考虑动态控制分配的空天飞行器再入姿态复合控制设计

针对空天飞行器再入大气层阶段的直接力/气动力复合控制分配问题,设计了一种基于改进指标函数的动态控制分配律,兼顾了反作用控制系统燃料消耗和闭环控制系统响应速度需求。此外,针对空天飞行器面对称大攻角再入引发的横侧向气动强耦合问题,在预测控制律中引入了通道间交叉耦合反馈项,对姿控过程进行增稳。对比仿真结果表明,动态分配算法在提高了再入姿态控制精度的同时降低了反作用控制系统的燃料消耗;交叉耦合反馈项的引入,缓解了倾侧角指令突变对偏航通道稳定性的干扰影响。     

多约束航迹规划与跟踪制导律

研究升力式飞行器多约束航迹规划与跟踪制导律设计。考虑到飞行器为满足任务需求规定了一定范围的禁飞区，为确保滑翔段末状态处于中末制导交班窗口内设置了严格的终端约束，导致传统基于最大升阻比、平衡滑翔策略的航迹规划不适用。针对飞行器在不同空域的动力学特性，结合飞行策略预划分手段分段提出不同状态下的攻角、倾侧角剖面，通过优化剖面构型参数将无穷维轨迹优化问题转化为有限维参数规划问题，完成多约束航迹规划。最后，考虑到气动不确定性带来的轨迹偏差，利用线性二次型调节器以位移加权误差最小为优化指标完成轨迹跟踪制导律设计，实现对规划航迹的在线纠偏，并通过仿真分析验证所提方法的有效性。     

IPL：运载火箭测试数据自动判读语言

为确保运载火箭测试数据的完整性与正确性，克服传统人工判读模式判读效率低、易误判漏判以及通用编程语言自动判读模式判读适应性、扩展性、复用性差的不足，提出并设计运载火箭测试数据处理领域的自动判读语言IPL（Interpretation Language），以及配套的语言解析与执行器，实现了运载火箭测试判据的形式化定义与描述，减轻了业务人员的学习、判读成本，使得海量测试数据的判读在分钟级即可全部自动完成，目前已在多种新一代运载火箭工程实践中得到成功应用。     

探测点序列的最优化与简化计算方法

在搜索状态建模和求解一阶搜索状态方程的特征迹线解的基础上,建立了对随机运动进行离散时间探测的发现概率最优控制模型,结合动态规划原理给出一种最优探测点序列的逼近算法,并给出了短时计算的算法简化形式。在满足一阶搜索状态方程的随机恒速目标条件以及有限指数探测函数条件下,将给出的算法及其简化形式应用到算例。算例表明,当随机恒速运动目标初始位置和速度均服从圆正态分布时,该算法及其简化形式均能够由任意给定的初始探测点序列优化收敛到满足精度要求的最优探测点序列。     

Aerial-ground collaborative routing with time constraints

The advancement of autonomous technology makes electric-powered drones an excellent choice for flexible logistics services at the last mile delivery stage. To reach a balance between green transportation and competitive edge, the collaborative routing of drones in the air and trucks on the ground is increasingly invested in the next generation of delivery, where it is particularly reasonable to consider customer time windows and time-dependent travel times as two typical time-related factors in daily services. In this paper, we propose the Vehicle Routing Problem with Drones under Time constraints (VRPD-T) and focus on the time constraints involved in realistic scenarios during the delivery. A mixed-integer linear programming model has been developed to minimize the total delivery completion time. Furthermore, to overcome the limitations of standard solvers in handling large-scale complex issues, a space-time hybrid heuristic-based algorithm has been developed to effectively identify a high-quality solution. The numerical results produced from randomly generated instances demonstrate the effectiveness of the proposed algorithm.     

Sequential dynamic resource allocation in multi-beam satellite systems:A learning-based optimization method

Multi-beam antenna and beam hopping technologies are an effective solution for scarce satellite frequency resources. One of the primary challenges accompanying with Multi-Beam Satellites(MBS) is an efficient Dynamic Resource Allocation(DRA) strategy. This paper presents a learning-based Hybrid-Action Deep Q-Network(HADQN) algorithm to address the sequential decision-making optimization problem in DRA. By using a parameterized hybrid action space,HADQN makes it possible to schedule the beam patte...     

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...     

Model predictive control for close-proximity maneuvering of spacecraft with adaptive convexification of collision avoidance constraints

This study investigated model predictive control (MPC) for close-proximity maneuvering of spacecraft. It is essential for a designed MPC to effectively handle collision avoidance between the servicer spacecraft and the client spacecraft, especially while the client is rotating. The rotating motion of the client leads to dynamic changes in the collision avoidance constraints, which increases the difficulty of optimizing the control input in the MPC framework. Therefore, this study presents a method to improve the performance and computational efficiency of MPC for rendezvous and docking with a nonrotating or rotating client. An ellipsoid is adopted to model the client’s keep-out zone (KOZ). Given the spherical KOZ of the servicer, an expanded ellipsoid is introduced to describe the KOZ for the center of mass of the servicer and modeled as a nonlinear constraint. The linearization method for reference points located at the expanded ellipsoid is adopted to convexify the nonlinear constraints. The reference points are adaptively determined according to the positions of the servicer, client, and expanded ellipsoidal KOZ. The resulting hyperplanes are then used to describe the collision avoidance constraints. By utilizing the aforementioned strategies, combined with the calculated reference points, an adaptive convex programming algorithm suitable for real-time implementation of MPC is derived. The performance of the proposed method is demonstrated through numerical simulations.     

Smooth free-cycle dynamic soaring in unspecified shear wind via quadratic programming

Harvesting wind energy is promising for extending long-endurance flights, which can be greatly facilitated by a flight technique called dynamic soaring. The presented study is concerned with generating model-based trajectories with smooth control histories for dynamic soaring maneuvers exploiting wind gradients. The desired smoothness is achieved by introducing a trigonometric series parameterization for the controls, which are formulated with respect to the normalized time.Specifically, the per...