Design and experimental study of a new flapping wing rotor micro aerial vehicle

A three-wing Flapping Wing Rotor Micro Aerial Vehicle (FWR-MAV) which can perform controlled flight is introduced and an experimental study on this vehicle is presented. A mechanically driven flapping rotary mechanism is designed to drive the three flapping wings and generate lift, and control mechanisms are designed to control the pose of the FWR-MAV. A flight control board for attitude control with robust onboard attitude estimation and a control algorithm is also developed to perform stable hovering flight and forward flight. A series of flight tests was conducted, with hovering flight and forward flight tests performed to optimize the control parameters and assess the performance of the FWR-MAV. The hovering flight test shows the ability of the FWR-MAV to counteract the moment generated by rotary motion and maintain the attitude of the FWR-MAV in space; the experiment of forward flight shows that the FWR-MAV can track the desired attitude.     

Reliability estimation of rotary lip seal in aircraft utility system based on time-varying dependence degradation model and its experimental validation

With several attractive properties, rotary lip seals are widely used in aircraft utility system, and their reliability estimation has drawn more and more attention. This work proposes a reliability estimation approach based on time-varying dependence analysis. The dependence between the two performance indicators of rotary lip seals, namely leakage rate and friction torque, is modeled by time-varying copula function with polynomial to denote the time-varying parameters, and an efficient copula selection approach is utilized to select the optimal copula function. Parameter estimation is carried out based on a Bayesian method and the reliability during the whole lifetime is calculated based on a Monte Carlo method. Degradation test for rotary lip seal is conducted and the proposed model is validated by test data. The optimal copula function and optimal order of polynomial are determined based on test data. Results show that this model is effective in estimating the reliability of rotary lip seals and can achieve a better goodness of fit.     

A multi-constraints based pose coordination model for large volume components assembly

In the assembly process of large volume product, engineering constraints limit the relative pose of components and serve as a standard for judging assembly quality. However, in the traditional process of target pose estimation, a general method is needed for establishing the correlation between engineering constraints and product pose, and it is difficult to evaluate pose by constraints comprehensively. Therefore, the process of target pose estimation and evaluation is separated. In this paper, a pose coordination model based on multi-constraints is proposed, which includes pre-processing, pose estimation, pose adjustment and evaluation. Firstly, engineering constraints are decoupled into 4 types of Minimum Geometrical Reference Constraints (MGRC), and the inequalities for solving target pose are formulated. Then the Constraint Coordination Index (CCI) is defined as the optimization objective to solve the target pose. Finally, with CCI as the numerical index, the target pose is evaluated to illustrate the quality of assembly. Taking the simulation experiment of wing-fuselage jointing as an example, the external and internal parameters of model are analyzed, and the pose estimation based on multi-constraints reduces the CCI by 12%, compared with the point-set-registration method.     

风电场雷达杂波动态重构抑制方法

随着风电场的大范围建设，风轮机杂波对雷达的干扰问题日益严重，常规杂波抑制方法难以有效解决风轮机杂波（WTC）干扰问题，因此提出了一种利用动态字典对风轮机杂波进行稀疏重构进而抑制的方法。首先，建立了WTC干扰下的雷达信号模型并分析了风轮机杂波的信号特征。其次，依据WTC的时频特征提出了一种微动参数粗估计方法，利用粗估计结果缩小了字典稀疏重构参数范围，在此基础上利用正交匹配追踪（OMP）算法对字典进行动态生成，并逐级更新字典原子。最后，通过动态字典对风轮机杂波信号进行稀疏重构，从而实现了对WTC的有效抑制。通过仿真实验，分析了风轮机杂波对目标检测的干扰影响，验证了基于动态稀疏重构的风电场杂波抑制方法在不同情况下的有效性。     

A multilayer perceptron and multiclass support vector machine based high accuracy technique for daily rainfall estimation from MSG SEVIRI data

The current paper introduces a new multilayer perceptron (MLP) and support vector machine (SVM) based approach to improve daily rainfall estimation from the Meteosat Second Generation (MSG) data. In this study, the precipitation is first detected and classified into convective and stratiform rain by two MLP models, and then four multi-class SVM algorithms were used for daily rainfall estimation. Relevant spectral and textural input features of the developed algorithms were derived from the spectral MSG SEVIRI radiometer channels. The models were trained using radar rainfall data set colected over north Algeria. Validation of the proposed daily rainfall estimation technique was performed by rain gauge network data set recorded over north Algeria. Thus, several statistical scores were calculated, such as correlation coefficient (r), root mean square error (RMSE), mean error (Bias), and mean absolute error (MAE). The findings given by: (r = 0.97, bias = 0.31 mm, RMSE = 2.20 mm and MAE = 1.07 mm), showed a quite satisfactory relationship between the estimation and the respective observed daily precipitation. Moreover, the comparison of the results with those of two advanced techniques based on random forests (RF) and weighted ‘k’ nearest neighbor (WkNN) showed higher accuracy obtained by the proposed model.     

Real-time sensor fault detection and isolation for LEO satellite attitude estimation through magnetometer data

Attitude estimation is a critical component of the Attitude Determination and Control System (ADCS) of any satellite. It is used to convert the sensor observation data to an estimated attitude using filtering algorithms. However, in the presence of sensor faults, the ADCS fails to achieve the desired attitude accuracy. In this paper, the Fault Tolerant Extended Kalman Filter (FTEKF) is proposed to handle this imperfection. In accordance, various filtering steps are included in the FTEKF design to enhance both attitude estimation and sensor fault detection. The developed algorithm can detect and isolate any unexpected sensor faults in real time, which provides a reliable attitude estimation. A comparative study with the classical and robust Kalman filters is performed through numerical simulations in order to validate the effectiveness of the adopted filter in case of magnetometer fault data.     

地基光学图像中本体-帆板结构航天器姿态估计方法

提出一种利用地基光学图像估计空间目标姿态的方法。针对本体-帆板结构航天器外形结构特点，定义了一种不易遮挡的两轴结构特征，设计了地基光学图像中该特征的提取方法；根据航天器成像过程建立了特征点二三维几何投影方程，实现了航天器三维姿态的解算。利用单站序列图像，可获得航天器姿态变化角速度信息。在轨航天器的试验结果表明，本方法能有效地从地基光学图像估计出航天器姿态。     

考虑跟踪性能约束的近空间飞行器控制器设计

针对一类可变后掠角的近空间飞行器(NSV)指令跟踪问题，考虑其受到外界扰动及参数不确定的影响，同时考虑系统的跟踪性能约束及姿态角速度约束，提出了一种基于模糊系统的切换控制器设计方法，确保系统在扰动影响以及给定约束下能够对给定信号进行稳定跟踪。建立了包含未知扰动及不确定项的近空间飞行器非线性切换模型；通过设计模糊系统对系统所受的总干扰进行实时估计，并基于反步法进行了切换控制器设计，在控制器中对干扰进行补偿；通过公共Barrier Lyapunov方法对系统稳定性及动态性能进行了分析。数值仿真算例校验了所提出方法的有效性及优越性。     

State and disturbance estimation for test masses of drag-free satellites based on self-recurrent wavelet neural network

In recent years, the drag-free satellites have been widely used for some fundamental physical experiments, such as checking short-range effects of general relativity, geopotential determination and the exploration of static ocean current. And the space-borne detector of gravitational waves is one of the important applications for drag-free satellites in the future. In this study, the estimation of relative motion state and disturbance for test masses of drag-free satellite after release are researched. Firstly, the relative motion model between the test masses is established based on corresponding reference frames. Secondly, a self-recurrent wavelet neural network estimator is designed to estimate the pure gravitational relative motion state and disturbance for the test masses, and the sliding mode controller is used to transfer the relative motion state to the ideal state. Finally, the proposed estimation methods are verified by the simulation results.     

Modeling spatial density in low earth orbits using wavelets and random search

The events that occurred after 2007 such as Chinese anti-satellite test, explosion of Briz-M upper stage, break up of cosmos-2421 and collision of cosmos-2251 with Iridium-33 satellites have completely changed the spatial density patterns in low earth orbits. This has increased the risk of collision between active satellites and debris created by them. Aftermath, the risk assessment of possible collisions called as conjunction analysis of working satellites from day to day has become more crucial. Spatial density models are useful in understanding the long-term likelihood of a collision in a particular region of space and helpful in pre-launch orbit planning. In this paper we present an algorithmic procedure for automatically estimating exact model parameters corresponding to the peak location and number of peaks using wavelets that will speed up the parameter estimation process for the models with peaks.