Distributed UAV swarm based on spatial grid model

Unmanned Aerial Vehicle (UAV) swarm has become the inevitable trend of development, which will enjoy broad prospects to be applied in the future. However, the change of UAV application mode will certainly bring new technical challenges in the flight management, environmental perception, collaborative control as well as other fields. This paper considers that it can be an effective solution to realize the unified management of spatial information on the UAV platform by adopting the spatial grid model represented by the GeoSOT-3D, and to reduce the workload of flight management, airborne environmental perception, and ranging in the neighborhood through the association and query of all spatial grid data.     

考虑观测的双冲量最优交会研究

针对跟踪星主动交会目标星的轨道转移问题,给出了考虑观测的双冲量最优交会迭代算法。首先对考虑观测的轨道交会问题进行了分析,给出了椭圆转移轨道的存在性判定方法。在此基础上,给出了基于粒子群的优化求解方案。经过对两异面椭圆轨道转移问题的仿真解算,求得了最优交会轨道,验证了算法的正确性。该研究成果可作为工程应用的有益参考,并为其他带约束的轨道交会优化问题提供可行的求解方案。     

空间大型机械臂系统载运轨迹优化方法

针对在搬运及组装数十吨级负载过程中,空间站用大型机械臂会对空间站载体姿态产生扰动的问题,提出了一种笛卡尔轨迹参数化方法。利用基于广义雅克比矩阵（GJM）的分解运动速度控制和优化算法来实现基座姿态扰动控制,建立了反映载体姿态变化的目标函数。基于关节运动范围及避免动力学奇异等约束,采用粒子群（PSO）算法进行目标函数的优化,有效降低了空间大型机械臂系统在搬运重型负载过程中对载体姿态的影响。仿真结果验证了算法的有效性。     

Comprehensive optimization design of aerodynamic and electromagnetic scattering characteristics of serpentine nozzle

Comprehensive optimization design of serpentine nozzle with trapezoidal outlet was studied to improve its aerodynamic and electromagnetic scattering performance. Serpentine nozzles with different center offsets and different ratios of the bases of the trapezoidal outlet were generated based on curvature control regulation. Computational Fluid Dynamics (CFD) simulations have been conducted to obtain the flow field in the nozzle, and Forward-Backward Iterative Physical Optics (FBIPO) method was applied to study the electromagnetic scattering characteristics of the nozzle. Guarantee Convergence Particle Swarm Optimization (GCPSO) algorithm based on Radial Basis Function (RBF) neural network was used to optimize the geometry of the nozzle in consideration of its aerodynamic and electromagnetic scattering characteristics. The results show that the GCPSO method based on RBF can be used to optimize the aerodynamic characteristics of the internal flow and the scattering characteristics of the cavity of the serpentine nozzle with irregular outlet. The optimized model has a higher center offset and a lower ratio of the bases of the trapezoidal outlet after optimization compared to the original model. The optimized model leads to a slight change in aerodynamic performance, with a total pressure recovery coefficient increase of 0.31% and a discharge coefficient increase of 0.41%. In addition, the Radar Cross Section (RCS) decreases also by around 83.33% and the overall performance is significantly improved, with a decrease of the optimized objective function by around 38.74%.     

Dynamic neighborhood genetic learning particle swarm optimization for high-power-density electric propulsion motor

To maximize the power density of the electric propulsion motor in aerospace application, this paper proposes a novel Dynamic Neighborhood Genetic Learning Particle Swarm Optimization (DNGL-PSO) for the motor design, which can deal with the insufficient population diversity and non-global optimal solution issues. The DNGL-PSO framework is composed of the dynamic neighborhood module and the particle update module. To improve the population diversity, the dynamic neighborhood strategy is first proposed, which combines the local neighborhood exemplar generation mechanism and the shuffling mechanism. The local neighborhood exemplar generation mechanism enlarges the search range of the algorithm in the solution space, thus obtaining high-quality exemplars. Meanwhile, when the global optimal solution cannot update its fitness value, the shuffling mechanism module is triggered to dynamically change the local neighborhood members. The roulette wheel selection operator is introduced into the shuffling mechanism to ensure that particles with larger fitness value are selected with a higher probability and remain in the local neighborhood. Then, the global learning based particle update approach is proposed, which can achieve a good balance between the expansion of the search range in the early stage and the acceleration of local convergence in the later stage. Finally, the optimization design of the electric propulsion motor is conducted to verify the effectiveness of the proposed DNGL-PSO. The simulation results show that the proposed DNGL-PSO has excellent adaptability, optimization efficiency and global optimization capability, while the optimized electric propulsion motor has a high power density of 5.207 kW/kg with the efficiency of 96.12%.     

An intelligent approach for flight risk prediction under icing conditions

Flight risk prediction is significant in improving the flight crew’s situational awareness because it allows them to adopt appropriate operation strategies to prevent risk expansion caused by abnormal conditions, especially aircraft icing conditions. The flight risk space representing the nonlinear mapping relations between risk degree and the three-dimensional commanded vector(commanded airspeed, commanded bank angle, and commanded vertical velocity) is developed to provide the crew with practi...     

NeQuick2 validation using multi-satellite and ground data

Global Navigation Satellite System’s (GNSS) positioning calculation is prone to ionospheric errors. Single frequency GNSS users receive ionospheric corrections through broadcast ionospheric models. Therefore, the accuracy of ionospheric models must be validated based on various geographic and geomagnetic conditions. In this work, an attempt is made to validate NeQuick2 electron density (Ne) using multiple sources of space-based and ground-based data at the Arabian Peninsula and for low solar activity conditions. These sources include space-based data from Swarm, DMSP and COSMIC-2 satellite constellations and ground-based data from GNSS receiver and the ionosonde. The period of this study is 1 year from October 2019 to September 2020. Analysis shows that the agreement between NeQuick2 and experimental Ne close to the peak density height depends on seasons and time of the day with the largest errors found in Autumn and during the daytime. NeQuick2 generally overestimates Ne during the daytime. During the early morning and evening hours, Ne estimates seem to be fairly accurate with slight underestimation in Winter and Spring. Estimation of slab thickness by NeQuick2 is found to be close to the values calculated using collocated ionosonde and GNSS receiver.     

水面无人艇集群编队控制技术综述

随着海上作业任务的日渐复杂以及水面无人艇控制理论的发展，单水面无人艇航行控制能力的局限性逐渐显现，集群编队控制技术得到了广泛关注。针对水面无人艇集群编队控制技术，分析了当前国内外应用情况与技术研究现状，重点从典型编队队形适用性、编队控制系统结构形式、编队协同控制方法、编队控制通信技术及异构条件下协同控制技术等方面分析了水面无人艇集群编队控制技术的研究进展。最后，进行了总结和展望，以期为水面无人艇集群编队控制技术的研究提供有益的参考。     

Precise orbit determination and baseline consistency assessment for Swarm constellation

Precise orbit determination (POD) and precise baseline determination (PBD) of Swarm satellites with 4 years of data are investigated. Ambiguity resolution (AR) plays a crucial role in achieving the best orbit accuracy. Swarm POD and PBD based on single difference (SD) AR and traditional double difference (DD) AR methods are explored separately. Swarm antenna phase center variation (PCV) corrections are developed to further improve the orbit determination accuracy. The code multipath of C1C, C1W and C2W observations is first evaluated and clear variations in code noise related to different receiver settings are observed. Carrier phase residuals of different time periods and different loop tracking settings of receiver are studied to explore the effect of ionospheric scintillation on POD. The reduction of residuals in the polar and geomagnetic equator regions confirms the positive impact of the updated carrier tracking loops (TLs) on POD performance. The SD AR orbits and orbits with float ambiguity (FA) are compared with the Swarm precise science orbits (PSOs). An average improvement of 27 %, 4 % and 16 % is gained in along-track, cross-track and radial directions by fixing the ambiguity to integer. For Swarm-A/B and Swarm-B/C formations, specific days are selected to perform the DD AR-based POD during which the average distance of the formation satellites is less than 5000 km. Satellite laser ranging (SLR) observations are employed to validate the performance of FA, SD AR and DD AR orbits. The consistency between the SD AR orbits and SLR data is at a level of 10 mm which shows an improvement of 25 % when comparing with the FA results. An SLR residuals reduction of 15 % is also achieved by the DD AR solution for the selected days. Precise relative navigation is also an essential aspect for spacecraft formation flying missions. The closure error method is proposed to evaluate the baseline precision in three dimensions. A baseline precision of 1–3 mm for Swarm-A/C formation and 3–5 mm for Swarm-A/B and Swarm-B/C satellite pairs is verified by both the consistency check and closure error method.     

Fractional order adaptive robust formation control of multiple quad-rotor UAVs with parametric uncertainties and wind disturbances

In recent times, multiple Unmanned Aerial Vehicles (UAVs) are being widely utilized in several areas of applications such as agriculture, surveillance, disaster management, search and rescue operations. Degree of robustness of applied control schemes determines how accurate a swarm of UAVs accomplish group tasks. Formation and trajectory tracking controllers are required for the swarm of multiple UAVs. Factors like external environmental effects, parametric uncertainties and wind gusts make the controller design process as a challenging task. This article proposes fractional order formation and trajectory tacking controllers for multiple quad-rotors using Super Twisting Sliding Mode Control (STSMC) technique. To compensate the effects of the disturbances due to parametric uncertainties and wind gusts, Lyapunov function based adaptive controllers are formulated. Moreover, Lyapunov theorem is used to guarantee the stability of the proposed controllers. Three types of controllers, namely fixed gain STSMC and fractional order Adaptive Super Twisting Sliding Mode Control (ASTSMC) methods are tested for the swarm of UAVs by performing the numerical simulations in MATLAB/Simulink environment. From the presented results, it is verified that in presence of wind disturbances and parametric uncertainties, the proposed fractional order ASTSMC technique showed improved robustness as compared to the fixed gain STSMC and integer order ASTSMC.