路径约束的时间最短多脉冲交会全局优化

不同于现有的多脉冲最优交会研究多集中于交会时间固定的最省燃料优化,研究了路径约束和脉冲受限的多脉冲最短时间交会问题。综合考虑了交会测量视场角、脉冲总量和脉冲作用时刻等约束,基于Lam-bert交会算法,建立了多脉冲交会最短时间优化的非线性规划模型。为了高效获得全局最优解,采用了模拟退火算法用于非线性优化问题的求解。最后,通过解决一个寻的三脉冲交会问题验证了模型和算法的有效性。该研究方法可寻找满足特定约束条件的最优交会轨道。     

An Approach to Optimization of Terminal Rendezvous

The optimal solution is presented to a cooperative game which is described by a common quadratic cost functional subject to linear ordinary differential equation constraints. The optimal feedback controller is constructed for both players when all components of the state vector can be measured. For the case that only some components of the state vector are available, the optimal feedback controller is designed using a dynamic observer. As a specific application, the approach is used in determining the optimal feedback controllers for two satellites which are performing a rendezvous on a circular orbit. Simulation results are presented to illustrate the applicability of the approach.     

交会对接任务天基双目标测控通信设计

针对交会对接任务对测控通信提出的高覆盖率和双目标测控等需求的问题,分析2颗中继卫星能够提供的覆盖率,设计双目标测控工作模式以及天地协同机制,计算中继链路的性能,分析表明,天基测控可提供约72%的测控覆盖率,能够支持双目标测控,链路余量满足要求;统计了任务中关键段落的测控通信工作情况,分析结果和实际任务情况验证了天基测控在交会对接任务测控通信中的重要作用;最后提出后续任务改进和完善的建议。     

基于分支深度强化学习的非合作目标追逃博弈策略求解

为解决航天器与非合作目标的空间交会问题,缓解深度强化学习在连续空间的应用限制,提出了一种基于分支深度强化学习的追逃博弈算法,以获得与非合作目标的空间交会策略。对于非合作目标的空间交会最优控制,运用微分对策描述为连续推力作用下的追逃博弈问题;为避免传统深度强化学习应对连续空间存在维数灾难问题,通过构建模糊推理模型来表征连续空间,提出了一种具有多组并行神经网络和共享决策模块的分支深度强化学习架构。实现了最优控制与博弈论的结合,有效解决了微分对策模型高度非线性且难于利用经典最优控制理论进行求解的难题,进一步提升了深度强化学习对离散行为的学习能力,并通过算例仿真检验了该算法的有效性。     

非合作目标交会的双层MPC全局轨迹规划控制

针对空间非合作目标近距离视线交会中的全局最优鲁棒轨迹规划与控制问题,提出了基于高斯伪谱方法（GPM）和线性时变模型预测控制（LTVMPC）的双层模型预测控制（MPC）算法。在轨迹规划方面,以视线坐标系下的相对轨道动力学为模型、能量最少和控制精度最优为性能指标构建最优控制问题,利用GPM精度高、收敛速度快的特点将最优控制问题转化为易于求解的全局非线性规划问题,在MPC框架下求解得到全局最优的标称轨迹,克服了传统的MPC不适用于全局大范围非线性规划的缺点;在轨迹跟踪控制方面,考虑预测时域内状态转移矩阵的时变特性,设计了LTVMPC算法对标称轨迹进行追踪,避免了存在不确定性时轨迹的重规划,从而降低在线计算量,保证算法在线自主实施,并且采用滚动优化的策略使算法对不确定性具有鲁棒性。由于规划层和控制层考虑的约束相同,因此规划的轨迹是可控、可达的。数字仿真表明,在燃料消耗和交会时间等方面,提出的方法均显著优于传统的MPC方法,相较于传统的MPC方法,新算法的交会时间减少50%左右,燃料消耗降低30%以上。     

人工智能在卫星任务规划中的应用

智能规划与调度是实现卫星自主规划其飞行任务的关键。将人工智能方法应用于卫星的任务规划,以执行对地观测任务为例,将任务规划问题归于组合优化问题,建立了相应的数学模型,并应用Hopfield神经网络算法进行求解,结果表明,该方法可用于单个仪器的任务规划。     

混合遗传算法在航天器最优交会中的应用

推导了航天器双冲量交会时的优化模型,以此为基础构造了最优交会的燃料-时间混合优化指标,并针对基本遗传算法局部搜索能力不强的问题,提出一种将最速下降法与遗传算法相结合的混合遗传算法,其中下降搜索的优化方向利用每一代中最劣个体所包含的优化信息获得。数值计算表明,该混合算法可加速算法的收敛,具有良好的优化性能和函数适应能力。最后,对共面圆轨道双冲量交会情况进行了仿真计算,仿真结果表明混合遗传算法的设计是成功的。     

Robust reliable control for autonomous spacecraft rendezvous with limited-thrust

This paper investigates the problem of robust reliable control for the spacecraft rendezvous with limited-thrust. Based on the Clohessy–Wiltshire (C–W) equations and by considering the uncertainties and the possible failures, the dynamic model for spacecraft rendezvous is proposed, and the orbital transfer control problem is transformed into a stabilization problem. Then, by a Lyapunov approach, the existence conditions for admissible controllers are formulated in the form of linear matrix inequalities (LMIs), and the controller design is cast into a convex feasibility problem subject to LMI constraints. With the obtained controllers, the rendezvous can be accomplished with the limited-thrust in spite of the possible thruster failures. The effectiveness of the proposed approach is illustrated by simulation examples.     

导航辅助下基于LAS码的天基多目标测控

中继卫星的天基测控是解决中低轨道航天器大范围、长时间、多目标测控的有效途径,但用户星到中继卫星的时延误差、多普勒频移校正误差等参数会对多目标测控带来干扰。针对该问题,首先分析了定位误差引起的时延误差、多普勒频移校正误差等因素,设计了天基多目标前向链路遥控SMA(S-band Multiple Access,S频段多址)信号形式和反向遥测链路SMA信号形式,选择与时延校正误差相匹配的LAS(Large Area Synchronous,大区域同步)码作为反向遥测信息的扩频码,建立了导航辅助的终端时延和频率预校正方案模型,可以有效消除多用户干扰。仿真表明,当Eb/N0≥10.5dB时,前向遥控信息误码率pe≤1×10~(-6),反向遥测信息误码率pe≤1×10~(-6),使用LAS码比Gold序列约有2dB性能改善,为基于我国天链卫星的中低轨道卫星稳定运行、载人航天交会对接以及后续空间站建设等任务的测控提供重要参考。     

On Optimal Allocation and Guidance Laws for Linear lnterception and Rendezvous Problems

This paper considers the problem of guiding N interceptors so that they intercept or rendezvous with N targets at the same time T. It is assumed that the interceptors and targets are described by linear time-varying differential equations (deterministic or stochastic). Under certain assumptions both the optimal (static or dynamic) interceptor-target allocation and the guidance of each interceptor for the optimal allocation can be obtained with modest real-time and storage computer requirements.     

一种用于空间交会绕飞与逼近段的模糊控制律

研究了空间交会绕飞与最后逼近段的控制问题,设计出一种用于实现绕飞与逼近控制的模糊控制方案。在考虑测量误差的情况下,分别利用最小二乘与卡尔曼滤波方法对测量数据进行优化处理,并采用模糊控制方案实现绕飞与逼近段的仿真,仿真结果证实了模糊控制算法控制精度可以满足交会任务的需要,也验证了在具有测量误差条件下不同仿真方案所采用的模糊控制策略的有效性。     

Orbital rendezvous using two-step sliding mode control

The problem of spacecraft rendezvous is studied, using sliding mode control in the presence of the earth's gravitational perturbation. The impulsive solution of Lambert's problem is obtained using the combined equations method to minimize total ΔV via an iterative method, and it is used as the desired trajectory for the rendezvous. In this paper, a two-step sliding mode control method is introduced for solving the rendezvous problem with finite-thrust including unmodeled dynamics.The thrust-coast-thrust type control laws for the system to follow the desired trajectories are represented and resultant trajectories are close enough to the Lambert's orbit with comparable amount of ΔV to the Lambert's impulsive solution. All state variables matched the final boundary conditions reasonably well at the end of maneuver.     

航天器多约束交会的仅测角导航最优多目标闭环制导

研究了航天器多约束交会的仅测角导航最优多目标闭环制导问题,优化目标包括交会时间、燃耗和仅测角导航可观性指标,并考虑了视觉传感器视场角、推力器推力幅度和最小安全距离等各种约束条件,建立了多约束、多目标优化下的仅测角导航和闭环制导问题的数学模型,分析了仅测角导航和闭环制导之间的耦合关系。最后,通过Matlab遗传算法工具箱中的多目标优化函数,求解得到了该多目标优化模型的Pareto最优解集,结果显示交会时间、燃耗和仅测角导航可观性指标不能同时达到最优,存在相互制约关系,即提高其中一种优化目标的性能会降低其他优化目标的性能。     

基于地基CEI技术的空间飞行器相对位置测量技术研究

讨论了差分CEI的基本原理,分析了差分CEI的相对位置确定的误差。通过分析得出结论：在CEI基线长度为1000m时,相对角度测量精度可以达到16urad,如果增加基线距离或者结合SBI技术,测量精度会进一步提高,测量精度能够满足交会过程中相对导航、编队卫星相对位置测量、高轨卫星共位等要求。     

基于Lambert问题的精确拦截与交会策略研究

Lambert交会问题的经典Gauss求解方法是建立在二体问题假设基础上的,不能满足实际空间任务需求。因此在考虑摄动影响的基础上,提出了一种修正方法,以实现精确拦截和交会,并通过仿真算例验证了该方法的正确性。     

Optimization of multiple-impulse minimum-time rendezvous with impulse constraints using a hybrid genetic algorithm

The minimum-time multiple-impulse rendezvous with impulse constraints is investigated in this paper. Based on the Clohessy–Wiltshire (C–W) equations, an optimization model including several different kinds of impulse constraints such as the maximum impulse magnitude, the total velocity change magnitude and the time of imposing impulse for multiple-impulse minimum-time rendezvous is established. A generalized inverse matrix solution for linear equation is applied to avoid handling the terminal equality constraints. In order to obtain the global solution efficiently, a hybrid optimizer combining the advantages of a floating-coded genetic algorithm and simplex method is employed. A low-earth orbit multiple-impulse rendezvous problem is used as an example. The influence of the number of impulses, the optimization variables and the constraints on the solution is analyzed, and the different optimization algorithms are compared. Results indicate our proposed model and approach is effective in designing linearized minimum-time rendezvous trajectory with impulse constraints.     

分布式卫星干涉测高系统编队构形优化设计方法

 分布式卫星干涉合成孔径雷达（InSAR）编队构形设计是系统总体设计的关键问题。从系统测高性能优化角度出发，提出分布式InSAR编队优化设计一般方法，将其概括为求解一个优化问题，以主星带辅星群体制分布式InSAR为例建立目标函数，针对其星载双站、斜视、空间基线等特点建立测高精度与辅星轨道根数的关系，基于近似的相对运动数学模型对该优化问题进行简化，并采用遗传算法求解。在此基础上，对多颗卫星组成编队以提高系统测高性能提出了一种多星编队设计方法。仿真分析表明，经优化得到的编队测高性能要优于干涉车轮和钟摆编队，该结果验证了优化设计方法的有效性和正确性。     

LEO navigation augmentation constellation design with the multi-objective optimization approaches

Low Earth Orbit (LEO) satellite for navigation augmentation applications can significantly reduce the precise positioning convergence time and attract increasing attention recently. A few LEO Navigation Augmentation (LEO-NA) constellations have been proposed, while corresponding constellation design methodologies have not been systematically studied. The LEO-NA constellation generally consists of a huge number of LEO satellites and it strives for multiple optimization purposes. It is essentially different from the communication constellation or earth observing constellation design problem. In this study, we modeled the LEO-NA constellation design problem as a multi-objective optimization problem and solve this problem with the Multi-Objective Particle Swarm Optimization (MOPSO) algorithm. Three objectives are used to strive for the best tradeoff between the augmentation performance and deployment efficiency, namely the Position Dilution of Precision (PDOP), visible LEO satellites and the orbit altitude. A fuzzy set approach is used to select the final constellation from a set of Pareto optimal solutions given by the MOPSO algorithm. To evaluate the performance of the optimized constellation, we tested two constellations with 144 and 288 satellites and each constellation has three optimization schemes: the polar constellation, the single-layer constellation and the two-layer constellation. The results indicate that the optimized two-layer constellation achieves the best global coverage and is followed by the single-layer constellation. The MOPSO algorithm can help to improve the constellation design and is suitable for solving the LEO-NA constellation design problem.     

基于混合粒子群算法的上升段交会弹道快速优化设计

基于梯度搜索的高效性和粒子群搜索的随机性,提出了一种混合粒子群算法,并应用该算法研究了运载火箭上升段交会弹道快速优化设计问题.以运载火箭与目标飞行器在交会时刻的距离最小为目标函数,设计了运载火箭飞行程序,建立了运载火箭上升段交会弹道优化模型,同时分别采用混合粒子群算法、遗传算法和粒子群算法进行求解.仿真结果表明:基于本文算法对运载火箭上升段交会弹道进行优化设计,平均交会位置误差为4.137m,较遗传算法减少了17.940m,平均优化耗时488.922s,较粒子群算法缩短了2342.125s.混合粒子群算法搜索速度较快,收敛精度较高,可用于运载火箭上升段交会弹道的快速优化设计.      

考虑潜在威胁区的航天器最优规避机动策略

随着一系列轨道转移飞行器的工程化实施,航天器可能面临的非合作交会威胁日趋严重。针对该问题,根据交会机动的特点定义了新的规避机动指标——潜在威胁区,相较于传统的相对距离和碰撞概率等规避指标,潜在威胁区更适合航天器在面对非合作交会追踪器时进行规避机动,能够有效提升航天器的抗交会能力。首先,建立追踪器多脉冲最优交会模型,以此为基础给出潜在威胁区的定义与计算方法;然后,以潜在威胁区弧长为优化目标,建立了目标器最优规避模型,采用遗传算法进行目标优化;最后,根据所建立的双层优化模型进行数值仿真,以初始相距100km为初始条件进行仿真并计算得到了使潜在威胁区为零所需规避脉冲值,验证了文中模型的正确性,结果显示所定义的潜在威胁区弧长随着规避脉冲的增大呈严格的单调递减关系。研究为在轨航天器在面对非合作交会时提供了有效的规避策略,提升了航天器的空间生存能力。