, the data correlation analysis is adopted to determine the criterion for proper model complexity and to simplify the structured model. Next, an active model is established, combining the simplified model with the model mismatch estimator. An adapted Kalman filter is utilized for the real-time estimation of states and model mismatch. We finally derive a linear system model while taking into account of model variance and external disturbance. Actual flight tests verify the effectiveness of our active model in different flight scenarios.