MBD-based precise motion platform control method and control device

Abstract

The invention discloses a precision motion platform control method and device based on MBD, and relates to the technical field of precision motion control. The precision motion platform control method based on MBD comprises a standard compiling step, a bionic step and an integration step, on one hand, the precision motion platform control method based on MBD avoids manual adjustment or empirical rules to carry out system design and adjustment, and can evaluate the performance of a control system through simulation analysis before an actual system is built; the trial and error process and the development period are reduced; and on the other hand, an intuitive interface can be provided through a visual design and analysis tool.

Description

Technical Field

[0001] The present invention relates to the technical field of precision motion control, and in particular to a precision motion stage control method and control device based on MBD. Background Art

[0002] In the field of precision motion control, precision motion stage control methods are usually used for precision motion control. It focuses on designing, developing and optimizing high-precision, high-speed, and high-stability motion systems, which includes comprehensive consideration of precision mechanical structures, motion control algorithms, sensor technology, and real-time feedback systems. This field can achieve accurate control of precise position, speed, and acceleration to meet the needs of manufacturing, medical equipment, semiconductor manufacturing, optical systems, and other fields for high precision and reliability of motion systems.

[0003] The control method of the precision motion stage in the prior art, on the one hand, usually adopts manual adjustment or empirical rules to design and adjust the system, which relies on the experience and intuition of professionals and cannot evaluate the performance of the control system through simulation analysis before the actual system is built, which increases the trial and error process and development cycle. On the other hand, it cannot provide an intuitive interface through visual design and analysis tools. Summary of the invention

[0004] In view of this, the present invention proposes a precision motion table control method and control device based on MBD, the main purpose of which is to avoid using manual adjustment or empirical rules for system design and adjustment, and to evaluate the performance of the control system through simulation analysis before the actual system is built, thereby reducing the trial and error process and development cycle; and, providing an intuitive interface through visual design and analysis tools.

[0005] In order to achieve the above object, the present invention mainly provides the following technical solutions:

[0006] In a first aspect, the present invention provides a precision motion stage control method based on MBD, the method comprising:

[0007] Compile standard steps, create an MBD precision motion stage control model, and compile a model standard for the MBD precision motion stage control model, determine model information of the precision motion stage control model according to the model standard, and define and annotate the model information in the motion stage control model of the Simulink software;

[0008] Bionics step: Design the control algorithm of the MBD precision motion stage through iterative learning control theory and proportional integral differential control theory, and use Simulink software to simulate the dynamic behavior of the system to ensure that the control algorithm meets the target performance requirements;

[0009] In the integration step, the MBD precision motion stage control model verified by the bionic step is converted into executable code using the Embedded Coder toolbox, the generated executable code is deployed to the motion stage control system, and integrated with the actual hardware to realize intelligent control of the precision motion stage.

[0010] Furthermore, in the step of compiling the standard, the model standard for compiling the MBD precision motion stage control model includes:

[0011] Determine the mathematical model of the precision motion table system, the motion model of the permanent magnet synchronous linear motor and the state model of the MBD system;

[0012] Definition and creation standards of MBD precision motion stage control model, including basic definition of MBD precision motion stage control model and selection of software version;

[0013] MBD system standards, including the meaning of each module in the MBD precision motion stage control model, and the input and output annotations of each module;

[0014] MBD performance requirements include system stability, response speed, accuracy, and anti-interference capability.

[0015] Furthermore, in the step of compiling the standard, when determining the motion model of the permanent magnet linear synchronous motor, the control strategy of the permanent magnet linear synchronous motor is vector control with the q-axis current being 0, and the motion model of the permanent magnet linear synchronous motor is:

[0016]

[0017] Where M is the mass of the linear motor, x is the position of the motor, and K e is the electromagnetic thrust constant, F l is the load disturbance, B v is the mechanical damping coefficient, v is the mover speed, i q is the current along the q axis in the dq coordinate system.

[0018] Furthermore, in the step of compiling the standard, the state model of the MBD system is determined as:

[0019] If the state variables of the system are defined as:

[0020]

[0021] Then the state equation of the system is:

[0022]

[0023] Because M and B v , K eis a constant, F l It can be defined as a variable f(t,x) that changes with time and position. Then, at i q When the system input is the state equation of the system, it can be further simplified as

[0024]

[0025] Where U k (t) is the system control vector.

[0026] Furthermore, in the bionic step:

[0027] After designing the control algorithm of the MBD precision motion table through iterative learning control theory and proportional-integral-differential control theory, it also includes designing the motor three-loop controller, and then using Simulink software to simulate the dynamic behavior of the system.

[0028] Furthermore, the control systems of the motor three-loop controller are respectively position loop, speed loop and current loop from outside to inside;

[0029] The position loop generates a speed command through proportional, integral and differential control algorithms to make the motor rotate to the target position;

[0030] In the speed loop, the motor current command is generated according to the speed error using the proportional, integral and differential control algorithm;

[0031] The current loop generates phase current commands based on the current error.

[0032] Furthermore, the mathematical model of the proportional-integral-differential control is:

[0033]

[0034] u(t) is the control output, e(t) is the error, that is, the difference between the expected value and the actual value, Kp is the weight parameter of the proportion, Ki is the weight parameter of the integration, and Kd is the weight parameter of the differentiation. represents the integral of the error over time, represents the time derivative of the error.

[0035] Furthermore, the mathematical model of the iterative learning control is:

[0036]

[0037] Among them, e k (t) represents the tracking error between the target trajectory and the controlled object generated during the kth operation, that is:

[0038] e k (t) = y d (t)-yk (t)

[0039] The learning rate is the control given sequence of the system at the k+1th iteration, and the control given sequence of the system at the k+1th iteration is equal to the sum of the control given sequence of the system at the kth iteration and the tracking error generated in the current iteration after calculation by the controller.

[0040] In a second aspect, the present invention provides a precision motion stage control device based on MBD, the device comprising:

[0041] Compile standard units, create an MBD precision motion stage control model, and compile a model standard for the MBD precision motion stage control model, determine model information of the precision motion stage control model according to the model standard, and define and annotate the model information in the motion stage control model of the Simulink software;

[0042] Bionic unit, the control algorithm of MBD precision motion stage is designed through iterative learning control theory and proportional integral differential control theory, and the dynamic behavior of the system is simulated using Simulink software to ensure that the control algorithm meets the target performance requirements;

[0043] The integration unit converts the MBD precision motion stage control model verified by the bionic step into executable code using the Embedded Coder toolbox, deploys the generated executable code to the motion stage control system, and integrates it with the actual hardware to realize intelligent control of the precision motion stage.

[0044] In a third aspect, the present invention provides a computer-readable storage medium, wherein the storage medium includes a stored program, wherein when the program is running, the device where the storage medium is located is controlled to execute the MBD-based precision motion stage control method described in the first aspect.

[0045] In a fourth aspect, the present invention provides a storage management device, the storage management device comprising:

[0046] Memory, used to store programs;

[0047] A processor is coupled to the memory and is used to run the program to execute the MBD-based precision motion stage control method described in the first aspect.

[0048] By means of the above technical solution, the present invention provides a control method and a control device for a precision motion stage based on MBD. The control of the precision motion stage based on MBD, on the one hand, avoids the use of manual adjustment or empirical rules for system design and adjustment, and can evaluate the performance of the control system through simulation analysis before the actual system is built, thereby reducing the trial and error process and the development cycle. On the other hand, it can provide an intuitive interface through visual design and analysis tools.

[0049] The above description is only an overview of the technical solution of the present invention. In order to more clearly understand the technical means of the present invention, it can be implemented according to the contents of the specification. In order to make the above and other purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0051] Figure 1 The flowchart of the MBD-based precision motion stage control method provided by the present invention is shown;

[0052] Figure 2 It shows the comparison between the given trajectory and the actual trajectory when the precision motion platform based on MBD is running;

[0053] Figure 3 A schematic diagram of a precision motion stage control device based on MBD provided by the present invention is shown;

[0054] Description of Figure Numbers:

[0055] 1. MBD-based precision motion stage control device;

[0056] 11. Prepare standard units;

[0057] 12. Bionic unit;

[0058] 13. Integrated unit. DETAILED DESCRIPTION

[0059] The exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided in order to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0060] The embodiment of the present invention provides a precision motion stage control method based on MBD, such as Figure 1 As shown, the method mainly includes:

[0061] 101. Prepare standard steps, create the MBD precision motion stage control model, and prepare the model standard of the MBD precision motion stage control model. Determine the model information of the precision motion stage control model according to the model standard, and define and annotate the model information in the motion stage control model of the Simulink software.

[0062] In the standard preparation step, the model standard for preparing the MBD precision motion table control model includes the determination of the mathematical model of the precision motion table system, the definition and creation standard of the MBD precision motion table control model, the MBD system standard and the MBD performance requirement standard. The mathematical model of the precision motion table system is determined, and the motion model of the permanent magnet synchronous linear motor and the state model of the MBD system are determined. The definition and creation standard of the MBD precision motion table control model includes the basic definition of the MBD precision motion table control model and the selection of the software version. The MBD system standard includes the meaning of each module in the MBD precision motion table control model and the input and output labeling of each module. The MBD performance requirement standard includes system stability, response speed, accuracy, and anti-interference ability.

[0063] For example, the model information is:

[0064] The definition and creation standard of the MBD precision motion stage control model includes but is not limited to the basic definition of the MBD precision motion stage control model and the selection of the software version.

[0065] The MBD system standard includes but is not limited to the meaning of each module in the MBD model and the input and output annotations of each module.

[0066] The MBD performance requirement standards include but are not limited to system stability, response speed, accuracy, and anti-interference ability to ensure that the model has efficient, accurate, and stable control performance in actual applications.

[0067] 102. Bionics step: Design the control algorithm of MBD precision motion platform through iterative learning control theory and proportional integral differential control theory, and use Simulink software to simulate the dynamic behavior of the system to ensure that the control algorithm meets the target performance requirements.

[0068] In the bionic step, after designing the control algorithm of the MBD precision motion table through iterative learning control theory and proportional integral differential control theory, it also includes designing the motor three-loop controller, and then using Simulink software to simulate the dynamic behavior of the system.

[0069] 103. In the integration step, the MBD precision motion stage control model verified by the bionic step is converted into executable code using the Embedded Coder toolbox, the generated executable code is deployed to the motion stage control system, and integrated with the actual hardware to realize the intelligent control of the precision motion stage.

[0070] Specifically, Embedded Coder is a code generation tool developed specifically for embedded processors, and TargetLanguage Compiler, or TLC, is an object property description file that uses TLC to customize the generated code.

[0071] By automatically configuring the TLC language file and main template file of the complete model of the model, the replaced model is generated into the target machine C code, and then the generated makefile file is compiled and deployed into the x86 target machine. The custom module library dependency files contained in the model can be automatically called in the background to ensure the successful compilation and operation of the complete model.

[0072] After the user has built his own algorithm model, he can call the Embedded Coder tool to compile the model and generate the corresponding .c code file. After downloading the .c code file to the target machine, it is compiled to generate the corresponding executable file. When the Embedded Coder tool starts the model, it starts the executable file of the target machine.

[0073] The executable file performs IPC communication with the kernel driver model according to the corresponding code functions in the module library in Simulink, thereby controlling the operating parameters of the hardware acquisition board and receiving the collected IO signals.

[0074] When the executable file is running, the model operation parameters and IO acquisition signals will be transmitted via Ethernet. The IO signals of the signal acquisition board are transmitted to the host computer Simulink algorithm model in real time, and the corresponding hardware signals and algorithm results can be intuitively viewed in the Simulink model.

[0075] By simplifying the actual controller, the Embedded Coder can directly generate embedded codes, thereby further improving the maintainability and repeatability of the system.

[0076] In this embodiment, the precision motion stage control method is a precision motion stage control method based on MBD. On the one hand, it avoids the use of manual adjustment or empirical rules for system design and adjustment, and can evaluate the performance of the control system through simulation analysis before the actual system is built, thereby reducing the trial and error process and development cycle. On the other hand, it can provide an intuitive interface through visual design and analysis tools.

[0077] In the present invention, exemplarily, in the step of compiling the standard, when determining the motion model of the permanent magnet linear synchronous motor, the control strategy of the permanent magnet linear synchronous motor is vector control with q-axis current of 0, then the motion model of the permanent magnet linear synchronous motor is:

[0078]

[0079] Where M is the mass of the linear motor, x is the position of the motor, and K e is the electromagnetic thrust constant, F l is the load disturbance, B v is the mechanical damping coefficient, v is the mover speed, i q is the current along the q axis in the dq coordinate system.

[0080] The state model of the MBD system is determined as:

[0081] If the state variables of the system are defined as:

[0082]

[0083] Then the state equation of the system is:

[0084]

[0085] Because M and B v , K e is a constant, F l It can be defined as a variable f(t,x) that changes with time and position. Then, at i q When the system input is the state equation of the system, it can be further simplified as

[0086]

[0087] Where U k (t) is the system control vector.

[0088] In the present invention, the control system of the motor three-loop controller is respectively a position loop, a speed loop, and a current loop from the outside to the inside. The position loop generates a speed command through a proportional, integral, and differential control algorithm to rotate the motor to the target position. In the speed loop, a motor current command is generated according to the speed error using a proportional, integral, and differential control algorithm. The current loop generates a phase current command according to the current error.

[0089] Exemplarily, the iterative learning controller replaces the proportional-integral-derivative control in the position loop, thereby achieving the requirement of improving the tracking accuracy of the position signal, thereby completing the design of the control algorithm.

[0090] For example, in the process of simulating the dynamic behavior of the system using Simulink software: in the motor three-loop control model after the proportional integral differential control controller of the position loop is replaced with the iterative learning control controller, the iteration period is set to 1s, the specified trajectory is set to y=sin(2pi*t), the proportional integral differential controller parameters of the current loop are Kp=50, ki=5000, Kd=0, the proportional integral differential controller parameters of the speed loop are Kp=20, Ki=500, Kd=0, the PD parameters of the position loop are Kp=1000, Kd=0.5, and among the various parameters of the PMSM, the stator resistance R s =0.0485Ω, fixed axis inductance L q =0.000395H, moment of inertia J = 0.0027kg·m 2 .

[0091] After setting the above parameters, the Simulink simulation results are as follows: Figure 2 As shown, it can be seen that the actual trajectory can track the specified trajectory very well, which also provides the basis for further building the MBD model.

[0092] Furthermore, the mathematical model of proportional integral derivative control is:

[0093]

[0094] u(t) is the control output, e(t) is the error, that is, the difference between the expected value and the actual value, Kp is the weight parameter of the proportion, Ki is the weight parameter of the integration, and Kd is the weight parameter of the differentiation. represents the integral of the error over time, represents the time derivative of the error.

[0095] The mathematical model of iterative learning control is:

[0096]

[0097] Among them, e k (t) represents the tracking error between the target trajectory and the controlled object generated during the kth operation, that is:

[0098] e k (t) = y d (t)-y k (t)

[0099] The learning rate is the control given sequence of the system at the k+1th iteration, and the control given sequence of the system at the k+1th iteration is equal to the sum of the control given sequence of the system at the kth iteration and the tracking error generated in the current iteration after calculation by the controller.

[0100] The present invention enables users to accurately describe the dynamic characteristics of the precision motion stage through an accurate mathematical model, thereby improving the accuracy of system modeling. MBD introduces an automated adjustment and optimization model, dynamically adjusts system parameters through real-time feedback, improves system stability and performance, and avoids the tedious process of manual adjustment.

[0101] In the MBD-based precision motion stage control method, the visual design and analysis Simulink software tool provides an intuitive interface that makes it easier for users to understand and analyze system behavior, thereby accelerating the system design and tuning process. In addition, the ability to comprehensively optimize the complete system level improves the overall performance of the system, including accuracy, speed, and stability.

[0102] Further, according to the above method embodiment, another embodiment of the present invention also provides a precision motion stage control device based on MBD, such as Figure 3 As shown, the device includes a compilation standard unit 11, a bionic unit 12 and an integration unit 13. The compilation standard unit 11 creates an MBD precision motion stage control model, and compiles the model standard of the MBD precision motion stage control model, determines the model information of the precision motion stage control model according to the model standard, and defines and annotates the model information in the motion stage control model of the Simulink software. The bionic unit 12 designs the control algorithm of the MBD precision motion stage through iterative learning control theory and proportional integral differential control theory, and uses Simulink software to simulate the dynamic behavior of the system. The integration unit 13 uses the Embedded Coder toolbox to convert the MBD precision motion stage control model verified by the bionic step into executable code, deploys the generated executable code to the motion stage control system, and integrates it with the actual hardware to realize the intelligent control of the precision motion stage.

[0103] In this embodiment, the MBD-based precision motion stage control device 1 first creates an MBD precision motion stage control model by compiling a standard unit 11, and compiles a model standard of the MBD precision motion stage control model, determines the model information of the precision motion stage control model according to the model standard, and defines and annotates the model information in the motion stage control model of the Simulink software; in the bionic unit 12, the control algorithm of the MBD precision motion stage is designed through iterative learning control theory and proportional integral differential control theory, and the dynamic behavior of the system is simulated using Simulink software to ensure that the control algorithm meets the target performance requirements; finally, in the integration unit 13, the Embedded Coder toolbox is used to convert the MBD precision motion stage control model verified by the bionic step into executable code, the generated executable code is deployed to the motion stage control system, and integrated with the actual hardware to realize the intelligent control of the precision motion stage.

[0104] The MBD precision motion stage control device provided by the embodiment of the present invention, on the one hand, avoids the use of manual adjustment or empirical rules for system design and adjustment, and can evaluate the performance of the control system through simulation analysis before the actual system is built, thereby reducing the trial and error process and development cycle. On the other hand, it can provide an intuitive interface through visual design and analysis tools.

[0105] In the MBD precision motion stage control device provided in the embodiment of the present invention, the detailed description of the method used in the operation process of each functional module can be found in Figure 1 The corresponding method of the method embodiment is explained in detail and will not be repeated here.

[0106] Further, according to the above embodiment, another embodiment of the present invention further provides a computer-readable storage medium, the storage medium includes a stored program, wherein when the program is running, the device where the storage medium is located is controlled to execute Figure 1 MBD-based precision motion stage control method.

[0107] Further, according to the above embodiment, another embodiment of the present invention further provides a storage management device, the storage management device comprising:

[0108] Memory, used to store programs;

[0109] A processor, coupled to the memory, for running a program to perform Figure 1 MBD-based precision motion stage control method.

[0110] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0111] It is understandable that the related features in the above methods and devices can be referenced to each other. In addition, the "first", "second" and the like in the above embodiments are used to distinguish the embodiments, and do not represent the advantages and disadvantages of the embodiments.

[0112] Those skilled in the art will appreciate that the embodiments of the present disclosure may be provided as methods, systems, or computer program products. Therefore, the embodiments of the present disclosure may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the embodiments of the present disclosure may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0113] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products of the embodiments of the present disclosure. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0114] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0115] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0116] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0117] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0118] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0119] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0120] It should be understood by those skilled in the art that the embodiments of the present disclosure may be provided as methods, systems or computer program products. Therefore, the embodiments of the present disclosure may take the form of a complete hardware embodiment, a complete software embodiment or an embodiment combining software and hardware. Moreover, the embodiments of the present disclosure may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0121] The above are only embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included within the scope of the claims of the present application.

Claims

1. A precision motion stage control method based on MBD, characterized in that: include: Compile standard steps, create an MBD precision motion stage control model, and compile a model standard for the MBD precision motion stage control model, determine model information of the precision motion stage control model according to the model standard, and define and annotate the model information in the motion stage control model of the Simulink software; Bionics step: Design the control algorithm of the MBD precision motion stage through iterative learning control theory and proportional integral differential control theory, and use Simulink software to simulate the dynamic behavior of the system to ensure that the control algorithm meets the target performance requirements; In the integration step, the MBD precision motion stage control model verified by the bionic step is converted into executable code using the Embedded Coder toolbox, the generated executable code is deployed to the motion stage control system, and integrated with the actual hardware to realize intelligent control of the precision motion stage.

2. The MBD-based precision motion stage control method according to claim 1, characterized in that: In the step of compiling the standard, the model standard for compiling the MBD precision motion stage control model includes: Determine the mathematical model of the precision motion table system, the motion model of the permanent magnet synchronous linear motor and the state model of the MBD system; Definition and creation standards of MBD precision motion stage control model, including basic definition of MBD precision motion stage control model and selection of software version; MBD system standards, including the meaning of each module in the MBD precision motion stage control model, and the input and output annotations of each module; MBD performance requirements include system stability, response speed, accuracy, and anti-interference capability.

3. The MBD-based precision motion stage control method according to claim 2, characterized in that: In the standard preparation step, when determining the motion model of the permanent magnet linear synchronous motor, the control strategy of the permanent magnet linear synchronous motor is vector control with q-axis current of 0, and the motion model of the permanent magnet linear synchronous motor is: Where M is the mass of the linear motor, x is the position of the motor, and K e is the electromagnetic thrust constant, F l is the load disturbance, B v is the mechanical damping coefficient, v is the mover speed, i q is the current along the q axis in the dq coordinate system.

4. The MBD-based precision motion stage control method according to claim 3, characterized in that: In the standard compilation step, the state model of the MBD system is determined as: If the state variables of the system are defined as: Then the state equation of the system is: Because M and B v , K e is a constant, F l It can be defined as a variable f(t,x) that changes with time and position. Then, at i q When the system input is the state equation of the system, it can be further simplified as Where U k (t) is the system control vector.

5. The MBD-based precision motion stage control method according to claim 1, characterized in that: In the biomimetic step: After designing the control algorithm of the MBD precision motion table through iterative learning control theory and proportional-integral-differential control theory, it also includes designing the motor three-loop controller, and then using Simulink software to simulate the dynamic behavior of the system.

6. The MBD-based precision motion stage control method according to claim 5, characterized in that: The control systems of the motor three-loop controller are position loop, speed loop and current loop from outside to inside; The position loop generates a speed command through proportional, integral and differential control algorithms to make the motor rotate to the target position; In the speed loop, the motor current command is generated according to the speed error using the proportional, integral and differential control algorithm; The current loop generates phase current commands based on the current error.

7. The MBD-based precision motion stage control method according to claim 5, characterized in that: The mathematical model of the proportional integral derivative control is: u(t) is the control output, e(t) is the error, that is, the difference between the expected value and the actual value, Kp is the weight parameter of the proportion, Ki is the weight parameter of the integration, and Kd is the weight parameter of the differentiation. represents the integral of the error over time, represents the time derivative of the error.

8. The MBD-based precision motion stage control method according to claim 5, characterized in that: The mathematical model of the iterative learning control is: Among them, e k (t) represents the tracking error between the target trajectory and the controlled object generated during the kth operation, that is: e k (t)=y d (t)-y k (t) The learning rate is the control given sequence of the system at the k+1th iteration, and the control given sequence of the system at the k+1th iteration is equal to the sum of the control given sequence of the system at the kth iteration and the tracking error generated in the current iteration after calculation by the controller.

9. A precision motion stage control device based on MBD, characterized in that: The device comprises: Compile standard units, create an MBD precision motion stage control model, and compile a model standard for the MBD precision motion stage control model, determine model information of the precision motion stage control model according to the model standard, and define and annotate the model information in the motion stage control model of the Simulink software; Bionic unit, the control algorithm of MBD precision motion stage is designed through iterative learning control theory and proportional integral differential control theory, and the dynamic behavior of the system is simulated using Simulink software to ensure that the control algorithm meets the target performance requirements; The integration unit converts the MBD precision motion stage control model verified by the bionic step into executable code using the Embedded Coder toolbox, deploys the generated executable code to the motion stage control system, and integrates it with the actual hardware to realize intelligent control of the precision motion stage.

10. A computer-readable storage medium, characterized in that: The storage medium includes a stored program, wherein when the program is executed, the device where the storage medium is located is controlled to execute the MBD-based precision motion stage control method according to any one of claims 1 to 8.

Images