阅读说明：本技术 一种基于代理模型的全过程轨迹优化方法及装置 (Overall process trajectory optimization method and device based on proxy model ) 是由 徐�明 和星吉 白雪 李林澄 郑亚茹 师鹏 陈曦 李黎 于灵慧 杨志 于 2021-07-16 设计创作，主要内容包括：本发明公开了一种基于代理模型的全过程轨迹优化方法及装置。所述方法包括：获取轨道飞行器在空中发射段内有效载荷最大的弹道；获取所述轨道飞行器在空间机动段内的二次脉冲和转移提前角；获取轨道飞行器在进入大气层之前的制动开始时刻和制动脉冲矢量；获取轨道飞行器在大气层再入阶段内的再入阶段轨迹；基于代理模型,对所述发射段目标轨道高度、再入制动前准备轨道高度、制动开始时刻进行优化,得到轨道飞行器的有效载荷最大的弹道、二次脉冲、转移提前角、制动开始时刻、制动脉冲矢量和再入阶段轨迹的在轨优化参量；基于在轨优化参量对轨道飞行器进行控制。本发明可以克服原始动力学模型过于复杂、优化求解效率低的问题,提高了优化迭代效率。(The invention discloses a whole-process track optimization method and device based on an agent model. The method comprises the following steps: acquiring a trajectory with the largest effective load of the orbital vehicle in an aerial launching section; acquiring secondary pulses and a transfer advance angle of the orbital vehicle in a space maneuvering section; obtaining the braking starting time and the braking pulse vector of the orbital vehicle before the orbital vehicle enters the atmosphere; acquiring a reentry stage track of the orbital vehicle in an atmospheric reentry stage; optimizing the target track height of the launching section, the height of a prepared track before reentry braking and the braking starting time based on a proxy model to obtain the trajectory, secondary pulse, transfer advance angle, braking starting time, braking pulse vector and the on-orbit optimization parameters of the reentry stage track with the maximum effective load of the orbital vehicle; and controlling the orbital vehicle based on the on-orbit optimization parameters. The method can solve the problems of too complex original dynamic model and low optimization solution efficiency, and improves the optimization iteration efficiency.)

1. A whole process track optimization method based on a proxy model is characterized by comprising the following steps:

acquiring a trajectory with the largest effective load of the orbital vehicle in an aerial launching section;

acquiring secondary pulses and a transfer advance angle of the orbital vehicle in a space maneuvering section;

obtaining the braking starting time and the braking pulse vector of the orbital vehicle before the orbital vehicle enters the atmosphere;

acquiring a reentry stage track of the orbital vehicle in an atmospheric reentry stage;

optimizing a target track height of a launching section, a prepared track height before reentry braking and a braking starting time based on a proxy model to obtain an on-orbit optimization parameter of the trajectory aircraft with the largest effective load, the secondary pulse, the transfer advance angle, the braking starting time, the braking pulse vector and the reentry stage track;

and controlling the orbital vehicle based on the on-orbit optimization parameters.

2. The method of claim 1, wherein the obtaining the trajectory of the orbital vehicle with the largest payload in the launch segment of the air comprises:

traversing global parameters of the orbital vehicle based on a genetic algorithm to obtain initial design variables of the orbital vehicle;

and processing the initial design variables based on a function set method and an interior point method to obtain the maximum trajectory of the effective load.

3. The method of claim 1, wherein the acquiring secondary pulses and transition advance angles of the orbiter within a space maneuver segment comprises:

acquiring initial states of the orbital vehicle and an aerial target;

acquiring a first pulse of Homan transfer based on the initial state and the Homan transfer theory;

and acquiring a second pulse and a transfer advance angle according to the first pulse and the transfer time.

4. The method of claim 1, wherein the obtaining a braking start time and a braking pulse vector of the orbital vehicle prior to entering the atmosphere comprises:

acquiring an initial braking starting moment and an initial braking pulse vector corresponding to the orbital vehicle according to the position vectors of the braking point and the reentry point corresponding to the orbital vehicle;

and correcting the second initial braking starting time and the initial braking pulse vector based on a quadratic programming algorithm to obtain the braking starting time and the braking pulse vector.

5. The method of claim 1, wherein the obtaining a reentry phase trajectory of the orbital vehicle within an atmospheric reentry phase comprises:

solving by adopting a Newton method and a golden section method according to the constraint condition of the atmosphere reentry stage and the reentry track endpoint of the atmosphere reentry stage to obtain the reentry stage track;

wherein the constraint condition comprises: a heat flow rate constraint, a pneumatic overload constraint, a dynamic pressure constraint, and a tilt angle constraint.

6. The method of claim 1, wherein the optimizing a launch segment target track height, a pre-reentry braking preparation track height, and a braking start time based on the proxy model to obtain the trajectory of the largest payload of the rail vehicle, the secondary pulse, the transfer advance angle, the braking start time, the braking pulse vector, and the in-orbit optimization parameters of the reentry phase trajectory comprises:

optimizing the target track height, the off-track preparation track height and the braking starting time according to a given launching date and the initial state of the orbital vehicle, and acquiring the target track height of the orbital vehicle, the off-track preparation track height and the starting time of transfer to a preparation track;

optimizing the trajectory with the maximum payload, the secondary pulse, the transfer advance angle, the braking start time, the braking pulse vector and the reentry stage trajectory based on the target trajectory height, the off-track preparation trajectory height and the start time to obtain on-track optimization parameters.

7. A whole-process trajectory optimization device based on a proxy model is characterized by comprising:

the maximum load trajectory acquisition module is used for acquiring the maximum effective load trajectory of the orbital vehicle in an aerial launching section;

the secondary pulse acquisition module is used for acquiring secondary pulses and transfer advance angles of the orbital vehicle in a space maneuvering section;

the braking moment vector acquisition module is used for acquiring the braking starting moment and the braking pulse vector of the orbital vehicle before the orbital vehicle enters the atmosphere;

the reentry stage trajectory acquisition module is used for acquiring a reentry stage trajectory of the orbital vehicle in an atmospheric reentry stage;

an on-orbit optimization parameter obtaining module, configured to optimize a target orbit height of a launch segment, a prepared orbit height before reentry braking, and a braking start time based on a proxy model, so as to obtain an on-orbit optimization parameter of the orbit aircraft, where the effective load is the largest, the secondary pulse, the transfer advance angle, the braking start time, the braking pulse vector, and the trajectory of the reentry segment;

and the rail vehicle control module is used for controlling the rail vehicle based on the on-orbit optimization parameters.

8. The apparatus of claim 7, wherein the load peak trajectory acquisition module comprises:

the initial design variable acquisition unit is used for traversing global parameters of the orbital vehicle based on a genetic algorithm to acquire initial design variables of the orbital vehicle;

and the load maximum trajectory acquisition unit is used for processing the initial design variables based on an action set method and an interior point method to obtain the maximum trajectory of the effective load.

9. The apparatus of claim 7, wherein the secondary pulse acquisition module comprises:

the initial state acquisition unit is used for acquiring the initial states of the orbital vehicle and the aerial target;

a first-time pulse acquisition unit, configured to acquire a first-time pulse of a huffman transfer based on the initial state and a huffman transfer theory;

and the second pulse acquisition unit is used for acquiring a second pulse and a transition advance angle according to the first pulse and the transition time.

10. The apparatus of claim 7, wherein the braking timing vector obtaining module comprises:

the initial braking time vector acquisition unit is used for acquiring an initial braking starting time and an initial braking pulse vector corresponding to the orbital vehicle according to the position vectors of the braking point and the reentry point corresponding to the orbital vehicle;

and the braking time vector acquisition unit is used for correcting the second initial braking starting time and the initial braking pulse vector based on a quadratic programming algorithm to obtain the braking starting time and the braking pulse vector.

11. The apparatus of claim 7, wherein the reentry stage trajectory acquisition module comprises:

the reentry stage trajectory acquisition unit is used for solving by adopting a Newton method and a golden section method according to the constraint condition of the atmospheric reentry stage and the reentry trajectory end point of the atmospheric reentry stage to obtain the reentry stage trajectory;

wherein the constraint condition comprises: a heat flow rate constraint, a pneumatic overload constraint, a dynamic pressure constraint, and a tilt angle constraint.

12. The apparatus of claim 7, wherein the on-track optimization parameter obtaining module comprises:

optimizing the target track height, the off-track preparation track height and the braking starting time according to a given launching date and the initial state of the orbital vehicle, and acquiring the target track height of the orbital vehicle, the off-track preparation track height and the starting time of transfer to a preparation track;

optimizing the trajectory with the maximum payload, the secondary pulse, the transfer advance angle, the braking start time, the braking pulse vector and the reentry stage trajectory based on the target trajectory height, the off-track preparation trajectory height and the start time to obtain on-track optimization parameters.

Technical Field

The invention relates to the technical field of aerospace, in particular to a whole-process trajectory optimization method and device based on a proxy model.

Background

Reusable orbital aircrafts represented by American X-37B aircrafts attract great attention of all aerospace countries due to the capabilities and advantages of being capable of staying in space for a long time, fast responding, resisting space attack and defense and the like. Since the retirement of the space shuttle, the aircraft becomes one of the best alternatives for performing space station repair, on-orbit maintenance and other space tasks. However, because the whole task process of such spacecraft includes launching, space maneuvering, off-orbit braking, lift reentry in the atmosphere and the like, the coupling relationship between the stages is complex, and the overall optimization of the whole task process is a typical nonlinear multi-objective optimization problem. For this problem, many related researches have been conducted on the trajectory optimization design of the above stages, such as: pescetelli et al uses a mixed random deterministic algorithm to realize the optimization of the trajectory of the ascending section of a single-stage orbit entering aircraft, Yokoyama et al uses a modified GA algorithm to solve the problem of the reentry trajectory of a space plane, and Jorris et al provides a hypersonic gliding aircraft optimal trajectory generation method based on Gaussian pseudo-spectrum optimization, and the like. However, most of the researches focus on independent stages of the whole process, optimization indexes are provided for each stage independently according to experience, the whole optimization of the whole process task cannot be realized, and related researches are few.

Due to the characteristics that heuristic algorithms such as a particle swarm algorithm and a genetic algorithm do not depend on system gradient information, are not easy to fall into local minimum values, are wide in applicable problem range and the like, a few scholars apply the heuristic algorithms to the optimization design of the whole task flow path. For example, Lin et al propose a two-layer iterative optimization strategy based on genetic algorithm to solve the global trajectory optimization problem. However, the dynamic model of the full task process is complex, and the direct optimization by using the original dynamic model often results in problems and disadvantages of low optimization iteration efficiency, long calculation time, high requirements on computer performance, and the like.

Disclosure of Invention

The technical problem solved by the invention is as follows: the defects of the prior art are overcome, and the whole process track optimization method and the whole process track optimization device based on the agent model are provided.

In order to solve the above technical problem, an embodiment of the present invention provides a whole process trajectory optimization method based on a proxy model, including:

acquiring a trajectory with the largest effective load of the orbital vehicle in an aerial launching section;

acquiring secondary pulses and a transfer advance angle of the orbital vehicle in a space maneuvering section;

obtaining the braking starting time and the braking pulse vector of the orbital vehicle before the orbital vehicle enters the atmosphere;

acquiring a reentry stage track of the orbital vehicle in an atmospheric reentry stage;

optimizing a target track height of a launching section, a prepared track height before reentry braking and a braking starting time based on a proxy model to obtain an on-orbit optimization parameter of the trajectory aircraft with the largest effective load, the secondary pulse, the transfer advance angle, the braking starting time, the braking pulse vector and the reentry stage track;

and controlling the orbital vehicle based on the on-orbit optimization parameters.

Optionally, the acquiring the trajectory of the orbital vehicle with the largest payload in the aerial launch section includes:

traversing global parameters of the orbital vehicle based on a genetic algorithm to obtain initial design variables of the orbital vehicle;

and processing the initial design variables based on a function set method and an interior point method to obtain the maximum trajectory of the effective load.

Optionally, the acquiring secondary pulses and a transfer advance angle of the orbiter in a space maneuver segment includes:

acquiring initial states of the orbital vehicle and an aerial target;

acquiring a first pulse of Homan transfer based on the initial state and the Homan transfer theory;

and acquiring a second pulse and a transfer advance angle according to the first pulse and the transfer time.

Optionally, the acquiring the braking start time and the braking pulse vector of the orbital vehicle before entering the atmosphere includes:

acquiring an initial braking starting moment and an initial braking pulse vector corresponding to the orbital vehicle according to the position vectors of the braking point and the reentry point corresponding to the orbital vehicle;

and correcting the second initial braking starting time and the initial braking pulse vector based on a quadratic programming algorithm to obtain the braking starting time and the braking pulse vector.

Optionally, the acquiring a reentry phase trajectory of the orbital vehicle in an atmospheric reentry phase includes:

solving by adopting a Newton method and a golden section method according to the constraint condition of the atmosphere reentry stage and the reentry track endpoint of the atmosphere reentry stage to obtain the reentry stage track;

wherein the constraint condition comprises: a heat flow rate constraint, a pneumatic overload constraint, a dynamic pressure constraint, and a tilt angle constraint.

Optionally, the optimizing a launch segment target track height, a reentry pre-braking preparation track height, and a braking start time based on the proxy model to obtain an on-orbit optimization parameter of the trajectory of the orbital vehicle with the largest payload, the secondary pulse, the transfer advance angle, the braking start time, the braking pulse vector, and the reentry stage trajectory includes:

optimizing the target track height, the off-track preparation track height and the braking starting time according to a given launching date and the initial state of the orbital vehicle, and acquiring the target track height of the orbital vehicle, the off-track preparation track height and the starting time of transfer to a preparation track;

optimizing the trajectory with the maximum payload, the secondary pulse, the transfer advance angle, the braking start time, the braking pulse vector and the reentry stage trajectory based on the target trajectory height, the off-track preparation trajectory height and the start time to obtain on-track optimization parameters.

In order to solve the above technical problem, an embodiment of the present invention provides an overall process trajectory optimization device based on a proxy model, including:

the maximum load trajectory acquisition module is used for acquiring the maximum effective load trajectory of the orbital vehicle in an aerial launching section;

the secondary pulse acquisition module is used for acquiring secondary pulses and transfer advance angles of the orbital vehicle in a space maneuvering section;

the braking moment vector acquisition module is used for acquiring the braking starting moment and the braking pulse vector of the orbital vehicle before the orbital vehicle enters the atmosphere;

the reentry stage trajectory acquisition module is used for acquiring a reentry stage trajectory of the orbital vehicle in an atmospheric reentry stage;

an on-orbit optimization parameter obtaining module, configured to optimize a target orbit height of a launch segment, a prepared orbit height before reentry braking, and a braking start time based on a proxy model, so as to obtain an on-orbit optimization parameter of the orbit aircraft, where the effective load is the largest, the secondary pulse, the transfer advance angle, the braking start time, the braking pulse vector, and the trajectory of the reentry segment;

and the rail vehicle control module is used for controlling the rail vehicle based on the on-orbit optimization parameters.

Optionally, the load maximum trajectory acquisition module includes:

the initial design variable acquisition unit is used for traversing global parameters of the orbital vehicle based on a genetic algorithm to acquire initial design variables of the orbital vehicle;

and the load maximum trajectory acquisition unit is used for processing the initial design variables based on an action set method and an interior point method to obtain the maximum trajectory of the effective load.

Optionally, the secondary pulse acquiring module includes:

the initial state acquisition unit is used for acquiring the initial states of the orbital vehicle and the aerial target;

a first-time pulse acquisition unit, configured to acquire a first-time pulse of a huffman transfer based on the initial state and a huffman transfer theory;

and the second pulse acquisition unit is used for acquiring a second pulse and a transition advance angle according to the first pulse and the transition time.

Optionally, the braking time vector obtaining module includes:

the initial braking time vector acquisition unit is used for acquiring an initial braking starting time and an initial braking pulse vector corresponding to the orbital vehicle according to the position vectors of the braking point and the reentry point corresponding to the orbital vehicle;

and the braking time vector acquisition unit is used for correcting the second initial braking starting time and the initial braking pulse vector based on a quadratic programming algorithm to obtain the braking starting time and the braking pulse vector.

Optionally, the reentry stage trajectory acquisition module includes:

the reentry stage trajectory acquisition unit is used for solving by adopting a Newton method and a golden section method according to the constraint condition of the atmospheric reentry stage and the reentry trajectory end point of the atmospheric reentry stage to obtain the reentry stage trajectory;

wherein the constraint condition comprises: a heat flow rate constraint, a pneumatic overload constraint, a dynamic pressure constraint, and a tilt angle constraint.

Optionally, the on-orbit optimization parameter obtaining module includes:

optimizing the target track height, the off-track preparation track height and the braking starting time according to a given launching date and the initial state of the orbital vehicle, and acquiring the target track height of the orbital vehicle, the off-track preparation track height and the starting time of transfer to a preparation track;

optimizing the trajectory with the maximum payload, the secondary pulse, the transfer advance angle, the braking start time, the braking pulse vector and the reentry stage trajectory based on the target trajectory height, the off-track preparation trajectory height and the start time to obtain on-track optimization parameters.

Compared with the prior art, the invention has the advantages that:

the embodiment of the invention provides a whole-process track optimization method and device based on an agent model. The method comprises the steps of obtaining a maximum trajectory of an effective load of the orbital vehicle in an air launching section, obtaining secondary pulses and a transfer advance angle of the orbital vehicle in a space maneuvering section, obtaining a braking start time and a braking pulse vector of the orbital vehicle before the orbital vehicle enters the atmosphere, obtaining a reentry stage track of the orbital vehicle in an atmosphere reentry stage, optimizing a launching section target track height, a reentry braking preparation track height and a braking start time based on a proxy model, obtaining on-orbit optimization parameters of the maximum trajectory, the secondary pulses, the transfer advance angle, the braking start time, the braking pulse vector and the reentry stage track of the orbital vehicle, and controlling the orbital vehicle based on the on-orbit optimization parameters. The embodiment of the invention utilizes the agent model to carry out optimization, thereby overcoming the problems of too complex original dynamic model and low optimization solving efficiency; and fitting the emission section by utilizing Fourier series, thereby further improving the optimization iteration efficiency.

Drawings

FIG. 1 is a flowchart illustrating steps of a method for optimizing a trajectory of an overall process based on a proxy model according to an embodiment of the present invention;

fig. 2 is a schematic diagram of a re-entry point search strategy according to an embodiment of the present invention;

fig. 3 is a schematic diagram of a braking off-track transition track according to an embodiment of the present invention;

FIG. 4 is a schematic diagram of a Fourier series fitting aerial transmission segment according to an embodiment of the present invention;

FIG. 5 is a schematic diagram of a launch and space maneuver segment provided by an embodiment of the present invention;

FIG. 6 is a schematic diagram of an off-track preparation track according to an embodiment of the present invention;

FIG. 7 is a schematic diagram of a proxy model optimization according to an embodiment of the present invention;

fig. 8 is a schematic structural diagram of an overall process trajectory optimization device based on a proxy model according to an embodiment of the present invention.

Detailed Description

The basic idea of the proxy model is to obtain a series of sample points by designing a proper test and establish a mapping relation between input and output of an original model; after the agent model is established, the output response can be obtained through direct calculation of the agent model, and recalculation of the original complex model is avoided. The addition of the agent model reduces the calculation difficulty and improves the efficiency of optimization iteration.

In order to realize the overall optimization design of the whole task flow path of the reusable orbital vehicle and overcome the problem that the original model is too complex and the iteration efficiency is influenced, the invention provides a whole process path optimization design method realized by using a proxy model. The method comprises the steps of firstly, respectively providing an optimization solution strategy for task stages such as air launching trajectory solution, space orbit maneuvering planning, off-orbit braking strategy design, reentry return trajectory calculation and the like, and then, carrying out overall optimization design on a task trajectory in the whole process formed by combining the four stages by using a proxy model.

Next, the technical solutions of the embodiments of the present invention will be described in detail below with reference to the drawings attached to the specification.

Example one

Referring to fig. 1, a flowchart illustrating steps of a method for optimizing a whole process trajectory based on a proxy model according to an embodiment of the present invention is shown, and as shown in fig. 1, the method may include the following steps:

step 101: and acquiring the trajectory of the orbital vehicle with the maximum payload in the launching section in the air.

In the embodiment of the invention, the air launching section takes a Pegasus air launching rocket as a reference. The rocket is delivered to a designated place, height and speed by an airplane for launching, and a reusable Orbital Vehicle (OV) is delivered to a predetermined orbit after launching. The motion of the rocket can be described in the launching inertial coordinate system as shown in the following formula (1):

ma_r＝P+A+mg-ma_e-ma_c (1)

in the formula (1), ar is rocket centroid acceleration, P is thrust vector, a is aerodynamic force, ae involves acceleration, ac is coriolis force, g is gravitational acceleration, and the above formula is developed according to components and can be written as:

in the above formula, Llb is a state transition matrix from the projectile coordinate system to the launch coordinate system, and Lba is a state transition matrix from the air flow coordinate system to the projectile coordinate system. Aerodynamic force a can be described in the air flow coordinate system:

wherein t1end, t2end and t3start are the first-stage shutdown, second-stage shutdown and third-stage startup time respectively, ts is the load separation time, and th is the coasting time before the third-stage startup after the second-stage shutdown. Furthermore, the pitch program angle of the rocket satisfies:

in the present invention, the idle-shooting sectionThe goal of ballistic optimization is to maximize the quality of the in-orbit load. The design variables in this problem are ten in total: 1) transmitting azimuth A_L(ii) a 2) The maximum attack angle alpha 1 of the large attack angle climbing section; 3) maximum angle of attack time of flight t 12; 4) maintaining a lift flight attack angle alpha 2; 5) keeping the lift flight time t23, and flying according to the optimal lift-drag ratio of the attack angle alpha 2; 6) a taxi time th; 7) vacuum first stage pitch program angular rate of change8) Three-stage ignition initial pitch angle9) Angular rate of change of vacuum second stage pitch programBy a multi-section linear pitch angle control strategy, the rocket trajectory inclination angle can be effectively controlled, and the target orbit can be cut in correctly; 10) the payload mass mp.

The invention solves the problem of air emission by adopting a hierarchical optimization process which simultaneously comprises a genetic algorithm, an active set method and an interior point method. Global optimization is carried out through a genetic algorithm, initial design variables of the optimization problem are screened, then an optimal solution in a local area of the initial optimization variables is obtained through a function set method and an interior point method, and finally the maximum effective load trajectory meeting flight process constraints and the orbit entering conditions is obtained.

After acquiring the trajectory of the orbital vehicle with the maximum payload in the air launching section, step 102 is performed.

Step 102: and acquiring secondary pulses and a transfer advance angle of the orbital vehicle in a space maneuvering section.

In this example, the primary maneuver of the spatial maneuver segment is the intersection maneuver of the OV with the Spatial Target (ST), which employs a modified Hoeman transfer maneuver under the J2 kinetic model. By applying the classical Hueman transfer theory under the two-body center gravity model, the first pulse, the second pulse, the corresponding transfer time and the intersection advance angle of the classical Hueman transfer can be obtained. The first pulse and the transfer time obtained under the two-body model are used as initial values, a transfer end point constraint is set, the first maneuvering and transfer time of modified Hoeman transfer under the J2 model can be obtained by correcting the first pulsing and the transfer time under the J2 dynamic model by using an inner point method, and then numerical integration is carried out on the first maneuvering and transfer time, so that the corresponding actual second pulse and the actual transfer advance angle can be obtained. Specifically, the detailed description may be made in conjunction with the following formulas.

The J2 kinetic model can be expressed using the following equation (2):

wherein R is the distance from the spacecraft to the Earth's center, μ is the Earth's gravitational constant, R_EIs the equatorial radius of the earth. Assume initial states of OV and ST are (roovi, vOVi) and (rSTi, vSTi), respectively, and the huffman transition time is Ttr. The ST states (rSTf, vSTf) at the end of the transition can be obtained by numerically integrating the J2 kinetic equation. The first pulse of the classical Human transfer can be obtained by respectively taking (rOVi, vOVi) and (rSTf, vSTf) as initial state and final state and applying the classical Human transfer theory under the two-body center gravity model:

and (3) second pulse:

ΔV_f＝V_STf-V_SPf

angle of advance of intersection:

the first pulse Deltav obtained under a two-body model_iTBAnd a transfer time T_trTBAs initial value and setting the transfer end point constraint as | | r_SPf-r_STf||<ε_dis. Using interior point method for Δ v_iTBAnd T_trTBThe modification under the J2 model can be obtained by carrying out the modification under the J2 dynamic modelAnd the positive Hoeman transfer first maneuver Δ vi and the transfer time Ttr are substituted into the related formula to obtain the corresponding actual second pulse and the actual transfer advance angle.

After acquiring the secondary pulse and the transfer advance angle of the orbiter in the space maneuver segment, step 103 is executed.

Step 103: and acquiring the braking start time and the braking pulse vector of the orbital vehicle before the orbital vehicle enters the atmosphere.

In this example, an off-orbit brake is required to be applied before the OV re-enters the atmosphere, from the moving near-earth orbit into a transition orbit connecting the near-earth orbit and the earth's atmospheric boundary. The main problem to be solved by off-track braking is to determine the moment and brake pulse vector at which braking is initiated. Maneuvers within the orbital plane consume less fuel than maneuvers that modify the orbital plane, and it is therefore reasonable to implement an off-orbit maneuver when the initial orbital (hereinafter referred to as the working orbital) plane on which the OV travels before off-orbit passes through a predetermined atmospheric edge re-entry point. In order to determine the reentry braking time, the subsatellite point of the OV working orbit needs to be forecasted under a J2 model, and the subsatellite point forecasting stops when the forecasted subsatellite point track of the working orbit passes through the reentry region. And selecting the subsatellite point which is closest to the reentrant point in the reentry area as a virtual reentrant point, and solving the derailment braking problem by taking the virtual reentrant point as the terminal point of the transition track for determining the derailment point and the derailment braking pulse vector. To find the initial value of the off-track point under the center gravity model of the body, the off-track pulse is assumed to be along the tangential direction of the track. Under the tangential impulse assumption, the transition track can be considered as a Hohmann-like transition to estimate transition times and obtain an approximate analytical solution for off-track braking. After an approximate analytical solution is obtained, the braking pulse is corrected by an SQP algorithm under a J2 dynamic model, and the braking pulse meeting various constraints under a J2 model is obtained. Specifically, the detailed description may be made in conjunction with the following formulas.

As shown in fig. 2, to determine the time of reentry braking, the subsatellite point of the SC orbit needs to be predicted under the J2 model. Assume longitude and latitude of a re-entry point asCorresponding tolerance error isδ_λThen the range of the reentry region is:

and stopping the satellite point forecasting when the forecasted satellite point track of the working track passes through the reentry region. And selecting the subsatellite point which is closest to the reentrant point in the reentry area as a virtual reentrant point, and solving the derailment braking problem by taking the virtual reentrant point as the terminal point of the transition track for determining the derailment point and the derailment braking pulse vector. To find the initial value of the off-track point under the center gravity model of the body, the off-track pulse is assumed to be along the tangential direction of the track. As shown in fig. 3, γ_do1And gamma_do2Respectively time of flight path angle at stopping point and reentry point (wherein gamma_do2Also considered as re-entry angle), r_do1And r_do2Respectively, the position vectors of the off-track point and the re-entry point. It is worth noting that under the tangential pulse assumption, γ is_do10. According to the conservation of energy and momentum, the tangential off-track pulse can be obtained as the magnitude:

in vector form ofWherein v is^- _do1Is the pre-braking velocity vector at the braking point. Central angle theta from off-track point to re-entry point_do2AnyThe conditions are satisfied:

cosθ_do2Any＝(r_do1 ^T·r_do2)/(r_do1·r_do2)

the time from the point of derailment to the point of re-entry is

Usually, the reentry angle γ_do2Very small, so under the tangential pulse assumption, the transition track can be considered as a Hohman-like transition to estimate the transition time T_deAny. After an approximate analytical solution is obtained, the braking pulse delta V is subjected to SQP algorithm under a J2 dynamic model_deAnyCorrecting to obtain brake pulse delta V meeting various constraints under the J2 model_de. The main flow of the correction is as follows: performing numerical integration on the J2 dynamic model by taking the braked state at the braking point as an initial value, and stopping the integration when the height of the OV meets the height constraint of the reentry point to obtain a transition orbit; and correcting the brake pulse by utilizing an SQP algorithm to ensure that the transition track end point meets the following constraint:

1) transitional track end point longitude and latitudeIs located within the range of the re-entry area,

2) the brake pulse size does not exceed the maximum pulse that the OV can provide,

3) the reentrant angle satisfies the reentrant angle constraint gamma_do2，

4) The transition track end point satisfies the re-entry point height constraint (this constraint is naturally satisfied according to the numerical integration transition track end condition).

By the correction, the determination of the off-track braking strategy based on the approximate analytical solution under the model J2 is completed.

After acquiring the braking start time and the braking pulse vector of the orbital vehicle before entering the atmosphere, step 104 is executed.

Step 104: and acquiring a reentry stage track of the orbital vehicle in an atmospheric reentry stage.

The main constraints of the atmospheric reentry phase are: 1) a heat flow rate constraint, typically a stagnation heat flow rate selected to characterize pneumatic heating severity; 2) the aerodynamic overload constraint can only consider normal overload under simplified conditions for a lift aircraft with a longer body reentry at a large attack angle; 3) dynamic pressure constraint, wherein the upper limit of the dynamic pressure needs to be considered when the tail section is re-entered; 4) the tilt angle constraint, and typically the angle of attack, is a function of mach number. The smaller the error between the reentry track end point and the longitude and latitude score of the preset target is, the better, specifically:

the main constraints of the atmospheric reentry phase are:

1) heat flow rate constraints. Stagnation Heat flow Rate is generally selectedTo characterize pneumatic heating severity and approximately meet

Where ρ is the atmospheric density, V is the dimensionless track velocity, and kQ is a constant associated with the aircraft configuration and surface material, k is taken in the present invention_Q＝1.7415×10^-4UV³。

2) And (5) pneumatic overload restraint. For lift aircraft with longer bodies reentry at large angles of attack, only the normal overload nN can be considered under simplified conditions

n_N＝|L cosα+D sinα|≤n_Nmax

3) And (4) dynamic pressure restraint. The upper limit of dynamic pressure is considered in the end of reentry

4) Tilt angle constraint

σ<σ_max

Typically, the angle of attack is a function of Mach number, and in the present invention the angle of attack profile is taken to be

The longitude and latitude of the reentry track terminal and the preset target are respectively assumed to beAndthe error between the two is s_fThe smaller the error, the better, so the optimization goal of the reentry phase can be set to

The initial state of the re-entry phase being the end state of the off-track braking phase, i.e.

The end point constraint of the reentry phase is

The method selects a Newton method and a golden section method to solve the reentry stage track.

After the reentry phase trajectory of the orbital vehicle within the atmospheric reentry phase is acquired, step 105 is performed.

Step 105: optimizing a target track height of a launching section, a prepared track height before reentry braking and a braking starting time based on a proxy model to obtain the trajectory with the maximum effective load of the orbital vehicle, the secondary pulse, the transfer advance angle, the braking starting time, the braking pulse vector and the on-orbit optimization parameters of the reentry stage trajectory.

Up to this point, dynamic models and solving methods for each stage from air launching to atmosphere reentry have been established. However, for the whole process trajectory design after the front and rear connection of each stage, the optimization of each stage cannot ensure the optimization of the whole process. Therefore, the whole process track needs to be optimized integrally, and the conversion from partial optimization to overall optimization and from module optimization to system optimization is realized. In general, it is of interest for space tasks that the overall task is time consuming, fuel consuming and load weight, i.e. the optimization objective can be set to

J_entitle＝min{T_total,ΔV_total,-M_load}

In the formula: t is_totalTime consuming for the overall task, Δ V_totalFor total velocity pulse consumption, M_loadThe quality of the loading is the quality of the track entering. This is a multi-constraint multi-objective optimization problem. The present invention solves this problem using a proxy model.

The six elements of the track used by the invention are as follows: semi-major axis a, eccentricity e, inclination angle i, ascension angle omega, perigee argument omega and latitude argument u. Assume that the initial number of tracks of ST is

S_opT0＝[a_T0,e_T0,i_T0,Ω_T0,ω_T0,u_T0]，

Corresponding epoch time t_eT0

(5.1) simplification of the emission section

Because the emission section is strong in constraint and slow in solving speed, in order to improve the iteration efficiency of the whole process optimization, the invention adopts 8-order Fourier series to fit the emission section. The target orbital plane of the transmit segment is a constraint of the transmit segment, i.e., (e, i, Ω) three parameters have been determined; in addition, the invention relates to a near-circular orbit, and the near-place argument omega has little influence on the final result and can not be considered in the simplification process. Therefore, as shown in FIG. 4, it is necessary to fit the in-track load M_loadThe relation between three parameters, namely a latitude argument u of an orbit entering point and the time t from the time of the transmission day zero to the orbit entering, and the target orbit height h of a transmitting section:

f_i(h)|_i∈(t,u,M)＝a₀+a₁cos(hw)+b₁sin(hw)+a₂cos(2hw)+b₂sin(2hw)+a₃cos(3hw)+b₃sin(3hw)+a₄cos(4hw)+b₄sin(4hw)+a₅cos(5hw)+b₅sin(5hw)+a₆cos(6hw)+b₆sin(6hw)+a₇cos(7hw)+b₇sin(7hw)+a₈cos(8hw)+b₈sin(8hw)

in the formula: a 0-a 8, b 1-b 8 and w are coefficients determined by fitting.

(5.2) optimization of the overall Process

As shown in fig. 5, the OV is launched into a parking track from which the rendezvous maneuver with the ST is then implemented. Since out-of-plane orbital transfer tends to consume a large amount of fuel, the plane of the OV's parking track (launched target track) is chosen to be the plane of the ST, i.e., (e, i, Ω) of the launch segment target track coincides with ST, and thus the launch segment requires a determined height H of the OV's parking track_P0. In the specific calculation process, firstly, the transmission date needs to be specified, then, the orbit prediction is carried out on the ST under the J2 model until the current day is 0, and the orbit plane at the current time is taken as the target orbit plane of the transmission segment to solve the transmission. After completing the task on the track, the OV starts to select a proper time t_dspA reentry return operation is performed. As shown in FIG. 6, OV and ST are separated and then subjected to a track-changing maneuver to enter a height H_dpThe track is prepared by off-track, and the modified Hoeman transfer strategy similar to that mentioned in the step (2) is adopted in the track transfer, and the description is omitted. Thereafter, the OV proceeds successively to off-track braking and atmospheric reentry. In summary, the overall process optimization problem can be described as: initial State S for a given ST_opT0And the launch date, searching for the appropriate launch target track height H_P0Off-track preparation track height H_dpTime t for starting transfer to preparation track_dspSo that the index is optimized. The invention solves the multi-objective optimization problem by adopting an optimization method based on the agent model. After the solution is completed, an optimized leading edge as shown in fig. 7 can be obtained, and technicians can select points meeting the actual needs of the technicians from the leading edge as results to guide the design of the full-mission process of the repeatable rail vehicle.

Step 106: and controlling the orbital vehicle based on the on-orbit optimization parameters.

After the on-orbit optimization parameters are acquired, the orbital vehicle can be controlled based on the on-orbit optimization parameters, and an on-orbit flight task of the on-orbit vehicle is realized.

Example two

Referring to fig. 8, a schematic structural diagram of an overall process trajectory optimization device based on a proxy model according to an embodiment of the present invention is shown, and as shown in fig. 8, the device may include the following modules:

a maximum-load trajectory acquisition module 810, configured to acquire a trajectory of the orbital vehicle with a maximum payload in an airborne launch segment;

a secondary pulse acquisition module 820, configured to acquire a secondary pulse and a transfer advance angle of the orbiter in a space maneuver segment;

a braking time vector obtaining module 830, configured to obtain a braking start time and a braking pulse vector of the orbital vehicle before entering an atmosphere;

a reentry stage trajectory acquisition module 840, configured to acquire a reentry stage trajectory of the orbital vehicle in an atmospheric reentry stage;

an on-orbit optimization parameter obtaining module 850, configured to optimize the target track height, the off-orbit preparation track height, and the braking start time based on a proxy model, so as to obtain an on-orbit optimization parameter of a trajectory, a secondary pulse, a transfer advance angle, a braking start time, a braking pulse vector, and a reentry stage trajectory of the orbital vehicle with the largest payload;

a rail vehicle control module 860 for controlling the rail vehicle based on the on-orbit optimization parameters.

Optionally, the load maximum trajectory acquisition module includes:

the initial design variable acquisition unit is used for traversing global parameters of the orbital vehicle based on a genetic algorithm to acquire initial design variables of the orbital vehicle;

and the load maximum trajectory acquisition unit is used for processing the initial design variables based on an action set method and an interior point method to obtain the maximum trajectory of the effective load.

Optionally, the secondary pulse acquiring module includes:

the initial state acquisition unit is used for acquiring the initial states of the orbital vehicle and the aerial target;

a first-time pulse acquisition unit, configured to acquire a first-time pulse of a huffman transfer based on the initial state and a huffman transfer theory;

and the second pulse acquisition unit is used for acquiring a second pulse and a transition advance angle according to the first pulse and the transition time.

Optionally, the braking time vector obtaining module includes:

the initial braking time vector acquisition unit is used for acquiring an initial braking starting time and an initial braking pulse vector corresponding to the orbital vehicle according to the position vectors of the braking point and the reentry point corresponding to the orbital vehicle;

and the braking time vector acquisition unit is used for correcting the second initial braking starting time and the initial braking pulse vector based on a quadratic programming algorithm to obtain the braking starting time and the braking pulse vector.

Optionally, the reentry stage trajectory acquisition module includes:

the reentry stage trajectory acquisition unit is used for solving by adopting a Newton method and a golden section method according to the constraint condition of the atmospheric reentry stage and the reentry trajectory end point of the atmospheric reentry stage to obtain the reentry stage trajectory;

wherein the constraint condition comprises: a heat flow rate constraint, a pneumatic overload constraint, a dynamic pressure constraint, and a tilt angle constraint.

Optionally, the on-orbit optimization parameter obtaining module includes:

optimizing the target track height, the off-track preparation track height and the braking starting time according to a given launching date and the initial state of the orbital vehicle, and acquiring the target track height of the orbital vehicle, the off-track preparation track height and the starting time of transfer to a preparation track;

optimizing the trajectory with the maximum payload, the secondary pulse, the transfer advance angle, the braking start time, the braking pulse vector and the reentry stage trajectory based on the target trajectory height, the off-track preparation trajectory height and the start time to obtain on-track optimization parameters.

The detailed description set forth herein may provide those skilled in the art with a more complete understanding of the present application, and is not intended to limit the present application in any way. Thus, it will be appreciated by those skilled in the art that modifications or equivalents may still be made to the present application; all technical solutions and modifications thereof which do not depart from the spirit and technical essence of the present application should be covered by the scope of protection of the present patent application.

Those skilled in the art will appreciate that those matters not described in detail in the present specification are well known in the art.