先进航天器轨道快速优化
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摘要
鉴于低成本的太空资源开发、巨大的战略利益等因素的考虑，当前许多发达国家相继将发展先进航天器ASV(可重复使用运载器RLV、乘员返回飞行器CRV、空间作战飞行器SOV、军用空天飞机MSP、空间机动飞行器SMV等)作为未来航天技术发展的重点。先进航天器飞行时应具备自主导航的能力，其实现的关键技术之一是用机载计算机近实时或实时地生成一条满足各种约束条件的优化轨道。虽然国内外学者在ASV轨道优化方面已经做了大量研究工作，取得了令人瞩目的成果，但是绝大多数优化方法要花大量的计算机时才能获得最优控制量及相应的最优轨道，即传统的算法不能满足ASV自主导航实时生成轨道的要求。本论文就ASV轨道快速优化问题进行了深入研究，主要内容包括两部分：再入轨道快速优化和上升轨道快速优化。
ASV再入轨道快速优化
本文根据ASV再入轨道快速优化的需求，在运动模型处理方面和优化算法方面做了如下工作：
模型处理：(1)根据ASV再入运动方程的特点和优化算法流程结构的特征，对模型做了合理的简化处理(将6状态量轨道状态方程分为参与数值优化迭代的一组状态方程和不参与数值优化迭代的一组状态方程)；(2)运动模型无量纲处理；(3)运动模型转化处理(将终端时间自由的轨道最优控制问题转化为终端积分变量固定的最优控制问题)。处理后的模型计算量少，更适合优化数值解法求解。
算法方面：与传统轨道优化算法不同，本文算法先根据轨道约束和准平衡约束规划出再入走廊，在再入走廊内选取满足航程约束的一条基准轨道，然后根据基准轨道反推算得到其中的一个控制量—滚转角，采用参数优化法优化滚转角。在此基础上，采用共轭梯度法对另一个控制量—迎角进行优化。
仿真结果表明，只需10-20秒左右的时间即能产生一条满足轨道约束、终端约束、控制量约束和航程约束的优化轨道。此轨道可以用作ASV自主导航的参考轨迹，也可用作应急情况下再入的参考轨迹，具有很好的工程应用价值。
ASV上升轨道快速优化
本文根据ASV上升轨道快速优化的需求，在运动模型处理方面和优化算法方面做了如下工作：
Nowadays, a number of developed countries have launched many programmes about Advanced Space Vehicles(ASV), which include Reusable Launch Vehicle, Crew Return Vehicle, Space Operation Vehicle, Military Space Plane, Space Maneuver Vehicle et al., ground on space resource exploitation and strategic interests. The guidance and control methods should enable the ASV to accomplish fully autonomous and adaptive flight, a key problem is to achieve the optimal controls quickly. However, determining how to find the best controls of an ASV so that it is able to safely reach Terminal Area Energy Management (TAEM) or go into specified orbit involves the solution of a two-point boundary value problem. This problem, which is considered to be difficult, is traditionally solved on the ground rather than onboard. The optimal controls are found regardless of computing time by most of algorithms, which can meet requirements of traditional shuttle guidance. That is, traditional trajectory optimization algorithms can not perform this fast trajectory optimization tasks. The main works of this dissertation are focused on the fast ASV trajectory optimization, including:
Fast optimization of three-dimensional reentry trajectory
Traditional trajectory optimization algorithms cannot perform this fast optimization task. In this dissertation, a new hypothesis is introduced according to the features of three-dimensional constrained reentry trajectory of ASV. The dynamics and kinematics equations of motion are divided into two sets and only one of those is involved in iterations of optimization algorithm, and this simplification reduces the computation labor greatly. Different from other optimization algorithms, firstly, the algorithm generates a reentry corridor according to all common inequality constraints and quasi-equilibrium glide conditions. Then, a normal trajectory can be achieved based on range constraints within the corridor and a normal control variable (the bank angle) will be obtained by utilizing the normal trajectory and quasi-equilibrium glide conditions. Next, the Conjugate-Gradient Method is applied to optimize another control variable (the angle of attack). All above methods and operationes accelerate the convergence of optimization iteration greatly. The simulation shows that this methodology is able to generate a feasible reentry trajectory of about 2000 seconds flight time in about 10 seconds on the desktop computer.
Fast optimization of three-dimensional launch trajectory
The dissertation focuses on fast generation and optimization of three-dimensional ascent trajectory for ASV, which is one of fundamental research work. Firstly, the set of dynamics and kinematics equations of motion is simplified according to the features of three-dimensional constrained ascent trajectory of ASV, and this simplification reduces the computation labor greatly. Then, the trajectory optimal
ASV再入轨道快速优化
本文根据ASV再入轨道快速优化的需求，在运动模型处理方面和优化算法方面做了如下工作：
模型处理：(1)根据ASV再入运动方程的特点和优化算法流程结构的特征，对模型做了合理的简化处理(将6状态量轨道状态方程分为参与数值优化迭代的一组状态方程和不参与数值优化迭代的一组状态方程)；(2)运动模型无量纲处理；(3)运动模型转化处理(将终端时间自由的轨道最优控制问题转化为终端积分变量固定的最优控制问题)。处理后的模型计算量少，更适合优化数值解法求解。
算法方面：与传统轨道优化算法不同，本文算法先根据轨道约束和准平衡约束规划出再入走廊，在再入走廊内选取满足航程约束的一条基准轨道，然后根据基准轨道反推算得到其中的一个控制量—滚转角，采用参数优化法优化滚转角。在此基础上，采用共轭梯度法对另一个控制量—迎角进行优化。
仿真结果表明，只需10-20秒左右的时间即能产生一条满足轨道约束、终端约束、控制量约束和航程约束的优化轨道。此轨道可以用作ASV自主导航的参考轨迹，也可用作应急情况下再入的参考轨迹，具有很好的工程应用价值。
ASV上升轨道快速优化
本文根据ASV上升轨道快速优化的需求，在运动模型处理方面和优化算法方面做了如下工作：
Nowadays, a number of developed countries have launched many programmes about Advanced Space Vehicles(ASV), which include Reusable Launch Vehicle, Crew Return Vehicle, Space Operation Vehicle, Military Space Plane, Space Maneuver Vehicle et al., ground on space resource exploitation and strategic interests. The guidance and control methods should enable the ASV to accomplish fully autonomous and adaptive flight, a key problem is to achieve the optimal controls quickly. However, determining how to find the best controls of an ASV so that it is able to safely reach Terminal Area Energy Management (TAEM) or go into specified orbit involves the solution of a two-point boundary value problem. This problem, which is considered to be difficult, is traditionally solved on the ground rather than onboard. The optimal controls are found regardless of computing time by most of algorithms, which can meet requirements of traditional shuttle guidance. That is, traditional trajectory optimization algorithms can not perform this fast trajectory optimization tasks. The main works of this dissertation are focused on the fast ASV trajectory optimization, including:
Fast optimization of three-dimensional reentry trajectory
Traditional trajectory optimization algorithms cannot perform this fast optimization task. In this dissertation, a new hypothesis is introduced according to the features of three-dimensional constrained reentry trajectory of ASV. The dynamics and kinematics equations of motion are divided into two sets and only one of those is involved in iterations of optimization algorithm, and this simplification reduces the computation labor greatly. Different from other optimization algorithms, firstly, the algorithm generates a reentry corridor according to all common inequality constraints and quasi-equilibrium glide conditions. Then, a normal trajectory can be achieved based on range constraints within the corridor and a normal control variable (the bank angle) will be obtained by utilizing the normal trajectory and quasi-equilibrium glide conditions. Next, the Conjugate-Gradient Method is applied to optimize another control variable (the angle of attack). All above methods and operationes accelerate the convergence of optimization iteration greatly. The simulation shows that this methodology is able to generate a feasible reentry trajectory of about 2000 seconds flight time in about 10 seconds on the desktop computer.
Fast optimization of three-dimensional launch trajectory
The dissertation focuses on fast generation and optimization of three-dimensional ascent trajectory for ASV, which is one of fundamental research work. Firstly, the set of dynamics and kinematics equations of motion is simplified according to the features of three-dimensional constrained ascent trajectory of ASV, and this simplification reduces the computation labor greatly. Then, the trajectory optimal
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