无人机群体视角下的轨迹预测CSCD

利用无人机对观测目标的运动轨迹进行预测是当前无人系统领域的关键任务之一。目前的目标轨迹预测研究通常基于单一无人机所采集的轨迹数据,但由于场景中障碍物以及视角倾斜等因素的影响,单无人机不易稳定监测目标具体位置,容易导致目标丢失。而且,现有利用无人机的目标轨迹预测一般基于鸟瞰视角,没有发挥出无人机的灵活性。随着无人机集群协同技术的发展,无人机群体视角为目标全方位监测提供了新的思路,在解决目标丢失和目标遮挡问题中具有明显的优势。同时,基于多无人机的位姿估计可以估计出目标的准确三维坐标,为无人机的灵活视角观测提供基础。因此,从轨迹预测的相关工作出发,探讨无人机群体视角下轨迹预测中面临的挑战和解决思路,以期对未来的轨迹预测研究以及集群协同技术发展提供一定帮助。     

Experimental study on transfer functions of an active rotor under different flight conditions

Vibrations impose negative impacts on the effectiveness and public acceptance of helicopters. Active rotors with trailing-edge flaps have been proved to be an effective way to actively eliminate helicopter vibrations. For the existing control algorithm based on offline system identification, the transfer functions of an active rotor under different flight conditions are pre-requisites to implement closed-loop vibration control. In this study, a three-bladed active rotor with improved trailing-edge flaps is designed, and wind-tunnel tests are conducted to identify the transfer functions of this active rotor using frequency sweep and phase sweep methods. The experimental results demonstrate that these transfer functions are insensitive to the variation of flight speeds: the amplitude of the transfer function varies slightly, while the phase delay almost remains unchanged. In addition, this finding is validated through closed-loop vibration control tests with the active rotor. The transfer function obtained from the hover test results is also applicable to closed-loop vibration control tests under the forward flight conditions. This will dramatically simplify the implementation and operation of an active rotor.     

Vector deflection stability control of aero-engine based on linear active disturbance rejection

Aimed at the problem of instability in engine control caused by vector deflection in experiment of turbofan engines with Axisymmetric Vectoring Exhaust Nozzle (AVEN), a vector deflection stability control method of aero-engine based on Linear Active Disturbance Rejection Control (LADRC) is proposed. Firstly, based on CFD numerical simulation, aerodynamic performance model of AVEN is established, and the aerodynamic load change rule of the nozzle throat area actuator during vector deflection is revealed. Subsequently, the integrated model of AVEN/turbofan engine is established by Simulink/AMESim co-simulation. Finally, the nozzle throat area control loop based on LADRC is designed. The simulation results show that the integrated model can reflect the influence of vector deflection on the stability of the control system. The accuracy comparison between the fan rotor speed and the test data during vector deflection is larger than 1%, indicating a high degree of confidence. Compared with the conventional PID control, the designed LADRC control loop reduces the speed of the low-pressure rotor during vector deflection by 70%, which effectively improves the control stability of the vector deflection. Meanwhile, the fuel flow ratechange during the vector deflection process is smaller and more economical, which provides an important reference for engineering applications.     

A high-safety active/passive hybrid control approach for compressor surge based on nonlinear model predictive control

Surge active control can expand the stable operating range of the compressor. However, the difficulty of flow measurement, dynamic uncertainty disturbance, actuator delay characteristics, hard constraints of control variable, and system security measures have not been fully considered in the existing active control system, which significantly hinders its engineering application. Therefore, a nonlinear model predictive surge active control method is first presented based on flow estimator designed by using a continuous-time Kalman filter for dealing with the hard constraint of control variable and the impact of actuator delay of compression system with dynamic uncertainty. Then, a high-safety active/surge passive hybrid control strategy is designed, dominated by the surge active control and supplemented by the surge passive control, to ensure the compression system’s safe and stable operation. Lastly, the simulation results suggest that the flow estimator accurately estimates the compressor flow. When considering the delay impact of the actuators and sensors and measurement noise on the system, the proposed method exhibits stronger robustness than the existing methods. The active/surge passive hybrid control strategy can successfully ensure the compression system's safe and stable operation. This paper is of high practical significance for the engineering application of future compressor surge active control technologies.     

基于改进式YOLOv2的红外图像目标识别方法

针对智能化导引头信息处理算法设计验证需求，本文对多类型目标、海陆空背景辐射特性数据进一步挖掘，提出引入深度学习算法应用于外场红外数据二次分析挖掘的方法。选择采集得到的包括车、船、无人机(UAVs)、客机等类型的红外数据，针对红外图像与可见光图像不同的成像特性，利用改进式YOLOv2红外目标检测与分类算法，融合多级特征，增加一个重组特征图，实现对红外弱小目标智能化快速分类研究，对提取的海量视频库中的目标红外辐射特征进行分类整理。     

Space law education in China: Status quo,shortcomings and possible ways out

Space law education has an essential role in the space capacity building of a country because of its importance for human resources development in space law. Comparisons between Canada and China, the European Union and China and the United States of America (USA) and China in space law degree education, course, teaching methodology, institute and practice and communication platform are provided in an attempt to review some issues which exist within the Chinese space law educational system and to seek a better choice for China’s space law education reform. Chinese space law education has achieved noticeable progress over the past two decades. However, it is still limited in comparison to its counterparts in Europe and Northern America. The range of the space law degree education programmes and space-law-related courses is comparatively limited. A gap remains between space law education and practice in China. Chinese space law classes are still dominated by the teacher-centred teaching methodology, although several universities have some new teaching practices. The establishment of seven space law-related research institutes plays an increasingly important role in Chinese space law education, space law and policy research and legal advisory services for the Chinese government and non-governmental sectors. However, these institutes still have a long way to go in comparison with their counterparts in Europe and Northern America. While China has established domestic research platforms for space law communication through international cooperation, it does not provide space law practice platforms for space law education. While international space law does not provide a direct legal foundation for space law education in China, Chinese educational laws can lay a profound legal foundation for Chinese space law education. To promote its national expertise and capacity in space law, based on the three-pillar model and the experiences of its counterparts in North America and Europe, China should adopt a systematic and sustainable regime for its space law education.     

Improving multi-target cooperative tracking guidance for UAV swarms using multi-agent reinforcement learning

Multi-Target Tracking Guidance(MTTG) in unknown environments has great potential values in applications for Unmanned Aerial Vehicle(UAV) swarms. Although Multi-Agent Deep Reinforcement Learning(MADRL) is a promising technique for learning cooperation, most of the existing methods cannot scale well to decentralized UAV swarms due to their computational complexity or global information requirement. This paper proposes a decentralized MADRL method using the maximum reciprocal reward to learn cooper...     

Cooperative differential games guidance laws for multiple attackers against an active defense target

This paper is concerned with a scenario of multiple attackers trying to intercept a target with active defense. Three types of agents are considered in the guidance: The multiple attackers, the target and the defender, where the attackers aim to pursuit the target from different directions and evade from the defender simultaneously. The guidance engagement is formulated in the framework of a zero-sum two-person differential game between the two opposing teams, such that the measurements on the m...     

集群多机器人系统建模研究的发展与展望

凭借高效、鲁棒、应用广泛的特性,集群多机器人系统已经成为当今研究的热点课题之一,具有重要的实用价值.首先简述了自顶而下和自底而上两种多机器人系统研究思路的当前研究概况.然后从拟生物集群系统模型引入,进而引出一致性系统模型,针对低阶、高阶、异质、时延等一致性模型进行分析总结,单独阐述了多智能体强化学习系统模型的研究情况,...     

Transfer learning: A new aerodynamic force identification network based on adaptive EMD and soft thresholding in hypersonic wind tunnel

The aerodynamic test in the pulse combustion wind tunnel is very important for the design, evaluation and optimization of aerodynamic characteristics of the hypersonic aircraft. The test accuracy even affects the success or failure of hypersonic aircraft development. In the aerodynamic test of pulse combustion wind tunnel, the aerodynamic signal is disturbed by the inertial force signal, which seriously affects the test accuracy of aerodynamic force. Aiming at the above problems, this paper innovatively proposes an aerodynamic intelligent identification method, that is the transfer learning network based on adaptive Empirical Modal Decomposition (EMD) and Soft Thresholding (TLN-AE&ST). Compared with the existing aerodynamic intelligent identification model based on deep learning technology, this study introduces the transfer learning idea into the aerodynamic intelligent identification model for the first time. The TLN-AE&ST effectively alleviates the problem of scarcity of training samples for intelligent models due to the high cost of wind tunnel tests, and provides a new idea for further implementation of deep learning technology in the field of wind tunnel aerodynamic testing. And this study designed residual attention block with soft threshold and dense block with adaptive EMD in TLN-AE&ST model. Residual attention block with soft threshold module can more effectively suppress the influence of instrument noise signal on model training effect. Dense block with adaptive EMD makes the deep learning model no longer a black box to a certain extent, and has certain physical significance. Finally, a series of wind tunnel tests were carried out in the Φ = 2.4 m pulse combustion wind tunnel of China Aerodynamic Research and Development Center to verify the effectiveness of TLN-AE&ST.