Distributed fixed-time attitude coordinated control for multiple spacecraft with actuator saturation

This paper investigates the distributed fixed-time attitude coordinated control problem for multiple spacecraft subject to actuator saturation under the directed topology. First, a distributed fixed-time observer is presented for each follower spacecraft to estimate the leader spacecraft’s states. Compared with the commonly used fixed-time observer, the settling time of the proposed fixed-time observer can be easily adjusted by some free design parameters. Next, a distributed fixed-time control ...     

Adaptive event-triggered distributed optimal guidance design via adaptive dynamic programming

In this paper, the multi-missile cooperative guidance system is formulated as a general nonlinear multi-agent system. To save the limited communication resources, an adaptive eventtriggered optimal guidance law is proposed by designing a synchronization-error-driven triggering condition, which brings together the consensus control with Adaptive Dynamic Programming(ADP) technique. Then, the developed event-triggered distributed control law can be employed by finding an approximate solution of eve...     

基于改进狼群算法的多无人机协同多目标分配CSCD

针对现代空战多无人机协同多目标任务分配问题,结合标准狼群算法,提出了一种改进狼群算法的多目标任务分配方法。根据狼群的不同分工以及搜索属性,建立了基于自主游走机制的头狼产生规则、基于多策略知识库的探狼游走机制和基于自适应步长的猛狼奔袭及围攻方式,从而对传统狼群算法的随机性进行智能化约束与控制,以解决多无人机协同多目标任务分配问题。数值仿真结果表明,该方法能够快速有效获得任务分配方案,避免陷入局部最优。     

航空公司欧美国际航线运营持续时间生存分析

航空公司航线进入后的运营可持续性直接影响其盈利水平。基于生存分析方法探究影响航线运营持续时间的因素，从成本和供给特征、航线和机场特征、市场结构特征、航司合作类型和时间异质性5个方面选取关键因素，以自由化程度较高的欧美跨大西洋市场为实证对象，研究年份为2003—2021共19年，采用Kaplan-Meier方法进行单因素分析，并构建威布尔参数生存模型分析影响因素与航线运营持续时间的定量关系。结果表明：（1）航司在欧美航线的平均运营持续时间为5年，持续运营超过10年的航线占比为16%;(2)距离、航司投入总运力、航线结构、端点机场类型和竞争程度、航司类型及所属区域和联盟对航司航线运营持续时间具有显著影响；（3）联盟和代码共享独立变量和交互变量均对航线生存产生显著影响，星空和天合联盟成员的航线运营持续时间更长，联盟成员在代码共享合作时承担不同承运人角色对航线退出风险影响存在显著差异。     

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...     

固定翼无人机编队的启发分布式模型预测控制

针对无人机编队飞行控制中队形保持、路径规划、重构、防撞等多重功能需求,采用启发型分布式模型预测控制框架,将需求转化为多目标优化问题中的代价函数与相容性约束求解,实现了对无人机编队飞行的一体化控制.同时,采用分阶段式的轨迹规划算法,融合模型预测轨迹规划与多项式轨迹规划,利用多项式轨迹系数实现高效的邻居轨迹信息交互,从而增大了模型预测控制的预测范围,并降低了规划控制过程中的计算量与通信量.最后,通过9架无人机的协同避障编队仿真,证明了该方法的有效性.     

Distributed satellite autonomous navigation using X-ray pulsars

Distributed X-ray pulsar-based navigation (DXNAV) is an effective method to realize earth-orbit satellite positioning under weak pulsar signal conditions. In this paper, we propose a new DXNAV method based on multiple information fusion. The DXNAV system principle and the pulse phase estimate Cramér-Rao lower bound are deduced. To suppress the calculation complexity and the error source, the X-ray pulsar photon time-of-arrival detected by each satellite is equivalently converted to the leading satellite directly using the inter-satellite link ranging and starlight angular distance measurement. A high precision estimate model of the pulse phase is built using pulsar standard profile, observed profile, and star-geocentric angular distance from distributed satellites. The estimated pulse phase is real-time supplied to the navigation system, which is established in the form of a deviation equation. The two-stage Kalman filter is designed to estimate the pulse phase in profile histogram bin step and the leader position in real-time step. Compared separately with the maximum likelihood phase estimate method and the celestial navigation method using only the star-geocentric angular distance, the simulation analysis shows that the estimation precisions of position and velocity are improved by 29% and 25%.     

Design of hybrid-electric aircraft with fault-tolerance considerations

The potential benefits of hybrid-electric or all-electric propulsion have led to a growing interest in this topic over the past decade. Preliminary design of propulsion systems and innovative configurations has been extensively discussed in literature, but steps towards higher levels of technological readiness, optimisation algorithms based on reliable weight estimation and simulation-based mission analysis are required. This paper focuses on the integration of a method for evaluating the lateral-directional controllability of an aircraft within a design chain that integrates aero-propulsive interactions, accurate modelling of the fuel system, and mid-fidelity estimation of the structural weight. Furthermore, the present work proposes a strategy for powerplant management in scenarios with an inoperative chain element. Benefits of hybrid-electric propulsion on the design of the vertical tail plane are evaluated involving the analysis of multiple failure scenarios and certification requirements. The proposed application concerns a commuter aircraft.     

非死锁合同网协议驱动的多机分布式时序任务分配

针对多无人机协同任务分配的时序约束问题，提出了基于非死锁合同网协议(DF CNP)的分布式时序任务分配方法，从理论上避免任务死锁，提升分配结果最优性。定义了局部信息条件下时序任务死锁判据，通过检测时序任务图环路状态与顶点可达性，判定分配方案的全局死锁状态，保证分配结果的可行性。定制了最近邻-深度优先混合搜索算法，在合同网排序过程中优先选择最近邻任务，并结合死锁判据递归回溯，在分布式架构下并行生成满足死锁约束的任务排序方案，提升分配结果的最优性。仿真对比结果表明：相比于非死锁遗传算法(TB GA)，DF CNP在求解效率方面具有显著优势；与耦合约束一致性束算法(CBBA TCC)相比，DF CNP结果最优性明显提升。