Vibration suppression control method and system for flexible base space manipulator

Abstract

The invention belongs to the field of space manipulators, and relates to a vibration suppression control method and system for a flexible base space manipulator, and the method is based on a Lagrangian method and considers multiple coupling effects to completely establish a dynamic model of the flexible base space manipulator system. An inertia matrix estimation item is constructed based on a parameter identification method to realize motion decoupling of the space manipulator, and a control law is designed based on a fast and slow subsystem theory to realize high-precision control of an assembly task of a space manipulator module and vibration suppression of a flexible base. And mechanical arm fine assembly operation control and base vibration suppression control for the flexible base space mechanical arm are achieved. The problem of how to complete a high-precision assembly task on the basis of restraining vibration of the base of the double-space mechanical arm is solved.

Description

Technical Field

[0001] The present invention belongs to the technical field of space manipulators, and in particular relates to a vibration suppression control method and system for a flexible base space manipulator. Background Art

[0002] The space manipulator has high flexibility and autonomous operation capability, and can perform various delicate operations in complex space environments, such as satellite capture, equipment maintenance, structural assembly, etc. Therefore, the space manipulator has broad application prospects in the aerospace field and can be used for satellite services, space station construction, astronaut assistance and other tasks, promoting space exploration and technological development.

[0003] Most of the space manipulators operating in orbit are installed on flexible floating bases such as space stations and satellites. When performing high-precision assembly tasks such as antennas and mirrors, the coupling between the space manipulator and the flexible base will cause the base to vibrate in a way that is difficult to observe.

[0004] Therefore, how to enable the space robot arm to complete high-precision assembly tasks while suppressing the vibration of the base is the current research focus.

[0005] Although a single robot arm performs well in many tasks, the advantages of dual robot arms are more significant in complex assembly tasks. Dual robot arms can better simulate the mode of collaborative work of human hands. Through division of labor and cooperation, multiple tasks can be handled at the same time, greatly improving assembly efficiency. In addition, dual robot arms are more flexible in spatial operations and can cope with complex three-dimensional space tasks, further expanding the scope of application of robot arms in industrial automation. Although the prior art considers the use of active damping control to suppress the vibration of the flexible base and other issues, it only considers the vibration suppression effect of the base under the trajectory movement of a single robot arm, and does not consider the dual-arm operation scenario, that is, it does not accurately model the coupling system between the dual-space robot arm and the assembly module under the module fine operation assembly task, and does not design a control law for the dual-space robot arm system, and cannot achieve precise control of the dual-space robot arm coupling system to perform assembly tasks while suppressing the vibration of the base. In addition, the prior art lacks the design of excitation functions for the spatial environment and operation scenarios in the process of realizing the decoupling of the spatial robot arm and the flexible base, and the accuracy of the robot arm parameter identification is lacking. Summary of the invention

[0006] In view of the shortcomings of the prior art described above, the purpose of the present invention is to provide a vibration suppression control method and system for a flexible base space manipulator, and to accurately model the multiple coupling systems, wherein the first level is the coupling modeling between the dual manipulators, and the second level is the coupling modeling between the dual manipulators and the flexible base, thereby obtaining the overall dynamic model of the flexible base space manipulator system. After the dual manipulators are decoupled from the flexible base through parameter identification, the nonlinear model predictive control introduced in the fast system is used to accurately couple the dual manipulators to perform fine assembly tasks. The present invention solves the problem of how the dual space manipulator system can complete high-precision assembly tasks on the basis of suppressing base vibrations through multiple coupling modeling, one-time decoupling, and the use of coupling control input for the dual space manipulator in the fast system.

[0007] To achieve the above purpose, the present invention adopts the following technical solution.

[0008] A first aspect of the present invention provides a vibration suppression control method for a flexible base space robot arm, which is applied to an assembly task scenario of a dual space robot arm facing a module to be assembled, and comprises the following steps: Based on the closed-chain constraints between the dual-space manipulators and the modules to be assembled, a dual-coupling system dynamics model is established. Then, the flexible base space manipulator system dynamics model is established by considering the coupling between the manipulators and the flexible base. A windowed finite-term Fourier series trajectory based on condition number optimization is designed as the excitation trajectory for parameter identification of the space manipulator. The two space manipulators are simultaneously excited to obtain two sets of inertia parameters of the space manipulators respectively. According to the inertia parameter sets of the space manipulators, an inertia matrix estimation term is constructed to decouple the motion of the flexible base and the dual space manipulators. The control law is designed based on the theory of fast and slow subsystems. The control part of the dual-space manipulator is regarded as the fast system, and the moving part of the flexible base is regarded as the slow system. Considering the coupling effect of the dual-space manipulator system, a nonlinear model predictive controller is designed to calculate the optimal control input of the fast system. An equivalent Kelvin-Voigt model of the flexible base and the environment is established to calculate the equivalent environmental force to suppress vibration and use it as the control input of the slow system, thereby realizing the dual-arm fine assembly of the flexible base space manipulator and the vibration suppression control of the flexible base.

[0009] As an optional implementation, the establishment of a dynamic model of the flexible base space manipulator includes: Establish the coordinate system of the flexible base space manipulator coupling system; Based on the flexible base space manipulator coupling system coordinate system, the flexible base space manipulator coupling system coordinate system includes a flexible base centroid coordinate system ∑ b , left robot end effector coordinate system∑ l , right robot end effector coordinate system∑ r, assembly module centroid coordinate system∑ o , inertial coordinate system∑ e ; Assuming that the end effector of each space manipulator is fixedly connected to the module during the module assembly task, the kinematic constraint between the coordinate system of the end effector of the space manipulator and the coordinate system of the center of mass of the module is established: ; in: Represents the position vector of each spatial manipulator end coordinate system in the inertial coordinate system; Represents the position vector of the module coordinate system in the inertial coordinate system; Represents the position vector of the module's center of mass to the coordinate system of each spatial manipulator end; Represents the attitude rotation matrix of each space manipulator end coordinate system in the inertial coordinate system; Represents the attitude rotation matrix of the module coordinate system in the inertial coordinate system; Represents the attitude rotation matrix of each space robot end coordinate system relative to the module center of mass coordinate system; represents the skew-symmetric matrix operator for vector cross product; and Respectively represent the rotation angular velocity of each spatial manipulator end effector and the module center of mass coordinate system; Establish the dynamic model of the module to be assembled: ; in: Module inertia matrix, is the nonlinear term related to module speed, represents the resultant force and moment applied by the space manipulator to the center of mass of the module, It represents the net force and net moment applied by the environment to the center of mass of the object; Establish the dynamic model of the dual-space manipulator coupling system: ; in: Represents the coupling inertia matrix of the two space manipulators. , This is the coupling inertia matrix of the left manipulator after adding the dynamic closed-chain constraint. is the inertia matrix of the left robotic arm, is the load distribution coefficient of the left robot arm, is the Jacobian matrix of the left robot arm, , This is the coupling inertia matrix of the right manipulator after adding the dynamic closed-chain constraint. is the inertia matrix of the right robotic arm, is the load distribution coefficient of the right robot arm, is the Jacobian matrix of the right robot arm; represents the coupling nonlinear term of the two space manipulators related to the generalized velocity. , This is the nonlinear term of the left manipulator coupling after adding the dynamic closed-chain constraint. is the nonlinear term of the left manipulator, , This is the nonlinear term of the right manipulator coupling after adding the dynamic closed-chain constraint. is the nonlinear term of the right robotic arm; Represents the joint angular displacement vectors of the two robotic arms; Establish the dynamic model of the flexible base space manipulator: ; Wherein: the flexible base space manipulator is a flexible base with m degrees of freedom and two n-degree-of-freedom space manipulators; represents the generalized displacement vector of the flexible base, represents the inertia matrix of the flexible base, represents the damping matrix of the flexible base, represents the stiffness matrix of the flexible base; Represents the inertial coupling matrix between the two space manipulators and the base; and represents the nonlinear term related to the generalized velocity; Represents the joint torque of the two spatial manipulators.

[0010] As an optional implementation, the design is based on the space manipulator parameter identification excitation trajectory of condition number optimization, and two space manipulators are simultaneously excited to obtain two space manipulator inertia parameter sets respectively, and an inertia matrix estimation item is constructed according to the space manipulator inertia parameter sets to perform motion decoupling of the flexible base and the dual space manipulators, including: Design a space manipulator parameter identification excitation trajectory based on condition number optimization, simultaneously excite two space manipulators to obtain two space manipulator inertia parameter sets respectively, collect data obtained by the space manipulator moving along the excitation trajectory, and solve the space manipulator inertia parameter set by the least square method. Construct an inertia matrix estimation term based on the inertia parameter set of the space manipulator , the motion of the flexible base and the dual-space manipulator is decoupled, and the dynamic model of the decoupled dual-space manipulator coupling system is obtained.

[0011] As an optional implementation, the design is based on the condition number optimization of the space manipulator parameter identification excitation trajectory, respectively collecting data obtained by the two space manipulators moving along the excitation trajectory, and solving the space manipulator inertial parameter set by the least squares method, including: Aiming at the zero-microgravity working environment of the space manipulator and the working characteristics of the manipulator's fine work in assembly tasks, a windowed finite-term Fourier series trajectory is designed as the excitation trajectory for the space manipulator's parameter identification to improve the signal quality and accuracy, which is suitable for the space manipulator's parameter identification under low-frequency dynamic characteristics. The excitation trajectories of each joint of the two spatial manipulators are: q i t = ∑ k =1 K [ a k , i w f l sin w f kt - b k , i w f l cos w f kt ] ∙ w ( k ) + q i 0 ; in: represents the fundamental frequency; K represents the number of Fourier coefficient terms; k represents the kth Fourier coefficient term; and is the amplitude of the sine and cosine functions of the i-th joint, The constant term representing the position of the i-th joint; represents the Hamming window, and its expression is: ; The angular velocity expression corresponding to the excitation trajectory of each joint is: q ̇ i t = ∑ k =1 K [ a k , i cos w f kt + b k , i sin w f kt ]∙ w ( k ) ; The angular acceleration expression corresponding to the excitation trajectory of each joint is: q ̈ i t = w f ∑ k =1 K [ b k , i l cos w f kt - a k , i l sin w f kt ]∙ w ( k ) ; The condition number is used as the optimization index of the excitation trajectory, and the sampling data obtained by the space manipulator moving along the excitation trajectory are ) to form the total vector matrix , define the matrix condition number as: ; Add constraints for the motion of the space manipulator: ; in: , and Indicates the maximum absolute value of the joint angle, joint angular velocity, and joint angular acceleration of the space manipulator. and Indicates the start and end time of a single excitation cycle; By solving the minimum problem of nonlinear multivariate function, , and As the parameter to be optimized in the excitation trajectory model, the matrix Minimum value, and then get the excitation trajectory of the space manipulator parameter identification; Solve the inertial parameter set of the space manipulator based on the least squares method: ; in: Y _ =[ q m t 1 , q ̇ m t 1 , q ̈ m t 1 ;⋯; q m t 2 n , q ̇ m t 2 n , q ̈ m t 2 n ] and They are the joint motion sequence and torque sequence obtained by the space manipulator following the optimized excitation trajectory. is the inertial parameter set of the space manipulator.

[0012] As an optional implementation, the inertia matrix estimation term is constructed according to the inertia parameter set of the space manipulator. , decouple the motion of the flexible base and the space manipulator, and obtain the decoupled dual space manipulator coupling system dynamics model, including: Constructing the inertia matrix estimation term composed of the inertia parameter set of the space manipulator , and substitute the estimated inertia matrix into the dynamic model of the flexible base space manipulator: ; Will The remaining items are combined into unknown items : ; in: is the input torque of the controller at the last moment. When the sampling frequency is higher than the preset sampling frequency , the unknown Substitute the dynamic model of the flexible base space manipulator and add the control input u to obtain the decoupled dynamic model of the space manipulator: ; The dynamic model of the flexible base space manipulator after decoupling the flexible base from the dual space manipulator is: .

[0013] As an optional implementation, the control law is designed based on the theory of fast and slow subsystems, with the control part of the manipulator as the fast system and the moving part of the flexible base as the slow system, including: The control law is designed based on the theory of fast and slow subsystems. The module assembly task trajectory tracking control of the space manipulator and the vibration suppression of the base are simultaneously realized through the control input u. It is defined that u consists of two parts: ; in: Acting on the movement of the robot arm, Acting on the base movement; Different from the single-space robot, after the decoupling of the dual-space robot and the flexible base is completed, the closed-chain constraint directly formed by the dual-space robot and the module makes the dual-space robot system still a nonlinear strong coupling system. The conventional PD control law cannot accurately control the dual-space robot to perform assembly tasks at the same time. Therefore, a nonlinear model predictive controller is introduced to calculate the optimal control increment of the fast system at each moment. , define the joint state vector x = [ q m , q ̇ m ] T , output , combined with the decoupled dual-space robotic arm system dynamics model, the continuous state equation of the dual-space robotic arm system is constructed: ; The continuous state equation is processed linearly and discretely to obtain the discrete time linearized state equation of the dual space manipulator system, i.e. the prediction model: ; in: , and are the state and control coefficients, respectively, which can be calculated from the expected trajectory and are constants in the prediction time domain N. is the current sampling time, For those who need to predict Optimal control increment at every moment; According to the prediction model, the time domain N after the sampling time is predicted, and the state vector of the system in the prediction time domain is expressed as: ; in: represents the predicted state vector of the system, represents the assumed control input vector of the system in the prediction domain, , and Reason , and The prediction iteration coefficient matrix composed of; Constructing the optimization objective function of the dual-space manipulator system , the expression is: ; in: It represents the tracking error vector of the system in the prediction time domain, that is, the tracking error between the expected trajectory of the module center of mass and the actual trajectory of the joint obtained by the kinematic closed chain constraint and the inverse kinematics solution of the manipulator. is the state error weight matrix of the dual-space manipulator system. Based on the least squares principle and the optimization objective function, the optimal control problem is transformed into a quadratic programming problem: ; in: , is the limit value of the joint angle of the space manipulator, , Input limit values ​​for the space manipulator fast system control, , is the limit value of the control input increment of the space manipulator fast system. According to the gradient optimization principle, the optimal control input increment of the fast system is obtained as follows: ; in: is the expected joint state vector of the dual-space manipulator at the sampling time, The lower triangular identity matrix, the optimal control input of the fast system can be obtained by the optimal control input increment: ; Consider the vibration of the flexible base as establishing a Kelvin-Voigt model with the environment, and the force generated by the environment on the flexible base is expressed as: ; in: is the equivalent stiffness of the Kelvin-Voigt model, is the equivalent viscous damping coefficient of the Kelvin-Voigt model. Combined with the decoupled flexible base space manipulator dynamics model, the slow system control input expression for suppressing base vibration is: u slow , k q b = - H bm q b , q md , k H ̂ m - 1 [ k e q b + b e q ̇ b ] ; in: represents the expected joint angle of the space manipulator at time k, Then the overall control law of the flexible base space manipulator is obtained: .

[0014] A second aspect of the present invention provides a vibration suppression control system for a flexible base space robot arm, which is applied to an assembly task scenario of a dual space robot arm facing a module to be assembled, and includes: The motion constraint unit is at least used to establish a dual-space manipulator coupling system dynamics model based on the closed-chain constraint between the dual-space manipulator and the assembly model, and then consider the manipulator and the flexible base to establish a flexible base space manipulator system dynamics model; A motion decoupling unit is at least used to design a space manipulator parameter identification excitation trajectory based on condition number optimization, and simultaneously excite two space manipulators to obtain two space manipulator inertia parameter sets respectively, and construct an inertia matrix estimation item according to the space manipulator inertia parameter sets to perform motion decoupling between the flexible base and the dual space manipulators; The vibration suppression control unit is at least used to design the control law based on the theory of fast and slow subsystems, taking the control part of the manipulator as the fast system and the moving part of the flexible base as the slow system, so as to realize the vibration suppression control of the flexible base space manipulator.

[0015] In summary, compared with the prior art, the present invention is a vibration suppression control of the base and a fine assembly operation control of the robot arm, rather than a vibration suppression control of the robot arm. The single-arm control disclosed in the prior art does not involve dual-arm coupling control, and cannot achieve precise control of the assembly operations of the two robot arms. The multiple coupling modeling specifically embodied in the present invention, the first level is the coupling modeling between the dual robot arms, and the second level is the coupling modeling between the dual robot arms and the flexible base, thereby obtaining the dynamic model of the entire system, which is a multiple coupling dynamic model. The present invention uses nonlinear model predictive control to solve the optimal control input of the fast system. In this way, dual robot arm coupling control can be achieved, and the assembly task can be better completed. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For those skilled in the art, other drawings can be obtained based on these drawings without creative work.

[0017] Figure 1 It is a flow chart of a vibration suppression control method for a flexible base space robot arm according to an embodiment of the present invention.

[0018] Figure 2 It is a flow chart of another vibration suppression control method for a flexible base space robot arm according to an embodiment of the present invention.

[0019] Figure 3 It is a schematic diagram of the assembly task scenario and coordinate system of the flexible base dual-space robotic arm module according to an embodiment of the present invention.

[0020] Figure 4 It is a flow chart of another vibration suppression control method for a flexible base space robot arm according to an embodiment of the present invention.

[0021] Figure 5 It is a flow chart of another vibration suppression control method for a flexible base space robot according to an embodiment of the present invention.

[0022] Figure 6 It is a control logic diagram of the space manipulator part of an embodiment of the present invention.

[0023] Figure 7 It is a control logic diagram of the flexible base empty dual space robot arm of an embodiment of the present invention.

[0024] Figure 8 The block diagram is a vibration suppression control system for a flexible base space robot according to an embodiment of the present invention. DETAILED DESCRIPTION

[0025] In the following description, specific details such as specific system structures, technologies, etc. are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present application. However, it should be clear to those skilled in the art that the present application may also be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to prevent unnecessary details from obstructing the description of the present application.

[0026] It should be understood that when used in this specification and the appended claims, the term "comprising" indicates the presence of described features, integers, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or groups thereof.

[0027] It should also be understood that the terms used in this application specification are only for the purpose of describing specific embodiments and are not intended to limit the application. As used in this application specification and the appended claims, the singular forms "a", "an" and "the" are intended to include plural forms unless the context clearly indicates otherwise.

[0028] The following is a clear and complete description of the technical solutions in the embodiments of the present application in conjunction with the drawings of the present application specification. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0029] It should be noted that the description order of the following embodiments is not intended to limit the preferred order of the embodiments of the present application. In addition, in the following embodiments, the description of each embodiment has its own emphasis, and for parts not described in detail in one embodiment, reference can be made to the relevant description of other embodiments.

[0030] like Figure 1 and Figure 2 As shown, the first aspect of the present invention provides a vibration suppression control method for a flexible base space robot arm, which is applied to an assembly task scenario of a dual space robot arm facing a module to be assembled, and includes the following steps: Step S100: Based on the closed-chain constraints between the dual-space manipulators and the modules to be assembled, a dual-coupling system dynamics model is established, and then a flexible base space manipulator system dynamics model is established by considering the coupling between the manipulators and the flexible base; Step S200: designing a windowed finite-term Fourier series trajectory based on condition number optimization as a spatial manipulator parameter identification excitation trajectory, simultaneously stimulating two spatial manipulators to obtain two spatial manipulator inertia parameter sets respectively, and constructing an inertia matrix estimation term according to the spatial manipulator inertia parameter sets to perform motion decoupling between the flexible base and the dual spatial manipulators; Step S300: Design the control law based on the theory of fast and slow subsystems, take the control part of the dual-space manipulator as the fast system, and the moving part of the flexible base as the slow system, consider the coupling effect of the dual-space manipulator system to design a nonlinear model predictive controller to calculate the optimal control input of the fast system, establish an equivalent Kelvin-Voigt model of the flexible base and the environment to calculate the equivalent environmental force to suppress vibration and use it as the control input of the slow system, so as to realize the dual-arm fine assembly of the flexible base space manipulator and the flexible base vibration suppression control.

[0031] Here, this method can solve the control accuracy problem of the module assembly task of the space robot arm under zero microgravity and the vibration suppression stability problem of the flexible base.

[0032] like Figure 3 and Figure 4 As shown, in one embodiment of the present invention, in step S100, the dual-coupling system dynamics model is established based on the closed-chain constraint between the dual-space manipulator and the module to be assembled, and then the flexible base space manipulator system dynamics model is established considering the coupling between the manipulator and the flexible base, including: Step S110: Establishing a flexible base space manipulator coupling system coordinate system, wherein the flexible base space manipulator coupling system coordinate system includes a flexible base centroid coordinate system ∑ b , left robot end effector coordinate system∑ l , right robot end effector coordinate system∑ r , assembly module centroid coordinate system∑ o , inertial coordinate system∑ e ; Step S120: Assuming that the end effector of each space robot is fixedly connected to the module during the module assembly task, a kinematic constraint between the coordinate system of the end effector of the space robot and the coordinate system of the center of mass of the module is established: ; in: Represents the position vector of each spatial manipulator end coordinate system in the inertial coordinate system; Represents the position vector of the module coordinate system in the inertial coordinate system; Represents the position vector of the module's center of mass to the coordinate system of each spatial manipulator end; Represents the attitude rotation matrix of each space manipulator end coordinate system in the inertial coordinate system; Represents the attitude rotation matrix of the module coordinate system in the inertial coordinate system; Represents the attitude rotation matrix of each space robot end coordinate system relative to the module center of mass coordinate system; represents the skew-symmetric matrix operator for vector cross product; and Respectively represent the rotation angular velocity of each spatial manipulator end effector and the module center of mass coordinate system; Step S130: Establishing a dynamic model of the module to be assembled: ; in: Module inertia matrix, is the nonlinear term related to module speed, represents the resultant force and moment applied by the space manipulator to the center of mass of the module, It represents the net force and net moment applied by the environment to the center of mass of the object; Step S140: Establishing a dual-space manipulator coupling system dynamics model: ; in: Represents the coupling inertia matrix of the two space manipulators. , This is the coupling inertia matrix of the left manipulator after adding the dynamic closed-chain constraint. is the inertia matrix of the left robotic arm, is the load distribution coefficient of the left robot arm, is the Jacobian matrix of the left robot arm, , This is the coupling inertia matrix of the right manipulator after adding the dynamic closed-chain constraint. is the inertia matrix of the right robotic arm, is the load distribution coefficient of the right robot arm, is the Jacobian matrix of the right robot arm; represents the coupling nonlinear term of the two space manipulators related to the generalized velocity. , This is the nonlinear term of the left manipulator coupling after adding the dynamic closed-chain constraint. is the nonlinear term of the left manipulator, , This is the nonlinear term of the right manipulator coupling after adding the dynamic closed-chain constraint. is the nonlinear term of the right robotic arm; Represents the joint angular displacement vectors of the two robotic arms; Step S150: Establishing a dynamic model of the flexible base space manipulator: .

[0033] Specifically, the purpose of establishing the flexible base space manipulator coupling system coordinate system is to determine the three-dimensional position information of the manipulator end effector and the object's center of mass. Furthermore, the kinematic closed-chain constraint described in the present invention is also established in accordance with the flexible base space manipulator coupling system coordinate system. Figure 3 As shown, the flexible base space manipulator coupling system coordinate system corresponds to Figure 3 Each sub-coordinate system in ∑ l ,∑ e The general term for etc. is based on Figure 3 In the present invention, the establishment of the coordinate system of the flexible base space manipulator coupling system is the basis for the motion control of each manipulator, and the establishment of the coordinate system of each scene or working environment is different.

[0034] In an application scenario, the flexible base space robot is a flexible base with m degrees of freedom and two space robots with n degrees of freedom.

[0035] Specifically, represents the generalized displacement vector of the flexible base, Represents the joint angular displacement vectors of the two robotic arms; represents the inertia matrix of the flexible base, represents the damping matrix of the flexible base, represents the stiffness matrix of the flexible base; Represents the inertia matrix of the two space manipulators; Represents the inertial coupling matrix between the two space manipulators and the base; and represents the nonlinear term related to the generalized velocity; Represents the joint torque of the two spatial manipulators.

[0036] Here, in this way, the expected movement trajectories of the two spatial robot end effectors can be solved based on the kinematic closed-chain constraints according to the module expected trajectories.

[0037] like Figure 5 As shown, in one embodiment of the present invention, in step S200, the design is based on the condition number optimization-based spatial manipulator parameter identification excitation trajectory, and two spatial manipulators are simultaneously excited to obtain two spatial manipulator inertia parameter sets respectively, and an inertia matrix estimation term is constructed according to the spatial manipulator inertia parameter sets to perform motion decoupling of the flexible base and the dual spatial manipulators, including: Step S210: designing a spatial manipulator parameter identification excitation trajectory based on condition number optimization, simultaneously exciting two spatial manipulators to obtain two spatial manipulator inertia parameter sets respectively, collecting data obtained when the spatial manipulators move along the excitation trajectory, and solving the spatial manipulator inertia parameter set by using the least squares method; Step S220: Constructing an inertia matrix estimation term according to the inertia parameter set of the space manipulator , the motion of the flexible base and the space robot is decoupled, and the dynamic model of the decoupled dual space robot coupling system is obtained.

[0038] Furthermore, the design is based on the space manipulator parameter identification excitation trajectory optimized by the condition number, and the data obtained by the two space manipulators moving according to the excitation trajectory are respectively collected, and the inertial parameter set of the space manipulator is solved by the least square method, including: Aiming at the zero-microgravity working environment of the space manipulator and the working characteristics of the manipulator's fine work in assembly tasks, a windowed finite-term Fourier series trajectory is designed as the excitation trajectory for the space manipulator's parameter identification to improve the signal quality and accuracy, which is suitable for the space manipulator's parameter identification under low-frequency dynamic characteristics. The specific expression of the excitation trajectory of each joint of the two spatial manipulators is: q i t = ∑ k =1 K [ a k , i w f l sin w f kt - b k , i w f l cos w f kt ] ∙ w ( k ) + q i 0 ; in: represents the fundamental frequency; K represents the number of Fourier coefficient terms; k represents the kth Fourier coefficient term; and is the amplitude of the sine and cosine functions of the i-th joint, represents the constant term of the i-th joint position, and t represents the time. represents the Hamming window, whose main lobe is narrower and has a higher resolution for the parameters of the space manipulator at different frequencies. Its expression is: .

[0039] Among them, the angular velocity expression corresponding to the excitation trajectory of each joint is: q ̇ i t = ∑ k =1 K [ a k , i cos w f kt + b k , i sin w f kt ]∙ w ( k ) .

[0040] Among them, the angular acceleration expression corresponding to the excitation trajectory of each joint is: q ̈ i t = w f ∑ k =1 K [ b k , i l cos w f kt - a k , i l sin w f kt ]∙ w ( k ) .

[0041] Furthermore, the condition number is used as the optimization index of the excitation trajectory, and the sampling data obtained by the space manipulator moving along the excitation trajectory are ) to form the total vector matrix , define the matrix condition number as: .

[0042] Furthermore, constraints on the motion of the space manipulator are added: ; in: , and They correspond to the maximum absolute values ​​of the joint angle, joint angular velocity and joint angular acceleration of the space manipulator, respectively. and Indicates the start and end time of a single excitation cycle.

[0043] Furthermore, by solving the minimum problem of nonlinear multivariate functions, , and As the parameter to be optimized in the excitation trajectory model, the matrix The minimum value is obtained, and then the excitation trajectory for parameter identification of the space manipulator is obtained.

[0044] Furthermore, the inertial parameter set of the space manipulator is solved based on the least squares method: ; in: Y _ =[ q m t 1 , q ̇ m t 1 , q ̈ m t 1 ;⋯; q m t 2 n , q ̇ m t 2 n , q ̈ m t 2 n ] and They are the joint motion sequence and torque sequence obtained by the space manipulator following the optimized excitation trajectory. Inertial parameter set of space manipulator.

[0045] Further, in step S220, the inertia matrix estimation term is constructed according to the inertia parameter set of the spatial manipulator , decouple the motion of the flexible base and the space manipulator, and obtain the decoupled dual space manipulator coupling system dynamics model, including: Constructing the inertia matrix estimation term composed of the inertia parameter set of the space manipulator , and substitute the estimated inertia matrix into the dynamic model term corresponding to the space manipulator: ; Will The remaining items are combined into unknown items : ; in: is the input torque of the controller at the last moment. When the sampling frequency is higher than the preset sampling frequency , the unknown Substitute the dynamic model of the flexible base space manipulator and add the control input u to obtain the decoupled dynamic model of the space manipulator: ; The dynamic model of the flexible base space manipulator after decoupling the flexible base from the dual space manipulator is: .

[0046] In one embodiment of the present invention, the pre-sampling frequency is 200-500 Hz, and those skilled in the art can make appropriate adjustments based on the computing power of the actual controller of the robotic arm while still being within the scope of protection of the present invention.

[0047] like Figure 6 and Figure 7As shown, in one embodiment of the present invention, in the step S300, the control law is designed based on the theory of fast and slow subsystems, the control part of the dual-space manipulator is used as the fast system, and the moving part of the flexible base is used as the slow system. The nonlinear model predictive controller is designed considering the coupling effect of the dual-space manipulator system to calculate the optimal control input of the fast system, and an equivalent Kelvin-Voigt model of the flexible base and the environment is established to calculate the equivalent environmental force to suppress vibration and use it as the control input of the slow system, so as to realize the vibration suppression control for the flexible base space manipulator, including: The control law is designed based on the theory of fast and slow subsystems. The module assembly task trajectory tracking control of the space manipulator and the vibration suppression of the base are simultaneously realized through the control input u. It is defined that u consists of two parts: ; in: Acting on the movement of the robot arm, Acting on the base movement; Different from the single-space robot, after the decoupling of the dual-space robot and the flexible base is completed, the closed-chain constraint directly formed by the dual-space robot and the module makes the dual-space robot system still a nonlinear strong coupling system. The conventional PD control law cannot accurately control the dual-space robot to perform assembly tasks at the same time. Therefore, a nonlinear model predictive controller is introduced to calculate the optimal control increment of the fast system at each moment. , define the joint state vector x = [ q m , q ̇ m ] T , output , combined with the decoupled dual-space robotic arm system dynamics model, the continuous state equation of the dual-space robotic arm system is constructed: ; The continuous state equation is processed linearly and discretely to obtain the discrete time linearized state equation of the dual space manipulator system, i.e. the prediction model: ; in: , and are the state and control coefficients, respectively, which can be calculated from the expected trajectory and are constants in the prediction time domain N. k is the current sampling time. is the optimal control increment at the k moment that needs to be predicted; According to the prediction model, the time domain N after the sampling time is predicted, and the state vector of the system in the prediction time domain is expressed as: ; in: represents the predicted state vector of the system, represents the assumed control input vector of the system in the prediction domain, , and Reason , and The prediction iteration coefficient matrix composed of; Constructing the optimization objective function of the dual-space manipulator system , the expression is: ; in: It represents the tracking error vector of the system in the prediction time domain, that is, the tracking error between the expected trajectory of the module center of mass and the actual trajectory of the joint obtained by the kinematic closed chain constraint and the inverse kinematics solution of the manipulator. is the state error weight matrix of the dual-space manipulator system. Based on the least squares principle and the optimization objective function, the optimal control problem is transformed into a quadratic programming problem: ; in: , is the limit value of the joint angle of the space manipulator, , Input limit values ​​for the space manipulator fast system control, , is the limit value of the control input increment of the space manipulator fast system. According to the gradient optimization principle, the optimal control input increment of the fast system is obtained as follows: ; in: is the expected joint state vector of the dual-space manipulator at the sampling time, The lower triangular identity matrix, the optimal control input of the fast system can be obtained by the optimal control input increment: ; Consider the vibration of the flexible base as establishing a Kelvin-Voigt model with the environment, and the force generated by the environment on the flexible base is expressed as: ; in: is the equivalent stiffness of the Kelvin-Voigt model, is the equivalent viscous damping coefficient of the Kelvin-Voigt model. Combined with the decoupled flexible base space manipulator dynamics model, the slow system control input expression for suppressing base vibration is: u slow , k q b = - H bm q b , q md , k H ̂ m - 1 [ k e q b + b e q ̇ b ] ; in: represents the expected joint angle of the space manipulator at time k, Then the overall control law of the flexible base space manipulator is obtained: .

[0048] Please continue reading Figure 6 , , , are the expected displacement, expected velocity and expected acceleration of the module center of mass, respectively. , , are the expected rotation angle, expected angular velocity and expected angular acceleration of each joint of the space manipulator. Specifically, Acting on the movement of the robot arm, Acting on the base motion; ε is a constant coefficient that tends to zero, ensuring that the robot arm converges at a faster speed; represents the expected joint angle acceleration of the space manipulator; e represents the error between the expected joint angle and the actual joint angle; Represents the error between the expected joint angular velocity and the actual joint angular velocity; and Represent the proportional and differential gain coefficients respectively; ; Indicates the desired joint angle of the space manipulator; Represents the damping control coefficient.

[0049] Please continue reading Figure 6 and Figure 7 .exist Figure 6 In the control loop, the inner control loop is responsible for the decoupling of the system dynamics model, and the outer control loop is responsible for controlling the robot to track the desired trajectory. The desired trajectory of the robot is obtained by the desired motion trajectory of the center of mass of the handling module through the kinematic closed-chain constraint. Figure 7 The active damping control law corresponds to The calculation formula for calculating the torque control law is The calculation formula is: Figure 7 It is the overall control block diagram, and each text box corresponds to each step of the formula calculation above.

[0050] Here, the present invention establishes a dynamic model of a flexible base dual space robot arm coupling system based on the Lagrangian method, establishes kinematic closed-chain constraints according to the assembly operation scenario, realizes space robot arm motion decoupling based on parameter identification, and realizes high-precision control of space robot arm module assembly tasks and flexible base vibration suppression based on the theoretical design control law of the fast and slow subsystems. The vibration suppression control method enables the space robot arm to have better assembly operation accuracy in a zero microgravity operation environment, enhances the space robot arm operation robustness, and improves the space robot arm operation efficiency.

[0051] like Figure 8 As shown, the second aspect of the present invention provides a vibration suppression control system for a flexible base space robot arm, which is applied to an assembly task scenario of a dual space robot arm facing a module to be assembled, comprising: The motion constraint unit 400 is at least used to establish a dual-space manipulator coupling system dynamics model based on the closed-chain constraint between the dual-space manipulator and the assembly model, and then consider the manipulator and the flexible base to establish a flexible base space manipulator system dynamics model; The motion decoupling unit 500 is at least used to design a space manipulator parameter identification excitation trajectory based on condition number optimization, and simultaneously excite the two space manipulators to obtain two space manipulator inertia parameter sets respectively, and construct an inertia matrix estimation item according to the space manipulator inertia parameter sets to perform motion decoupling between the flexible base and the dual space manipulators; The vibration suppression control unit 600 is at least used to design the control law based on the theory of fast and slow subsystems, taking the control part of the robot arm as the fast system and the moving part of the flexible base as the slow system, so as to realize the double-arm fine assembly of the flexible base space robot arm and the vibration suppression control of the flexible base.

[0052] Based on the same idea as the method in the above embodiment, the system provided by the present invention can implement the method in the above embodiment. For the convenience of explanation, the structural diagram of the system embodiment only shows the parts related to the embodiment of the present invention. Those skilled in the art can understand that the illustrated structure does not constitute a limitation on the system, and may include more or less components than shown in the figure, or combine certain components, or arrange the components differently.

[0053] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In actual applications, the above-mentioned function allocation can be completed by different functional units and modules as needed, that is, the internal structure of the above-mentioned device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the implementation method can be integrated into a processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of the present invention. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method implementation method, which will not be repeated here.

[0054] It should be noted that the methods and detailed examples provided in the above embodiments can be combined with the devices and equipment provided in the embodiments, and references can be made to each other, and no further details will be given.

[0055] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0056] The above-mentioned embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit them. Although the present invention has been described in detail with reference to the above-mentioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above-mentioned embodiments, or replace some of the technical features therein by equivalents. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention, and should all be included in the protection scope of the present invention.

Claims

1. A vibration suppression control method for a flexible base space robot arm, applied to an assembly task scenario of a dual space robot arm facing a module to be assembled, characterized in that: The following steps are involved: Based on the closed-chain constraints between the dual-space manipulators and the modules to be assembled, a dual-coupling system dynamics model is established. Then, the flexible base space manipulator system dynamics model is established by considering the coupling between the manipulators and the flexible base. A windowed finite-term Fourier series trajectory based on condition number optimization is designed as the excitation trajectory for parameter identification of the space manipulator. The two space manipulators are simultaneously excited to obtain two sets of inertia parameters of the space manipulators respectively. According to the inertia parameter sets of the space manipulators, an inertia matrix estimation term is constructed to decouple the motion of the flexible base and the dual space manipulators. The control law is designed based on the theory of fast and slow subsystems. The control part of the dual-space manipulator is regarded as the fast system, and the moving part of the flexible base is regarded as the slow system. Considering the coupling effect of the dual-space manipulator system, a nonlinear model predictive controller is designed to calculate the optimal control input of the fast system. An equivalent Kelvin-Voigt model of the flexible base and the environment is established to calculate the equivalent environmental force to suppress vibration and use it as the control input of the slow system, thereby realizing the dual-arm fine assembly of the flexible base space manipulator and the vibration suppression control of the flexible base.

2. The vibration suppression control method for a flexible base space manipulator according to claim 1, characterized in that: The method establishes a dual-coupling system dynamics model based on the closed-chain constraints between the dual-space manipulators and the modules to be assembled, and then establishes a flexible base space manipulator system dynamics model by considering the coupling between the manipulators and the flexible base, including: Establish a flexible base space manipulator coupling system coordinate system, wherein the flexible base space manipulator coupling system coordinate system includes a flexible base centroid coordinate system ∑ b , left robot end effector coordinate system∑ l , right robot end effector coordinate system∑ r , assembly module mass center coordinate system∑ o , inertial coordinate system∑ e ; Assuming that the end effector of each space manipulator is fixedly connected to the module during the module assembly task, the kinematic constraint between the coordinate system of the end effector of the space manipulator and the coordinate system of the center of mass of the module is established: ； in: Represents the position vector of each spatial manipulator end coordinate system in the inertial coordinate system; Represents the position vector of the module coordinate system in the inertial coordinate system; Represents the position vector of the module's center of mass to the coordinate system of each spatial manipulator end; Represents the attitude rotation matrix of each space manipulator end coordinate system in the inertial coordinate system; Represents the attitude rotation matrix of the module coordinate system in the inertial coordinate system; Represents the attitude rotation matrix of each space robot end coordinate system relative to the module center of mass coordinate system; represents the skew-symmetric matrix operator for vector cross product; and Respectively represent the rotation angular velocity of each spatial manipulator end effector and the module center of mass coordinate system; Establish the dynamic model of the module to be assembled: ； in: Module inertia matrix, is the nonlinear term related to module speed, represents the resultant force and moment applied by the space manipulator to the center of mass of the module, It represents the net force and net moment applied by the environment to the center of mass of the object; Establish the dynamic model of the dual-space manipulator coupling system: ； in: Represents the coupling inertia matrix of the two space manipulators. , This is the coupling inertia matrix of the left manipulator after adding the dynamic closed-chain constraint. is the inertia matrix of the left robotic arm, is the load distribution coefficient of the left robot arm, is the Jacobian matrix of the left robot arm, , This is the coupling inertia matrix of the right manipulator after adding the dynamic closed-chain constraint. is the inertia matrix of the right robotic arm, is the load distribution coefficient of the right robot arm, is the Jacobian matrix of the right robot arm; represents the coupling nonlinear term of the two space manipulators related to the generalized velocity. , This is the nonlinear term of the left manipulator coupling after adding the dynamic closed-chain constraint. is the nonlinear term of the left manipulator, , This is the nonlinear term of the right manipulator coupling after adding the dynamic closed-chain constraint. is the nonlinear term of the right robotic arm; Represents the joint angular displacement vectors of the two robotic arms; Establish the dynamic model of the flexible base space manipulator: ； Wherein: the flexible base space manipulator is a flexible base with m degrees of freedom and two n-degree-of-freedom space manipulators; represents the generalized displacement vector of the flexible base, represents the inertia matrix of the flexible base, represents the damping matrix of the flexible base, represents the stiffness matrix of the flexible base; Represents the inertial coupling matrix between the two space manipulators and the base; and represents the nonlinear term related to the generalized velocity; Represents the joint torque of the two spatial manipulators.

3. The vibration suppression control method for a flexible base space manipulator according to claim 1, characterized in that: The design identifies the excitation trajectory of the space manipulator parameters based on condition number optimization, and simultaneously excites two space manipulators to obtain two space manipulator inertia parameter sets respectively, and constructs the inertia matrix estimation item according to the space manipulator inertia parameter sets to perform motion decoupling between the flexible base and the dual space manipulators, including: Design a space manipulator parameter identification excitation trajectory based on condition number optimization, simultaneously excite two space manipulators to obtain two space manipulator inertia parameter sets respectively, collect data obtained by the space manipulator moving along the excitation trajectory, and solve the space manipulator inertia parameter set by the least square method. Construct an inertia matrix estimation term based on the inertia parameter set of the space manipulator , the motion of the flexible base and the dual-space manipulator is decoupled, and the dynamic model of the decoupled dual-space manipulator coupling system is obtained.

4. The vibration suppression control method for a flexible base space manipulator according to claim 3, characterized in that: The design is based on the condition number optimization of the space manipulator parameter identification excitation trajectory, respectively collects the data obtained by the two space manipulators moving according to the excitation trajectory, and solves the space manipulator inertial parameter set by the least square method, including: Aiming at the zero-microgravity working environment of the space manipulator and the working characteristics of the manipulator's fine work in assembly tasks, a windowed finite-term Fourier series trajectory is designed as the excitation trajectory for the space manipulator's parameter identification to improve the signal quality and accuracy, which is suitable for the space manipulator's parameter identification under low-frequency dynamic characteristics. The excitation trajectories of each joint of the two spatial manipulators are: ； in: represents the fundamental frequency; K represents the number of Fourier coefficient terms; k represents the kth Fourier coefficient term; and is the amplitude of the sine and cosine functions of the i-th joint, represents the constant term of the position of the i-th joint, and t represents the time; represents the Hamming window, and its expression is: ； The angular velocity expression corresponding to the excitation trajectory of each joint is: ； The angular acceleration expression corresponding to the excitation trajectory of each joint is: ； The condition number is used as the optimization index of the excitation trajectory, and the sampling data obtained by the space manipulator moving along the excitation trajectory are ) to form the total vector matrix , define the matrix condition number as: ； Add constraints for the motion of the space manipulator: ； in: , and Indicates the maximum absolute value of the joint angle, joint angular velocity, and joint angular acceleration of the space manipulator. and Indicates the start and end time of a single excitation cycle; By solving the minimum problem of nonlinear multivariate function, , and As the parameter to be optimized in the excitation trajectory model, the matrix Minimum value, and then get the excitation trajectory of the space manipulator parameter identification; Solve the inertial parameter set of the space manipulator based on the least squares method: ； in: and They are the joint motion sequence and torque sequence obtained by the space manipulator following the optimized excitation trajectory. is the inertial parameter set of the space manipulator.

5. The vibration suppression control method for a flexible base space manipulator according to claim 4, characterized in that: The inertia matrix estimation term is constructed according to the inertia parameter set of the space manipulator , decouple the motion of the flexible base and the space manipulator, and obtain the decoupled dual space manipulator coupling system dynamics model, including: Constructing the inertia matrix estimation term composed of the inertia parameter set of the space manipulator , and substitute the estimated inertia matrix into the dynamic model of the flexible base space manipulator: ； Will The remaining items are combined into unknown items : ； in: is the input torque of the controller at the last moment. When the sampling frequency is higher than the preset sampling frequency , the unknown Substitute the dynamic model of the flexible base space manipulator and add the control input u to obtain the decoupled dynamic model of the space manipulator: ； The dynamic model of the flexible base space manipulator after decoupling the flexible base from the dual space manipulator is: 。 6. The vibration suppression control method for a flexible base space manipulator according to claim 1 or 5, characterized in that: The control law is designed based on the theory of fast and slow subsystems. The control part of the dual-space manipulator is taken as the fast system, and the moving part of the flexible base is taken as the slow system. The nonlinear model predictive controller is designed considering the coupling effect of the dual-space manipulator system to calculate the optimal control input of the fast system. The equivalent Kelvin-Voigt model of the flexible base and the environment is established to calculate the equivalent environmental force to suppress vibration and use it as the control input of the slow system to achieve vibration suppression control for the flexible base space manipulator, including: The control law is designed based on the theory of fast and slow subsystems. The module assembly task trajectory tracking control of the space manipulator and the vibration suppression of the base are simultaneously realized through the control input u. It is defined that u consists of two parts: ； in: Acting on the movement of the robot arm, Acting on the base movement; Different from the single-space robot, after the decoupling of the dual-space robot and the flexible base is completed, the closed-chain constraint directly formed by the dual-space robot and the module makes the dual-space robot system still a nonlinear strong coupling system. The conventional PD control law cannot accurately control the dual-space robot to perform assembly tasks at the same time. Therefore, a nonlinear model predictive controller is introduced to calculate the optimal control increment of the fast system at each moment. , define the joint state vector , output , combined with the decoupled dual-space robotic arm system dynamics model, the continuous state equation of the dual-space robotic arm system is constructed: ； The continuous state equation is processed linearly and discretely to obtain the discrete time linearized state equation of the dual space manipulator system, i.e. the prediction model: ； in: , and are the state and control coefficients, respectively, which can be calculated from the expected trajectory and are constants in the prediction time domain N. is the current sampling time, For those who need to predict Optimal control increment at every moment; According to the prediction model, the time domain N after the sampling time is predicted, and the state vector of the system in the prediction time domain is expressed as: ； in: represents the predicted state vector of the system, represents the assumed control input vector of the system in the prediction domain, , and Reason , and The prediction iteration coefficient matrix composed of Constructing the optimization objective function of the dual-space manipulator system , the expression is: ； in: It represents the tracking error vector of the system in the prediction time domain, that is, the tracking error between the expected trajectory of the module center of mass and the actual trajectory of the joint obtained by the kinematic closed chain constraint and the inverse kinematics solution of the manipulator. is the state error weight matrix of the dual-space manipulator system. Based on the least squares principle and the optimization objective function, the optimal control problem is transformed into a quadratic programming problem: ； in: , is the limit value of the joint angle of the space manipulator, , Input limit values ​​for the space manipulator fast system control, , is the limit value of the control input increment of the space manipulator fast system. According to the gradient optimization principle, the optimal control input increment of the fast system is obtained as follows: ； in: is the expected joint state vector of the dual-space manipulator at the sampling time, The lower triangular identity matrix, the optimal control input of the fast system can be obtained by the optimal control input increment: ； The vibration of the flexible base is regarded as establishing a Kelvin-Voigt model with the environment. The force generated by the environment on the flexible base is expressed as: ； in: is the equivalent stiffness of the Kelvin-Voigt model, is the equivalent viscous damping coefficient of the Kelvin-Voigt model. Combined with the decoupled flexible base space manipulator dynamics model, the slow system control input expression for suppressing base vibration is: ； in: represents the expected joint angle of the space manipulator at time k, Then the overall control law of the flexible base space manipulator is obtained: 。 7. A vibration suppression control system for a flexible base space robot arm, applied to an assembly task scenario of a dual space robot arm facing a module to be assembled, characterized in that: include: The motion constraint unit is at least used to establish a dual-space manipulator coupling system dynamics model based on the closed-chain constraint between the dual-space manipulator and the assembly model, and then consider the manipulator and the flexible base to establish a flexible base space manipulator system dynamics model; A motion decoupling unit is at least used to design a space manipulator parameter identification excitation trajectory based on condition number optimization, and simultaneously excite two space manipulators to obtain two space manipulator inertia parameter sets respectively, and construct an inertia matrix estimation item according to the space manipulator inertia parameter sets to perform motion decoupling between the flexible base and the dual space manipulators; The vibration suppression control unit is at least used to design the control law based on the theory of fast and slow subsystems, taking the control part of the manipulator as the fast system and the moving part of the flexible base as the slow system, so as to realize the vibration suppression control of the flexible base space manipulator.

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