A spacecraft platform and payload integrated control method for space remote sensing

Abstract

The present invention relates to the field of aerospace technology, and discloses a spacecraft platform and payload integrated control method for space remote sensing, comprising the following steps: step S01: stably controlling the spacecraft platform; step S02: payload operation control; step S03: constructing a spacecraft platform and payload integrated model; step S04: adjusting working parameters in combination with actual mission requirements; by providing step S01 and step S02, it is beneficial to accurately control the attitude of the spacecraft platform and improve the stability of the spacecraft platform, and at the same time, obtain the optimal path of the payload operation through a genetic algorithm, form a payload operation control strategy, generate a payload operation control instruction, and realize precise control of the payload; ensure stability and accuracy during the imaging process, realize the coordinated work between the platform and the payload through the integrated design of the control system of the spacecraft platform and the payload, improve the stability of the spacecraft in orbit, and at the same time improve the accuracy of remote sensing data.

Description

Technical Field

[0001] The present invention relates to the field of aerospace technology, and more specifically to a spacecraft platform and payload integrated control method for space remote sensing. Background Art

[0002] As the carrier of remote sensing payload, the performance of the spacecraft platform directly affects the acquisition and processing of remote sensing data. The integrated control technology of the spacecraft platform and payload is the key to improving the quality of remote sensing images, reducing system complexity and increasing the success rate of missions.

[0003] However, the traditional separation design between spacecraft platform and payload has problems such as poor stability, difficult control, and high energy consumption when dealing with complex space environments, making it difficult to achieve efficient data acquisition and processing. Therefore, a spacecraft platform and payload integrated control method for space remote sensing is needed. By integrating the design of the control system of the spacecraft platform and payload, the collaborative work between the platform and payload can be achieved, thereby improving the stability of the spacecraft's on-orbit operation and the accuracy of remote sensing data. Summary of the invention

[0004] In order to overcome the above-mentioned defects of the prior art, the present invention provides a spacecraft platform and payload integrated control method for space remote sensing to solve the problems existing in the above-mentioned background technology.

[0005] The present invention provides the following technical solution: a spacecraft platform and payload integrated control method for space remote sensing, comprising the following steps:

[0006] Step S01: Stable control of the spacecraft platform: Stable control of the spacecraft platform is achieved through attitude control;

[0007] Step S02: Load operation control: design a load control strategy to achieve precise control of the load;

[0008] Step S03: Based on step S01 and step S02, a spacecraft platform and payload integrated model is constructed to achieve coordinated control of the platform and payload;

[0009] Step S04: Adjust the working parameters according to the actual task requirements.

[0010] Preferably, the specific manner of the posture control is:

[0011] Step S11: Collecting the spacecraft platform attitude information and establishing an attitude kinematics model;

[0012] Step S12: designing a posture control algorithm based on the posture kinematics model established in step S11;

[0013] Step S13: Implement attitude adjustment to achieve stable control of the spacecraft platform.

[0014] Preferably, the attitude information in step S11 is the quaternion of the spacecraft; The four parameters β1, β2, and β3 define the rotation quaternion from coordinate system a to coordinate system b, where: is the angle of rotation of coordinate system a around ON, β1 is the angle between ON and coordinate axis X a β2 is the angle between ON and the coordinate axis Y a β3 is the angle between ON and the coordinate axis Z a The angle of the coordinate system a is OX a Y a Z a , coordinate system b is OX b Y b Z b , coordinate system a rotates around axis ON That is, it coincides with coordinate system b;

[0015] , where Q ba Represents the rotation quaternion from coordinate system a to coordinate system b, q0 is the quaternion's standard part, is the vector part of the quaternion, satisfying ; Quaternions are composed of real numbers plus three imaginary units, q1, q2 and q3 are represented as imaginary units;

[0016] The posture kinematics model is expressed by the formula: , where Q' is the attitude kinematics model representation, F(ω) represents the angular velocity parameter, and the formula is expressed as: , where ω is the angular velocity of coordinate system b relative to coordinate system a at OX b Y b Z b The component array in , where ω x is the angular velocity component in the x-axis direction, ω y is the angular velocity component in the y-axis direction, ω z is the angular velocity component in the z-axis direction.

[0017] Preferably, the specific method of designing the posture control algorithm in step S12 is:

[0018] Step S21: Based on the attitude kinematics model, the target attitude of the spacecraft is set. The quaternion of the target attitude relative to the orbital coordinate system is denoted as q m , the quaternion of the stellar body relative to the orbital coordinate system is denoted as q b , the angular velocity of the target attitude relative to the orbital coordinate system is ω m, the angular velocity of the star relative to the orbital coordinate system is expressed as ω b , the angular acceleration of the target attitude relative to the orbital coordinate system is a m ;

[0019] Step S22: Calculate the attitude quaternion error and the attitude angular velocity error: The calculation formula of the attitude quaternion error is: , where q e is the attitude quaternion error;

[0020] The calculation formula of the attitude angular velocity error is: , where ω e is the attitude angular velocity error, A(q e ) is the rotation matrix of the star attitude relative to the target attitude;

[0021] Step S23: Using a control algorithm based on quaternion and attitude angular velocity feedback, control the current attitude of the spacecraft to approach the target attitude, and obtain feedback control torque: , where u f is the feedback control torque, q ev is the vector part of the attitude quaternion error, K and D are the constant diagonal matrices of control parameters, sat(·) is the limit, and the superscript and subscript correspond to the upper and lower limits of the limit, respectively; q evmax is the limit value of the quaternion error in the controller, using vector limit method, the formula is expressed as: .

[0022] Preferably, the specific method of load operation control is:

[0023] Step S21: Obtaining the working parameters of the track and the load;

[0024] Step S22: Obtain the optimal load operation path and form a load operation control strategy;

[0025] Step S23: Based on the control strategy of step S22, a load operation control instruction is generated, and the operation instruction is implemented through the load actuator to achieve precise control of the load.

[0026] Preferably, the operating parameters in step S21 include orbital position, spacecraft speed, temperature, pressure, and historical load operation path;

[0027] The step S22 obtains the optimal path of the load operation through a genetic algorithm, and controls the load operation based on the optimal path as a control strategy;

[0028] The specific method of the genetic algorithm is:

[0029] Step A1: Obtain the load operation path, encode it, obtain the chromosome, and construct the initial population;

[0030] Encode the load operation path as X, where X is the chromosome, and randomly generate N chromosomes to form the initial population. ;

[0031] Step A2: Determine the fitness function;

[0032] The fitness function is expressed as: , where F i is the fitness corresponding to the i-th chromosome, PP i is the matching degree corresponding to the i-th chromosome, i=1, 2, 3...N;

[0033] Step A3: natural selection of chromosomes in the population;

[0034] Step A4: crossover recombination of chromosomes in the population;

[0035] Step A5: mutate the chromosomes in the population;

[0036] Step A6: Obtain a new population, preset the population generation to be L, the fitness threshold to be Q, L is an integer greater than 0, and Q is a real number greater than 0; loop steps A3 to A5 until the generation corresponding to the new population is L or the fitness corresponding to the chromosome in the new population is greater than or equal to the fitness threshold, the loop ends, and the load operation path corresponding to the chromosome with the maximum fitness in the new population is obtained as the optimal load operation path.

[0037] Preferably, the specific method of constructing the spacecraft platform and payload integrated model is:

[0038] Make an integrated layout of the spacecraft platform and payload, and integrate the subsystems of the spacecraft platform and payload, including mechanical integration, electrical integration, and software integration; establish a three-dimensional simulation model of the integrated spacecraft platform and payload, perform performance simulation on the model, and verify whether the various performance indicators of the spacecraft meet the requirements.

[0039] Technical effects and advantages of the present invention:

[0040] The present invention is provided with step S01 and step S02, which is conducive to collecting the attitude information of the spacecraft platform, establishing an attitude kinematic model, and designing an attitude control algorithm based on the established attitude kinematic model, so as to accurately control the attitude of the spacecraft platform, control the attitude of the spacecraft platform based on quaternions, improve the stability of the spacecraft platform, and at the same time obtain the optimal path of the payload operation through the genetic algorithm, form a payload operation control strategy, generate the payload operation control instruction, and realize the precise control of the payload; ensure the stability and accuracy in the imaging process, build an integrated model after analyzing the spacecraft platform and the payload, realize the coordinated work between the platform and the payload through the integrated design of the control system of the spacecraft platform and the payload, improve the stability of the spacecraft in orbit, and at the same time improve the accuracy of the remote sensing data. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 The present invention is a flow chart of the spacecraft platform and payload integrated control method for space remote sensing.

[0042] Figure 2 It is a schematic diagram of the coordinate system rotation of the present invention. DETAILED DESCRIPTION

[0043] The technical solution of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the present invention. In addition, the forms of the various structures recorded in the following embodiments are only examples. The spacecraft platform and payload integrated control method for space remote sensing involved in the present invention is not limited to the various structures recorded in the following embodiments. All other implementations obtained by ordinary technicians in this field without making creative work belong to the scope of protection of the present invention.

[0044] like Figure 1 As shown, the present invention provides a spacecraft platform and payload integrated control method for space remote sensing, comprising the following steps:

[0045] Step S01: Stable control of the spacecraft platform: Stable control of the spacecraft platform is achieved through attitude control to ensure that the attitude of the spacecraft on orbit is stable;

[0046] Step S02: Payload operation control: designing an optoelectronic payload control strategy to ensure stability and accuracy during the imaging process and achieve precise control of the payload;

[0047] Step S03: Based on step S01 and step S02, a spacecraft platform and payload integrated model is constructed to achieve coordinated control of the platform and payload;

[0048] Step S04: Adjust the operating parameters according to the actual mission requirements; the operating parameters include the attitude, orbit and payload of the spacecraft platform.

[0049] In this embodiment, it should be specifically explained that the specific manner of the posture control is:

[0050] Step S11: Collecting the spacecraft platform attitude information and establishing an attitude kinematics model;

[0051] Step S12: designing a posture control algorithm based on the posture kinematics model established in step S11;

[0052] Step S13: Implement attitude adjustment to achieve stable control of the spacecraft platform.

[0053] In this embodiment, it should be specifically explained that the specific method of load operation control is:

[0054] Step S21: Obtaining the working parameters of the track and the load;

[0055] Step S22: Obtain the optimal load operation path and form a load operation control strategy;

[0056] Step S23: Based on the control strategy of step S22, a load operation control instruction is generated, and the operation instruction is implemented through the load actuator to achieve precise control of the load.

[0057] In this embodiment, it should be specifically explained that the attitude information in step S11 is the quaternion of the spacecraft; a commonly used attitude description in engineering is the Euler angle, which has only three attitude angle parameters and has obvious geometric meaning. However, when the spacecraft has a large-angle attitude maneuver, the Euler angle will produce a singular problem that makes the kinematics unsolvable. Therefore, the quaternion is used to describe the attitude of the spacecraft in maneuver control;

[0058] like Figure 2 As shown, according to The four parameters β1, β2, and β3 define the rotation quaternion from coordinate system a to coordinate system b, where: is the angle of rotation of coordinate system a around ON, β1 is the angle between ON and coordinate axis X a β2 is the angle between ON and the coordinate axis Y a β3 is the angle between ON and the coordinate axis Z a The angle of the coordinate system a is OX a Y a Z a , coordinate system b is OX b Y b Z b , the coordinate system a rotates around the axis ON That is, it coincides with coordinate system b;

[0059] , where Q ba Represents the rotation quaternion from coordinate system a to coordinate system b, q0 is the quaternion's standard part, is the vector part of the quaternion, satisfying ; Quaternions are composed of real numbers plus three imaginary units, q1, q2 and q3 are represented as imaginary units;

[0060] The posture kinematics model is expressed by the formula: , where Q' is the attitude kinematics model representation, F(ω) represents the angular velocity parameter, and the formula is expressed as: , where ω is the angular velocity of coordinate system b relative to coordinate system a at OX b Y b Z b The component array in , where ω x is the angular velocity component in the x-axis direction, ω y is the angular velocity component in the y-axis direction, ω z is the angular velocity component in the z-axis direction.

[0061] In this embodiment, it should be specifically explained that the specific method of designing the posture control algorithm in step S12 is:

[0062] Step S21: Based on the attitude kinematics model, the target attitude of the spacecraft is set. The quaternion of the target attitude relative to the orbital coordinate system is denoted as q m , the quaternion of the stellar body relative to the orbital coordinate system is denoted as q b , the angular velocity of the target attitude relative to the orbital coordinate system is ω m , the angular velocity of the star relative to the orbital coordinate system is expressed as ω b , the angular acceleration of the target attitude relative to the orbital coordinate system is a m ;

[0063] Step S22: Calculate the attitude quaternion error and the attitude angular velocity error: The calculation formula of the attitude quaternion error is: , where q e is the attitude quaternion error;

[0064] The calculation formula of the attitude angular velocity error is: , where ω e is the attitude angular velocity error, A(q e ) is the rotation matrix of the star attitude relative to the target attitude;

[0065] Step S23: Using a control algorithm based on quaternion and attitude angular velocity feedback, control the current attitude of the spacecraft to approach the target attitude, and obtain feedback control torque: , where u f is the feedback control torque, q ev is the vector part of the attitude quaternion error, K and D are the constant diagonal matrices of control parameters, sat(·) is the limit, and the superscript and subscript correspond to the upper and lower limits of the limit, respectively; q evmax is the limit value of the quaternion error in the controller, using vector limit method, the formula is expressed as: .

[0066] In this embodiment, it should be specifically explained that the working parameters in step S21 include but are not limited to orbital position, spacecraft speed, temperature, pressure and historical load operation path;

[0067] The step S22 obtains the optimal path of the load operation through a genetic algorithm, and controls the load operation based on the optimal path as a control strategy;

[0068] The specific method of the genetic algorithm is:

[0069] Step A1: Obtain the load operation path, encode it, obtain the chromosome, and construct the initial population;

[0070] Encode the load operation path as X, where X is the chromosome, and randomly generate N chromosomes to form the initial population. ;

[0071] Step A2: Determine the fitness function;

[0072] The fitness function is expressed as: , where F i is the fitness corresponding to the i-th chromosome, PP i is the matching degree corresponding to the i-th chromosome, i=1, 2, 3...N;

[0073] Step A3: natural selection of chromosomes in the population;

[0074] Step A4: crossover recombination of chromosomes in the population;

[0075] Step A5: mutate the chromosomes in the population;

[0076] Step A6: obtain a new population, the preset population generation number is L, the fitness threshold is Q, L is an integer greater than 0, and Q is a real number greater than 0; loop steps A3 to A5 until the generation number corresponding to the new population is L or the fitness corresponding to the chromosome in the new population is greater than or equal to the fitness threshold, the loop ends, and the load operation path corresponding to the chromosome with the maximum fitness in the new population is obtained as the optimal load operation path; illustratively, if the preset population generation number is 1, the chromosomes in the initial population are subjected to natural selection, crossover recombination and mutation to obtain a new population, and the generation number corresponding to the new population is 1 at this time, so the loop ends;

[0077] The fitness threshold is preset by technical personnel in this field according to the algorithm accuracy. The population algebra L is obtained by technical personnel in this field under multiple different historical load operation paths by using a genetic algorithm multiple times to obtain the corresponding optimal load operation path. In each process of using the genetic algorithm, when the fitness corresponding to the chromosome in the new population is greater than or equal to the fitness threshold, the cycle ends and the algebra corresponding to the new population is obtained; the largest algebra among the multiple algebras is used as the population algebra L.

[0078] In this embodiment, it should be specifically explained that the method for obtaining the matching degree in step A2 includes:

[0079] The historical optimal load operation path and the load operation path corresponding to the chromosome are used as analysis data, and the analysis data is input into the trained matching degree analysis model to predict the corresponding matching degree;

[0080] The specific training process of the matching degree analysis model includes:

[0081] Collect the matching degrees corresponding to multiple groups of analysis data in advance, convert the analysis data and the corresponding matching degrees into a corresponding set of feature vectors, use each set of feature vectors as the input of the model, use a set of predicted matching degrees corresponding to each set of analysis data as the output, and use the actual matching degree corresponding to each set of analysis data as the prediction target. The actual matching degree is the matching degree corresponding to the analysis data collected in advance; minimize the sum of the prediction errors of all analysis data as the training target; the calculation formula of the prediction error is: , where Z K is the prediction error, K is the group number of the eigenvector corresponding to the analyzed data, a K is the predicted matching degree corresponding to the Kth group of analysis data, μ K is the actual matching degree corresponding to the Kth group of analysis data; the matching degree analysis model is trained until the sum of the prediction errors reaches convergence and the training is stopped; the matching degree analysis model is specifically a deep neural network model.

[0082] In this embodiment, it should be specifically explained that the natural selection in step A3 is performed by combining the elite method and the rotation method; the elite method produces F1 offspring chromosomes, and for a population with a capacity of N, the fitness corresponding to the N chromosomes is arranged from large to small, and each of the F1 chromosomes at the front produces a offspring chromosome; the rotation method produces F2 offspring chromosomes, that is, N chromosomes produce F2 offspring chromosomes according to the corresponding rotation probability; F1 and F2 satisfy F1+F2=N, so as to keep the offspring population capacity N unchanged and the population increases in number of generations;

[0083] The rotation probability is expressed by the formula: , where P i is the rotation probability corresponding to the i-th chromosome;

[0084] In the step A4, U chromosomes are randomly selected from the population for crossover recombination to obtain U chromosomes. The crossover recombination adopts the PMX method, which is a prior art method and will not be described in detail here. After the chromosome crossover recombination, the fitness of the U new chromosomes is calculated, and the fitness of the U new chromosomes and the fitness of the U chromosomes are sorted from large to small to generate a sorting table. The U chromosomes in the sorting table are replaced with the U chromosomes for crossover recombination in the population in positive order. In this embodiment, U=0.7N is selected. If the calculated U is not an integer, U is rounded up to ensure that the calculated U is an integer.

[0085] The preset mutation probability in step A5 is denoted as G, and the N chromosomes in the population are mutated according to the mutation probability. The mutation method is to randomly select the positions of two genes in the chromosome and exchange the two gene values. In this embodiment, G=0.02 is selected. The mutation probability is preset by a person skilled in the art according to the algorithm efficiency and algorithm accuracy.

[0086] In this embodiment, it should be specifically explained that the specific method of constructing the spacecraft platform and payload integrated model is:

[0087] The spacecraft platform and payload are laid out in an integrated manner, and the subsystems of the spacecraft platform and payload are integrated, including mechanical integration, electrical integration, and software integration, to ensure the collaborative work of various systems. A three-dimensional simulation model of the integrated spacecraft platform and payload is established, and the performance of the model is simulated to verify whether the various performance indicators of the spacecraft meet the requirements. Through multiple simulations, the impact of changes in various design parameters on the final imaging effect can be intuitively seen, and the imaging quality is effectively guaranteed through collaborative control.

[0088] In the present embodiment, it should be specifically explained that the difference between the present embodiment and the prior art lies mainly in that the present embodiment has step S01 and step S02, which is conducive to acquiring the attitude information of the spacecraft platform, establishing an attitude kinematic model, and designing an attitude control algorithm based on the established attitude kinematic model, so as to accurately control the attitude of the spacecraft platform, control the attitude of the spacecraft platform based on quaternions, improve the stability of the spacecraft platform, and at the same time obtain the optimal path of the payload operation through the genetic algorithm, form a payload operation control strategy, generate payload operation control instructions, and realize precise control of the payload; ensure the stability and accuracy of the imaging process, build an integrated model after analyzing the spacecraft platform and the payload, and realize the collaborative work between the platform and the payload by integrating the design of the control system of the spacecraft platform and the payload, thereby improving the stability of the spacecraft in orbit and the accuracy of the remote sensing data.

[0089] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

[0090] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A spacecraft platform and payload integrated control method for space remote sensing, characterized in that: The following steps are involved: Step S01: Stable control of the spacecraft platform: Stable control of the spacecraft platform is achieved through attitude control; Step S02: Load operation control: design a load control strategy to achieve precise control of the load; Step S03: Based on step S01 and step S02, a spacecraft platform and payload integrated model is constructed to achieve coordinated control of the platform and payload; Step S04: adjusting the working parameters according to the actual task requirements; The specific method of the posture control is: Step S11: Collecting the spacecraft platform attitude information and establishing an attitude kinematics model; Step S12: designing a posture control algorithm based on the posture kinematics model established in step S11; Step S13: Implement attitude adjustment to achieve stable control of the spacecraft platform; The attitude information in step S11 is the quaternion of the spacecraft; the rotation quaternion from coordinate system a to coordinate system b is defined according to four parameters θ, β1, β2, and β3, where θ is the angle of rotation of coordinate system a around ON, β1 is the angle between ON and coordinate axis X a β2 is the angle between ON and the coordinate axis Y a β3 is the angle between ON and the coordinate axis Z a The angle of the coordinate system a is OX a Y a Z a , coordinate system b is OX b Y b Z b , coordinate system a rotates θ around axis ON and coincides with coordinate system b; Among them, Q ba Represents the rotation quaternion from coordinate system a to coordinate system b, q0 is the quaternion's standard part, [q1 q2 q3] T is the vector part of the quaternion, satisfying Quaternions are composed of real numbers plus three imaginary units, q1, q2 and q3 are represented as imaginary units; The posture kinematics model is expressed by the formula: Among them, Q' is the attitude kinematics model representation, F(ω) represents the angular velocity parameter, and the formula is expressed as: Where ω is the angular velocity of coordinate system b relative to coordinate system a at OX b Y b Z b The component array in ω=[ω x ω y ω z ] T , where ω x is the angular velocity component in the x-axis direction, ω y is the angular velocity component in the y-axis direction, ω z is the angular velocity component in the z-axis direction; The specific method of designing the posture control algorithm in step S12 is: Step S21: Based on the attitude kinematics model, the target attitude of the spacecraft is set. The quaternion of the target attitude relative to the orbital coordinate system is denoted as q m , the quaternion of the stellar body relative to the orbital coordinate system is denoted as q b , the angular velocity of the target attitude relative to the orbital coordinate system is ω m , the angular velocity of the star relative to the orbital coordinate system is expressed as ω b , the angular acceleration of the target attitude relative to the orbital coordinate system is a m ; Step S22: Calculate the attitude quaternion error and the attitude angular velocity error: The calculation formula of the attitude quaternion error is: Among them, q e is the attitude quaternion error; The calculation formula of the attitude angular velocity error is: ω e =ω b -A(q e )ω m , where ω e is the attitude angular velocity error, A(q e ) is the rotation matrix of the star attitude relative to the target attitude; Step S23: Using a control algorithm based on quaternion and attitude angular velocity feedback, control the current attitude of the spacecraft to approach the target attitude, and obtain feedback control torque: Among them, u f is the feedback control torque, q ev is the vector part of the attitude quaternion error, K and D are the constant diagonal matrices of control parameters, sat(·) is the limit, and the superscript and subscript correspond to the upper and lower limits of the limit, respectively; q evmax is the limit value of the quaternion error in the controller, using vector limit method, the formula is expressed as:

2. The method for integrated control of a spacecraft platform and payload for space remote sensing according to claim 1, characterized in that: The specific method of load operation control is: Step S21: Obtaining the working parameters of the track and the load; Step S22: Obtain the optimal load operation path and form a load operation control strategy; Step S23: Based on the control strategy of step S22, a load operation control instruction is generated, and the operation instruction is implemented through the load actuator to achieve precise control of the load.

3. The method for integrated control of a spacecraft platform and payload for space remote sensing according to claim 2, characterized in that: The operating parameters in step S21 include orbital position, spacecraft speed, temperature, pressure, and historical load operation path; The step S22 obtains the optimal path of the load operation through a genetic algorithm, and controls the load operation based on the optimal path as a control strategy; The specific method of the genetic algorithm is: Step A1: Obtain the load operation path, encode it, obtain the chromosome, and construct the initial population; The load operation path is encoded as X, where X is the chromosome, and N chromosomes are randomly generated to form the initial population Z0 = {X1, X2, X3, ..., X N }; Step A2: Determine the fitness function; The fitness function is expressed as: i =PP i , where F i is the fitness corresponding to the i-th chromosome, PP i is the matching degree corresponding to the i-th chromosome, i = 1, 2, 3...N; Step A3: natural selection of chromosomes in the population; Step A4: crossover recombination of chromosomes in the population; Step A5: mutate the chromosomes in the population; Step A6: Obtain a new population, preset the population generation to be L, the fitness threshold to be Q, L is an integer greater than 0, and Q is a real number greater than 0; loop steps A3 to A5 until the generation corresponding to the new population is L or the fitness corresponding to the chromosome in the new population is greater than or equal to the fitness threshold, the loop ends, and the load operation path corresponding to the chromosome with the maximum fitness in the new population is obtained as the optimal load operation path.

4. The method for integrated control of a spacecraft platform and payload for space remote sensing according to claim 1, characterized in that: The specific method of constructing the spacecraft platform and payload integrated model is as follows: Make an integrated layout of the spacecraft platform and payload, and integrate the subsystems of the spacecraft platform and payload, including mechanical integration, electrical integration, and software integration; establish a three-dimensional simulation model of the integrated spacecraft platform and payload, perform performance simulation on the model, and verify whether the various performance indicators of the spacecraft meet the requirements.

Images