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A simple method to design non-collision relative orbits for close spacecraft formation flying

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Science China(Physics,Mechanics & Astronomy) 2018年第5期61卷 20-35页

作者： Wei jiang JunFeng Li fanghua jiang Franco Bernelli-Zazzera School of Aerospace Engineering Tsinghua University Department of Aerospace Science and Technology Politecnico di Milano

A set of linearized relative motion equations of spacecraft flying on unperturbed elliptical orbits are specialized for particular cases, where the leader orbit is circular or equatorial. Based on these extended equations, we are able to analyze the relative motion regulation between a pair of spacecraft flying on arbitrary unperturbed orbits with the same semi-major axis in close formation. Given the initial orbital elements of the leader, this paper presents a simple way to design initial relative orbital elements of close spacecraft with the same semi-major axis, thus preventing collision under non-perturbed conditions. Considering the mean influence of J_2 perturbation, namely secular J_2 perturbation, we derive the mean derivatives of orbital element differences, and then expand them to first order. Thus the first order expansion of orbital element differences can be added to the relative motion equations for further analysis. For a pair of spacecraft that will never collide under non-perturbed situations, we present a simple method to determine whether a collision will occur when J_2 perturbation is considered. Examples are given to prove the validity of the extended relative motion equations and to illustrate how the methods presented can be used. The simple method for designing initial relative orbital elements proposed here could be helpful to the preliminary design of the relative orbital elements between spacecraft in a close formation, when collision avoidance is necessary.

关键词：相对轨道太空船非碰撞设计单方相对运动方程船形领导人

An identifier-actor-optimizer policy learning architecture for optimal control of continuous-time nonlinear systems

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Science China(Physics,Mechanics & Astronomy) 2020年第6期63卷 42-53页

作者： Lin Cheng ZhenBo Wang fanghua jiang JunFeng Li School of Aerospace Engineering Tsinghua UniversityBeijing 100084China Department of Mechanical Aerospaceand Biomedical EngineeringUniversity of TennesseeKnoxville TN 37996USA

An intelligent solution method is proposed to achieve real-time optimal control for continuous-time nonlinear systems using a novel identifier-actor-optimizer(IAO)policy learning architecture.In this IAO-based policy learning approach,a dynamical identifier is developed to approximate the unknown part of system dynamics using deep neural networks(DNNs).Then,an indirect-method-based optimizer is proposed to generate high-quality optimal actions for system control considering both the constraints and performance index.Furthermore,a DNN-based actor is developed to approximate the obtained optimal actions and return good initial guesses to the optimizer.In this way,the traditional optimal control methods and state-of-the-art DNN techniques are combined in the IAO-based optimal policy learning method.Compared to the reinforcement learning algorithms with actor-critic architectures that suffer hard reward design and low computational efficiency,the IAO-based optimal policy learning algorithm enjoys fewer user-defined parameters,higher learning speeds,and steadier convergence properties in solving complex continuous-time optimal control problems(OCPs).Simulation results of three space flight control missions are given to substantiate the effectiveness of this IAO-based policy learning strategy and to illustrate the performance of the developed DNN-based optimal control method for continuous-time OCPs.

关键词： continous-time nonlinear systems identifier-actor-optimizer architecture intelligent optimal control deep neural net-works

Real-time control for fuel-optimal Moon landing based on an interactive deep reinforcement learning algorithm

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Astrodynamics 2019年第4期3卷 375-386页

作者： Lin Cheng Zhenbo Wang fanghua jiang Tsinghua University Beijing 100084China University of Tennessee KnorvilleTN 37996USA

In this study,a real-time optimal control approach is proposed using an interactive deep reinforcement learning algorithm for the Moon fuel-optimal landing problem.Considering the remote communication restrictions and environmental uncertainties,advanced landing control techniques are demanded to meet the high requirements of real-time performance and autonomy in the Moon landing missions.Deep reinforcement learning(DRL)algorithms have been recently developed for real-time optimal control but suffer the obstacles of slow convergence and difficult reward function design.To address these problems,a DRL algorithm is developed using an actor-indirect method architecture to achieve the optimal control of the Moon landing mission.In this DRL algorithm,an indirect method is employed to generate the optimal control actions for the deep neural network(DNN)learning,while the trained DNNs provide good initial guesses for the indirect method to promote the efficiency of training data generation.Through sufficient learning of the state-action relationship,the trained DNNs can approximate the optimal actions and steer the spacecraft to the target in real time.Additionally,a nonlinear feedback controller is developed to improve the terminal landing accuracy.Numerical simulations are given to verify the effectiveness of the proposed DRL algorithm and demonstrate the performance of the developed optimal landing controller.

关键词： fuel-optimal landing problem indirect methods deep reinforcement learning interactive network learning real-time optimal control

Optimization of observing sequence based on nominal trajectories of symmetric observing con guration

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Astrodynamics 2018年第1期2卷 25-37页

作者： Hongwei Yang Gao Tang fanghua jiang School of Aerospace Engineering Tsinghua UniversityBeijing 100084China Department of Mechanical Engineering and Materials Science Duke UniversityDurhamNC 27708USA

This paper presents the crucial method for obtaining our team's results in the 8th Global Trajectory Optimization Competition(GTOC8).Because the positions and velocities of spacecraft cannot be completely determined by one observation on one radio source,the branch and bound method for sequence optimization of multi-asteroid exploration cannot be directly applied here.To overcome this diculty,an optimization method for searching the observing sequence based on nominal low-thrust trajectories of the symmetric observing con guration is proposed.With the symmetric observing con guration,the normal vector of the triangle plane formed by the three spacecraft rotates in the ecliptic plane periodically and approximately points to the radio sources which are close to the ecliptic plane.All possible observing opportunities are selected and ranked according to the nominal trajectories designed by the symmetric observing con guration.First,the branch and bound method is employed to nd the optimal sequence of the radio source with thrice observations.Second,this method is also used to nd the optimal sequence of the left radio sources.The nominal trajectories are then corrected for accurate observations.The performance index of our result is 128,286,317.0 km which ranks the second place in GTOC8.

关键词： branch and bound optimization symmetric observing configuration GTOC low thrust

PBL教学法在检验科带教中的作用及对其考核成绩的影响

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中国卫生产业 2024年第3期21卷 192-194,198页

作者：杨慧江芳华陈友孙清陈志敏魏建威福建中医药大学附属第二人民医院检验科福建福州350003

目的评价检验科带教期间应用以问题为导向教学法(Problem-Based Learning,PBL)教学法所取效果,评估对实习生考核成绩的影响。方法选取2019年10月—2023年10月福建中医药大学附属第二人民医院实习的50名检验专业学生,经简单随机化法划分... 详细信息

目的评价检验科带教期间应用以问题为导向教学法(Problem-Based Learning,PBL)教学法所取效果,评估对实习生考核成绩的影响。方法选取2019年10月—2023年10月福建中医药大学附属第二人民医院实习的50名检验专业学生,经简单随机化法划分为对照组(n=25,常规教学法)、观察组(n=25,PBL教学法),对比两组教学效果,评估指标包含考核成绩、教学质量、综合能力。结果观察组考核成绩均高于对照组,差异有统计学意义(P<0.05);理论深化、仪器教学、实操教学、检验技能指导各指标对比,观察组高于对照组,差异有统计学意义(P均<0.05);相比于对照组,观察组综合能力较强,各项指标评分较高,差异有统计学意义(P均<0.05)。结论在检验科带教期间采取“问题式学习”教学法具有显著作用,有益于提高实习生考核成绩以及整体教学质量。

关键词：问题式学习检验科带教考核成绩

Low-thrust trajectory optimization of asteroid sample return mission with multiple revolutions and moon gravity assists

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Science China(Physics,Mechanics & Astronomy) 2015年第11期58卷 107-120页

作者： TANG Gao jiang fanghua LI JunFeng School of Aerospace Engineering Tsinghua University

Near-Earth asteroids have gained a lot of interest and the development in low-thrust propulsion technology makes complex deep space exploration missions possible. A mission from low-Earth orbit using low-thrust electric propulsion system to rendezvous with near-Earth asteroid and bring sample back is investigated. By dividing the mission into five segments, the complex mission is solved separately. Then different methods are used to find optimal trajectories for every segment. Multiple revolutions around the Earth and multiple Moon gravity assists are used to decrease the fuel consumption to escape from the Earth. To avoid possible numerical difficulty of indirect methods, a direct method to parameterize the switching moment and direction of thrust vector is proposed. To maximize the mass of sample, optimal control theory and homotopic approach are applied to find the optimal trajectory. Direct methods of finding proper time to brake the spacecraft using Moon gravity assist are also proposed. Practical techniques including both direct and indirect methods are investigated to optimize trajectories for different segments and they can be easily extended to other missions and more precise dynamic model.

关键词：科学学科学知识物理学力学天文学

Fuel optimal low thrust rendezvous with outer planets via gravity assist

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Science China(Physics,Mechanics & Astronomy) 2011年第4期54卷 756-769页

作者： GUO TieDing jiang fanghua BAOYIN HeXi LI JunFeng School of Aerospace Tsinghua University Beijing 100084 China

Low thrust propulsion and gravity assist (GA) are among the most promising techniques for deep space explorations.In this paper the two techniques are combined and treated comprehensively,both on modeling and numerical techniques.Fuel optimal orbit rendezvous via multiple GA is first formulated as optimal guidance with multiple interior constraints and then the optimal necessary conditions,various transversality conditions and stationary conditions are derived by Pontryagin's Maximum Principle (PMP).Finally the initial orbit rendezvous problem is transformed into a multiple point boundary value problem (MPBVP).Homotopic technique combined with random searching globally and Particle Swarm Optimization (PSO),is adopted to handle the numerical difficulty in solving the above MPBVP by single shooting method.Two scenarios in the end show the merits of the present approach.

关键词：遗传优化小推力燃料外行星引力数字技术多点边值问题轨道交会

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变频器驱动双电机谐波状态估计方法

电工技术 2022年第7期 123-126页

作者：蒋芳华湖南华菱湘潭钢铁有限公司湖南湘潭411101

变频器中的驱动双电机在接入电网时往往会出现谐波状态改变,造成谐波污染,产生电能问题。传统的基于最小二乘法的谐波状态估计方法的耦合关系提取困难,量测方程不稳定,因此改进了生成对抗网络,设计了新的变频器驱动双电机谐波估计方法... 详细信息

变频器中的驱动双电机在接入电网时往往会出现谐波状态改变,造成谐波污染,产生电能问题。传统的基于最小二乘法的谐波状态估计方法的耦合关系提取困难,量测方程不稳定,因此改进了生成对抗网络,设计了新的变频器驱动双电机谐波估计方法。首先配置了变频器驱动双电机谐波量测点,根据该量测点,设计了双电机谐波状态估计网络结构,进行了网络选择和数据预处理。最后构建了谐波状态估计网络对抗模型,实现了谐波状态估计。实验结果表明,此次设计方法的真实值曲线与预估值曲线拟合度高,具有准确性,有一定的应用价值。

关键词：变频器驱动双电机谐波状态估计

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近距离航天器间碰撞概率线性模型的解析修正

清华大学学报（自然科学版） 2019年第9期59卷 705-711页

作者：姜薇蒋方华李俊峰清华大学航天航空学院

该文提出一种针对近距离航天器间碰撞概率线性模型的解析修正法。原有碰撞概率线性模型较简单,使用条件严格,适用范围有限,不适用于轨道差别较小的相对运动情况。通过分析碰撞概率线性模型计算结果与Monte Carlo仿真计算结果之间的误差... 详细信息

该文提出一种针对近距离航天器间碰撞概率线性模型的解析修正法。原有碰撞概率线性模型较简单,使用条件严格,适用范围有限,不适用于轨道差别较小的相对运动情况。通过分析碰撞概率线性模型计算结果与Monte Carlo仿真计算结果之间的误差,寻找其与航天器间最大和最小相对运动距离之间的近似解析关系,对原有线性模型进行修正,使其更接近真实碰撞概率。仿真结果表明:该方法拓展了原有线性模型的适用范围,并提高了精度。

关键词：碰撞概率线性模型解析修正