Method for maintaining surface shape of segmented telescope primary mirror based on multi-agent cooperative control

Abstract

The present application relates to the technical field of space telescope, and especially relates to a method for maintaining the surface shape of a main mirror of a spliced telescope based on multi-agent collaborative control, wherein an agent is arranged on each sub-mirror of the main mirror, and current attitude information of each sub-mirror is obtained; each sub-mirror is connected to other sub-mirrors through wireless communication by the agent, and the current attitude information of each sub-mirror is shared in real time to the connected sub-mirror, and then current shared attitude information of each sub-mirror is obtained; a current dynamic model of each sub-mirror is determined according to the current attitude information and the current shared attitude information of each sub-mirror, and then next-time attitude information of each sub-mirror is obtained; the above content is repeated until the current attitude information of each sub-mirror converges to ideal attitude information of each sub-mirror, so that information sharing between the sub-mirrors and collaborative decision between the sub-mirrors and the connected sub-mirror are realized, dynamic adaptability is improved, and the demand for real-time adjustment of the sub-mirror attitude and the main mirror surface shape is met.

Description

Technical Field

[0001] This invention belongs to the field of space telescope technology, and particularly relates to a method for maintaining the surface shape of the primary mirror of a spliced ​​telescope based on multi-agent cooperative control. Background Technology

[0002] The primary mirror of a modular telescope is composed of multiple independent sub-mirror units, increasing the telescope's aperture and improving resolution and light-gathering capabilities, but also introducing technical challenges in maintaining its surface shape. Existing sub-mirror collaborative control methods include centralized control, decentralized control, distributed control, feedback control, adaptive control, fuzzy control, H-infinity-based control, predictive control, and intelligent control. Centralized control suffers from single-point-of-failure risk, heavy computational burden, and poor scalability; decentralized control lacks global coordination, making it difficult to achieve global optimization of the overall surface shape; distributed control, while improving coordination, requires complex communication networks and algorithms; feedback control has insufficient response speed in the face of rapidly changing environments; adaptive control is complex to design and computationally expensive; fuzzy control requires a large amount of experience and data for rule formulation and optimization, limiting its performance; H-infinity-based control is complex to design and computationally expensive; predictive control is computationally expensive and depends on model accuracy; intelligent control algorithms are complex, requiring a large amount of data and computational resources for training and optimization, and the control decision-making process is opaque.

[0003] Chinese patent publication number CN117130172A, published on November 28, 2023, entitled "A Global Assembly and Adjustment Method, Device, Equipment, and Medium for a Mosaic Space Telescope," proposes an invention patent application that constructs a first-order linear relationship between different types of wave aberration coefficients and various misalignments. This allows for the phased calculation and adjustment of different misalignments, which is beneficial for the development and application of large-aperture mosaic space telescopes. However, this patent's global assembly and adjustment only involves the adjustment of the mechanical system and does not design coordinated control, thus failing to guarantee the system's dynamic performance.

[0004] The multi-agent cooperative control scheme overcomes the shortcomings of existing technologies by introducing cooperation and information sharing among agents, improving the overall performance and robustness of the system. It can withstand uncertainties in the operating environment and maintain high performance even when the primary mirror is disturbed. Cooperation and information exchange among agents achieve optimized control of the global surface shape, avoiding local optima problems. Distributed computing and real-time information exchange enhance the system's real-time response capability. The modular design of the multi-agent cooperative control makes the design and implementation of control algorithms more flexible and simple, providing reliable technical support for maintaining the high-precision, high-robust surface shape of modular telescopes in scientific research. Summary of the Invention

[0005] In view of this, the present invention aims to provide a method for maintaining the surface shape of a spliced ​​telescope primary mirror based on multi-agent cooperative control. By setting an agent on each sub-mirror of the spliced ​​primary mirror, information sharing between the sub-mirrors is achieved through the agents, thereby realizing global coordination. This not only improves the overall performance of the system, but also enhances the system's robustness to external disturbances and uncertainties.

[0006] To achieve the above objectives, the technical solution created by this invention is implemented as follows:

[0007] A method for maintaining the surface shape of a spliced ​​telescope primary mirror based on multi-agent cooperative control includes the following steps:

[0008] S1: An intelligent agent is set on each sub-mirror in the main mirror to set the initial attitude information, the ideal attitude information and the dynamic model of each sub-mirror.

[0009] S2: Obtain the current attitude information of each sub-mirror and subtract it from the ideal attitude information of each sub-mirror to obtain the current attitude information error of each sub-mirror;

[0010] S3: Use an intelligent agent to wirelessly connect each sub-mirror to other sub-mirrors, so that the current attitude information of each sub-mirror is shared with the connected sub-mirrors in real time, thereby obtaining the current shared attitude information received by each sub-mirror.

[0011] S4: Based on the current attitude information of each sub-mirror and its current shared attitude information, determine the current control input and the current dynamic model of each sub-mirror, and then obtain the attitude information of each sub-mirror at the next moment.

[0012] S5: Repeat steps S2 to S4 until the current pose information of each sub-mirror converges to the ideal pose information of each sub-mirror.

[0013] Furthermore, in step S1, the dynamic model of each sub-mirror... for:

[0014] ;

[0015] in, This represents the pose information of the i-th sub-mirror. This represents the control input for the i-th sub-mirror. A Represents the state matrix, B This represents the control matrix.

[0016] Furthermore, in step S3, the current shared attitude information of each sub-mirror is determined by the following formula. for:

[0017] ;

[0018] in, This indicates the number of connected sub-mirrors connected to the i-th sub-mirror. This represents the total number of connected sub-mirrors connected to the i-th sub-mirror.

[0019] Furthermore, in step S4, the current control input for each sub-mirror is determined by the following formula. for:

[0020] ;

[0021] in, K Represents the control gain matrix. This represents the information weighting factor for the connected sub-mirrors of the i-th sub-mirror. This represents the current shared attitude information received by the nth connected sub-mirror, which is connected to the i-th sub-mirror, at time j.

[0022] Then, the dynamic model of each sub-mirror is combined. Obtain the current dynamic model for each sub-mirror for:

[0023] ;

[0024] The attitude information of each sub-mirror at the next moment is determined by the following formula. for:

[0025] ;

[0026] in, Indicates the time step.

[0027] Compared with the prior art, the present invention can achieve the following beneficial effects:

[0028] (1) The surface shape maintenance method of the spliced ​​telescope primary mirror based on multi-agent cooperative control described in this invention realizes information sharing between sub-mirrors and collaborative decision-making between connected sub-mirrors by setting an agent on each sub-mirror of the spliced ​​primary mirror, thus achieving more flexible dynamic adaptability. Unlike the traditional H-infinity control scheme which mainly focuses on global performance optimization, cooperative control can respond to changes in the surface shape error of the primary mirror more quickly, meet the needs of real-time adjustment of sub-mirror attitude and primary mirror surface shape. Each sub-mirror not only optimizes itself according to its own state, but also coordinates with the state information of connected sub-mirrors, thereby improving the overall control accuracy and the real-time response capability of the system.

[0029] (2) The surface shape preservation method of the main mirror of the spliced ​​telescope based on multi-agent collaborative control described in this invention has excellent scalability: as the number of sub-mirrors increases, the system can be expanded by adding more agents without significantly modifying the overall control algorithm or hardware configuration. This feature enables it to effectively avoid the computational burden of the central controller when facing large spliced ​​telescopes, thereby improving the overall efficiency and flexibility of the system.

[0030] (3) In the method for maintaining the surface shape of the main mirror of the spliced ​​telescope based on multi-agent collaborative control described in this invention, each sub-mirror independently calculates its control input, which improves the computing power and reliability. Even if some sub-mirrors or related modules fail, the overall normal operation can still be maintained. This method significantly improves the robustness and fault tolerance of the system. At the same time, it finds a balance between local and global, ensuring that the spliced ​​telescope can maintain a high-precision main mirror surface shape under various complex conditions. Attached Figure Description

[0031] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments and descriptions of the invention are used to explain the invention and do not constitute an undue limitation of the invention. In the drawings:

[0032] Figure 1 This is a flowchart illustrating the surface shape preservation method for the primary mirror of a spliced ​​telescope based on multi-agent cooperative control, as described in an embodiment of the present invention. Detailed Implementation

[0033] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and do not constitute a limitation thereof.

[0034] It should be noted that, unless otherwise specified, the embodiments and features described in the present invention can be combined with each other.

[0035] In the description of this invention, it should be understood that the terms "center," "longitudinal," "lateral," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," and "outer," etc., indicating orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation on this invention. Furthermore, the terms "first," "second," etc., are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, features defined with "first," "second," etc., may explicitly or implicitly include one or more of that feature. In the description of this invention, unless otherwise stated, "a plurality of" means two or more.

[0036] In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art will understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0037] The invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0038] like Figure 1 As shown in the embodiment of the present invention, the method for maintaining the surface shape of the primary mirror of a spliced ​​telescope based on multi-agent cooperative control includes the following steps:

[0039] S1: An intelligent agent is set on each sub-mirror in the main mirror, and the initial attitude information, ideal attitude information and dynamic model of each sub-mirror are set.

[0040] Specifically, a base coordinate system is established using the primary mirror, and the initial attitude information of each sub-mirror is... Including the initial position coordinates of each sub-mirror in the base coordinate system And the initial rotation angles of each sub-mirror around the x-axis, y-axis, and z-axis of the base coordinate system. , where i represents the number of sub-mirrors, i.e., the initial pose information of each sub-mirror. Ideal pose information for each sub-mirror Including the ideal position coordinates of each sub-mirror in the base coordinate system And the ideal rotation angles of each sub-mirror around the x-axis, y-axis, and z-axis of the base coordinate system. That is, the ideal pose information of each sub-mirror. The initial attitude information and the ideal attitude information of each sub-mirror are obtained through measurement or preset configuration.

[0041] Each sub-mirror's intelligent agent is connected to the adjustment mechanism that adjusts that sub-mirror, enabling the agent to collect the attitude information of the corresponding sub-mirror in real time and receive the attitude information of all connected sub-mirrors. The agent controls the adjustment mechanism based on the attitude information of the corresponding sub-mirror and connected sub-mirrors, thereby completing the attitude adjustment of the corresponding sub-mirror. In this embodiment of the invention, a six-degree-of-freedom adjustment platform is used as the intelligent agent. The output end of the six-degree-of-freedom adjustment platform is connected to the adjustment mechanism of the sub-mirror, and the control center of the six-degree-of-freedom adjustment platform completes the acquisition, transmission, reception, and computation processing of sub-mirror data.

[0042] Dynamic model of each sub-mirror for:

[0043] ;

[0044] in, This represents the pose information of the i-th sub-mirror. This represents the control input for the i-th sub-mirror. A Represents the state matrix, B This represents the control matrix. State matrix A is identified by a single sub-mirror system and describes the state changes of each sub-mirror; each sub-mirror has a specific state matrix A. Control matrix B describes how the actuators are actuated by output control quantities to control the attitude and position of the sub-mirrors. Control matrix B is also identified by a single sub-mirror system, and each sub-mirror has a specific control matrix B. The control input for each sub-mirror... Control input refers to the signals or actions applied to a system to drive the system to achieve the desired behavior. Specifically, in the attitude adjustment of sub-mirrors in a modular telescope, control input refers to the forces, torques, or electrical signals used to adjust the position and attitude of the sub-mirrors. These inputs are generated by the controller in the intelligent agent and act on the adjustment mechanism of the sub-mirrors to compensate for or correct errors in the measured attitude information of the sub-mirrors.

[0045] S2: Obtain the current attitude information of each sub-mirror and subtract it from the ideal attitude information of each sub-mirror to obtain the current attitude information error of each sub-mirror.

[0046] In step S2, the attitude information of each sub-mirror at the first moment is its initial attitude information. Starting from the second moment, the attitude information of each sub-mirror is measured by a wavefront sensor and an interferometric measurement device. The current attitude information error of each sub-mirror is obtained by the following formula. :

[0047] ;

[0048] Where j represents time. Attitude information error data is usually represented as a wavefront error distribution across the entire primary mirror surface, typically a two-dimensional matrix or phase distribution map, representing the deviation at each sampling point decomposed onto each sub-mirror. The surface shape error of the primary mirror can be directly mapped onto each sub-mirror based on the position and geometry of the sub-mirrors. This method assumes that the error occurs locally and is expressed by the following formula:

[0049] ;

[0050] in, This represents the surface shape error of the primary mirror at time j. This represents the region where the i-th sub-mirror is located. Let A represent the area of ​​the i-th sub-mirror, and let A represent the error, where A is the current pose information error of each sub-mirror. The average error is given. The error value for each sub-mirror region can be obtained by integration. This method assumes that the attitude information error of each sub-mirror is the sum of the local surface shape errors of the primary mirror, thus enabling a relatively accurate distribution of the global error to each sub-mirror.

[0051] S3: Connect each sub-mirror to other sub-mirrors via wireless communication using an intelligent agent, and share the current attitude information of each sub-mirror with the connected sub-mirrors in real time, thereby obtaining the current shared attitude information received by each sub-mirror.

[0052] Each sub-mirror shares its own state and error information with other sub-mirrors in real time via wireless communication or by forming a local area network through an intelligent agent, ensuring the real-time nature and accuracy of the information. In this embodiment of the invention, the wireless communication connection method in step S3 is as follows: the intelligent agents of all sub-mirrors are connected to an information processing center such as a server or host computer. The information processing center centrally collects the information of all sub-mirrors through the intelligent agents of each sub-mirror, and then distributes the information of all sub-mirrors to the intelligent agents of each sub-mirror, thereby realizing the sharing of sub-mirror attitude information. In some other embodiments, the wireless communication connection method in step S3 can also be as follows: the intelligent agent of each sub-mirror is directly connected to the intelligent agents of other sub-mirrors, that is, every two connected intelligent agents directly connect to form a wireless communication or local area network, without the need for an information processing center such as a server or host computer.

[0053] In step S3, the current shared attitude information of each sub-mirror is determined by the following formula. for:

[0054] ;

[0055] in, This indicates the number of connected sub-mirrors connected to the i-th sub-mirror. This represents the total number of connected sub-mirrors connected to the i-th sub-mirror, and the current shared pose information of each sub-mirror. This represents the average attitude information of all connected sub-mirrors connected to the i-th sub-mirror. This information from the connected sub-mirrors helps each sub-mirror better understand its surroundings and adjust its control strategy, thus enabling collaboration between sub-mirrors.

[0056] S4: Based on the current attitude information of each sub-mirror and its current shared attitude information, determine the current control input and the current dynamic model of each sub-mirror, and then obtain the attitude information of each sub-mirror at the next moment.

[0057] In this embodiment of the invention, the current control input for each sub-mirror is calculated and determined by designing an H-infinite control law. ,Right now:

[0058] ;

[0059] in, This represents the current shared attitude information received by the nth connected sub-mirror, which is connected to the i-th sub-mirror, at time j. This represents the information weighting factor for the connected sub-mirrors of the i-th sub-mirror. K This represents the control gain matrix.

[0060] Information weighting factor in the above formula This is based on the feedback of system state or the dynamic adjustment of performance indicators over time, thereby changing the dependence of each sub-mirror on connected sub-mirrors. For example, if there is a large difference between the attitude information of the current sub-mirror and the attitude information of its connected sub-mirrors, the information weighting factor can be increased. The value is adjusted based more on the attitude information of the connected sub-mirrors; the information weighting factor is reduced as the error decreases. The value, in a common form, is obtained by adjusting the information weighting factor using the following formula:

[0061] ;

[0062] in, and These are the current attitude information of the a-th sub-mirror and the b-th sub-mirror, respectively. The a-th sub-mirror and the b-th sub-mirror are connected wirelessly via an intelligent agent.

[0063] The control gain matrix in the above formula K The following linear matrix inequalities need to be applied:

[0064] ;

[0065] This is transformed into a convex optimization problem with H infinity, where P denotes a symmetric positive definite matrix. , Denotes the upper bound of the H-norm. C and D represent the output matrix and transfer matrix, respectively, used to describe the relationship between the system output and its state and input. In this embodiment of the invention, by changing the variables, the problem is transformed from a non-convex form to a convex optimization form, thereby solving for the control gain matrix. K That is, introducing new variables and Using these new variables, the original inequality becomes a linear matrix inequality with respect to variables W and Y. Now, considering the state feedback problem, the control gain matrix in the original problem... K The solution can be achieved using the following formula:

[0066] ;

[0067] In this embodiment of the invention, convex optimization tools, such as LMI Solver or YALMIP in MATLAB, can be used to solve this type of linear matrix inequality problem. The convex optimization tool will determine the solution based on the defined objective function (i.e., the upper bound of the H infinity norm). To minimize the control gain matrix, we solve for variables W and Y. K .

[0068] The current control input for each sub-mirror is obtained from the above. Then, the dynamic model of each sub-mirror is combined. Obtain the current dynamic model for each sub-mirror for:

[0069] ;

[0070] The attitude information of each sub-mirror at the next moment is determined by the following formula. for:

[0071] ;

[0072] in, Indicates the time step.

[0073] S5: Repeat steps S2-S4 until the current attitude information of each sub-mirror converges to the ideal attitude information of each sub-mirror. The attitude information error of each sub-mirror at the next time step can be expressed as:

[0074] ;

[0075] The control input for each sub-mirror at the next moment can be expressed as:

[0076] .

[0077] It should be understood that the various forms of processes shown above can be used to reorder, add, or delete steps. For example, the steps described in this invention disclosure can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution disclosed in this invention can be achieved, and this is not limited herein.

[0078] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method for maintaining the surface shape of a spliced ​​telescope primary mirror based on multi-agent cooperative control, characterized in that: Includes the following steps: S1: An intelligent agent is set up on each sub-mirror in the main mirror, and the initial attitude information, ideal attitude information, and dynamic model of each sub-mirror are set; in step S1, the dynamic model of each sub-mirror... for: ； in, This represents the pose information of the i-th sub-mirror. This represents the control input for the i-th sub-mirror. A Represents the state matrix, B Represents the control matrix; S2: Obtain the current attitude information of each sub-mirror and subtract it from the ideal attitude information of each sub-mirror to obtain the current attitude information error of each sub-mirror; S3: Using the intelligent agent, each sub-mirror is wirelessly connected to other sub-mirrors, enabling the current attitude information of each sub-mirror to be shared in real time with the connected sub-mirrors, thereby obtaining the current shared attitude information received by each sub-mirror; in step S3, the current shared attitude information of each sub-mirror is determined by the following formula. for: ； in, This indicates the number of connected sub-mirrors connected to the i-th sub-mirror. This represents the total number of connected sub-mirrors connected to the i-th sub-mirror; S4: Based on the current attitude information of each sub-mirror and its current shared attitude information, determine the current control input and the current dynamic model of each sub-mirror, and then obtain the attitude information of each sub-mirror at the next moment. S5: Repeat steps S2 to S4 until the current pose information of each sub-mirror converges to the ideal pose information of each sub-mirror.

2. The method for maintaining the surface shape of the primary mirror of a spliced ​​telescope based on multi-agent cooperative control as described in claim 1, characterized in that: In step S4, the current control input for each sub-mirror is determined by the following formula. for: ； in, K Represents the control gain matrix. This represents the information weighting factor for the connected sub-mirrors of the i-th sub-mirror. This represents the current shared attitude information received by the nth connected sub-mirror, which is connected to the i-th sub-mirror, at time j. Then, the dynamic model of each sub-mirror is combined. Obtain the current dynamic model for each sub-mirror. for: ； The attitude information of each sub-mirror at the next moment is determined by the following formula. for: ； in, Indicates the time step.

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