System-level prognostics approach for failure prediction of reaction wheel motor in satellites

The reaction wheels actuated by motors are widely used for advanced attitude control of satellites. During the satellite operation, the performance of reaction wheel motor degrades and results in unexpected failures. To guarantee the reliability and safety of satellites, it is important to predict its remaining useful life while it is in operation. To address this issue, this study presents a system-level prognostics approach for the reaction wheel motor, by regarding it as a system composed of multiple components. The approach is demonstrated by using the motor operation data obtained during the accelerated-life tests on ground for 3 years. Health degradation of each components of the motor are estimated using the adaptive extended Kalman filter. Failure threshold of the motor performance is established by the design requirement on characteristic curve. The anomaly detection and failure prediction are performed using the shifting kernel particle filter.     

遥感卫星多路数据传输系统同频共用方法

为节省频率资源，遥感卫星通常采用扩频体制实现多路数据的同频共用传输，针对通道间容易引起相互干扰的问题进行了研究，通过改进码分多址干扰估算模型，对采用平衡Gold码序列扩频系统抗干扰容限上界进行预测。在满足国际电信联盟（ITU）对卫星辐射功率通量密度约束条件下，提出了一种基于直接序列扩频体制的两路业务数据同频共用传输方法。仿真结果表明：当载波频率2GHz左右，两路辐射源的EIRP之差不大于8～15dBw时可以实现同频共用传输；如对信号扩频带宽进行差异化处理，则其相互兼容性还可进一步提高。     

导弹滑模抗干扰自动驾驶仪设计

针对拦截弹的抗干扰控制问题，设计了一种基于扩张状态观测器和快速滑模控制的三通道自动驾驶仪。首先建立考虑有界未知不确定性和外界干扰的拦截弹系统模型，构建扩张状态观测器对有界未知不确定性和外界干扰进行估计；在此基础上，根据自动驾驶仪系统特性，设计了一种快速滑模控制算法使得系统在受到有界未知不确定性和外界干扰的情况下仍然能精准快速跟踪指令信号，并基于李雅普诺夫函数证明了其稳定性。仿真结果验证了所设计控制算法的有效性。     

SINS/GNSS integrated navigation system based on maximum versoria filter

In the missile-borne Strapdown Inertial Navigation System/Global Navigation Satellite System (SINS/GNSS) integrated navigation system, due to the factors such as the high dynamics, the signal blocking by obstacles, the signal intefereces, etc., there always exist pulse interferences or measurement information interruptions in the satellite receiver, which make nonstationary measurement process. The traditional Kalman Filter (KF) can tackle the state estimation problem under Gaussian white noise, but its performance will be significantly reduced under non-Gaussian noises. In order to deal with the non-Gaussian conditions in the actual missile-borne SINS/GNSS integrated navigation systems, a Maximum Versoria Criterion Extended Kalman Filter (MVC-EKF) algorithm is proposed based on the MVC and the idea of M-estimation, which assigns a smaller weight to the anomalous measurements so as to suppress the influence of anomalous measurements on the state estimation while maintaining a relatively low calculation cost. Finally, the integrated navigation simulation experiments prove the effectiveness and robustness of the proposed algorithm.     

Stationkeeping of halo orbits in Jupiter-Europa-Io system

Europa is one of the most promising exploration targets in search for extraterrestrial life. In the observation of Europa, halo orbits are suitable locations, because they are periodic and three-dimensional, and stationary with respect to Europa. However, halo orbits are naturally unstable and thus need stationkeeping. This study addresses the stationkeeping problem of halo orbits in the Jupiter-Europa system perturbated by another Galilean moon Io, in which case Io’s mass and orbital rate are assumed to be unknown. A tight stationkeeping scheme is proposed while accounting for autonomous navigation. To deal with the unknown gravitational perturbation from Io, the mass and orbital rate of Io are estimated during the flight and are then used to enhance the control robustness and stability, and improve the navigation accuracy. The control saturation problem is addressed by introducing adjustable parameters into the control law. The accuracy and error distribution of estimation is evaluated through Monte Carlo simulation.     

Autonomous mission reconstruction during the ascending flight of launch vehicles under typical propulsion system failures

In recent years, Chinese Long March(LM) launchers have experienced several launch failures, most of which occurred in their propulsion systems, and this paper studies Autonomous Mission Reconstruction(AMRC) technology to alleviate losses due to these failures. The status of the techniques related to AMRC, including trajectory and mission planning, guidance methods,and fault tolerant technologies, are reviewed, and their features are compared, which reflect the challenges faced by AMRC technology...     

基于自抗扰的无人机俯仰姿态控制

针对无人机俯仰姿态控制回路在模型参数和复杂外界环境等不确定性干扰影响下鲁棒性差、系统响应速度慢的问题,采用工程上易实现的自抗扰控制(ADRC)方法设计了俯仰姿态控制器,通过构造线性扩张状态观测器(LESO)估计不确定性干扰,并在控制回路中对干扰进行实时补偿.性能分析与仿真结果表明,基于ADRC的无人机俯仰姿态控制器具有良好的性能和干扰抑制能力,并且能够实现对控制指令的精确跟踪.     

基于固定阈值事件触发扩张状态观测器的多智能体协同目标环绕控制

针对复杂多扰环境下面向未知运动目标的多智能体对峙跟踪问题,提出了一种基于固定阈值事件触发扩张状态观测器(FTESO)的多智能体协同目标环绕控制方法。首先,建立了智能体与目标的相对运动模型,将目标加速度、模型非线性、环境摄动视为集总干扰,利用量测的相对位置信息构造可降低测量端状态更新频次的FTESO,以实现在非周期采样条件下对于相对速度不可测和集总干扰未知的精准估计。其次,结合速度方向场理论生成目标与智能体间的期望相对速度,根据相邻智能体间的相对角间距信息与FTESO的观测结果,设计了一种不依赖目标加速度信息的多智能体相位协同一致性协议,使得多智能体能够以指定环绕半径、环绕角速度和相对角间距实现对未知运动目标的环绕跟踪。借助Lyapunov稳定性理论,证明了闭环系统中所有误差信号最终一致有界。最后,通过仿真和比较结果验证了所提算法的有效性。