Space non-cooperative target switching enhanced force position control method and system and electronic equipment

Abstract

The present application relates to the technical field of space non-cooperative target manipulation, and particularly relates to a space non-cooperative target switching enhanced force-position control method, a system and an electronic device, the space non-cooperative target switching enhanced force-position control method comprising: constructing and designing a space non-cooperative target switching enhanced force-position hybrid controller based on a flexible base space mechanical arm dynamics model; performing visual identification on the space non-cooperative target before contact and obtaining a corresponding contact model; performing parameter identification based on the obtained contact model to obtain parameters identified for each target; feeding back the identified parameters to the switching enhanced force-position hybrid controller to drive the switching enhanced force-position hybrid controller to execute a corresponding vibration suppression strategy for each target to achieve adaptive force-position hybrid control of the space non-cooperative target. The present application can smoothly transition, suppress oscillation and ensure safe and reliable space non-cooperative target capture operation.

Description

Technical Field

[0001] This invention relates to the field of space non-cooperative target manipulation technology, specifically to a space non-cooperative target switching enhanced force-position control method, system, and electronic device. Background Technology

[0002] With the development of space technology, the number of spacecraft launches worldwide has continued to grow rapidly, leading to a continuous increase in the number of in-orbit defunct satellites, malfunctioning satellites, and space debris. These uncontrolled space objects occupy valuable Earth orbital resources and pose a significant collision threat to currently operational spacecraft. A collision could trigger a chain reaction, further exacerbating the Kessler effect, leading to a deterioration of the orbital environment, and even threatening the safe operation of critical infrastructure such as space stations, communication satellites, and navigation satellites.

[0003] Therefore, research on active on-orbit servicing and removal technologies for non-cooperative targets in space has become a key focus of urgent attention in the international aerospace community. Among these, compliant capture technology is one of the crucial links in achieving safe and reliable on-orbit operations. Compliant capture requires that the robotic arm or end effector of the servicing satellite can effectively adapt to the unknown mechanical properties of the target upon contact, avoiding excessive impact force, vibration, or structural damage, thereby ensuring the safety of the capture process and the controllability of subsequent operations.

[0004] Force / position hybrid control, as a classic compliant control method, has been widely applied in the operation of ground industrial robots and space robotic arms. This method achieves a good balance between positional accuracy and contact force compliance by applying positional control or force control separately on different degrees of freedom. However, traditional force / position hybrid control has significant limitations: it requires pre-specifying which degrees of freedom will be controlled by position and which by force, relying on precise prior knowledge of the target environment constraints. In actual space missions, the constraints of non-cooperative target environments are highly unknown and unpredictable, making traditional force / position hybrid control difficult to apply directly and prone to contact failure or target damage.

[0005] Furthermore, during actual control mode switching, especially the transient transition from position control to force control, system stability is often difficult to guarantee. Due to abrupt changes in the control law, dynamic model mismatch, and the influence of unknown target stiffness at the moment of switching, significant force / position overshoot, residual vibration, and even, in extreme cases, the end effector may detach from the target. These transient instabilities not only reduce the success rate of acquisition but may also cause irreversible damage to vulnerable components of the target.

[0006] Therefore, in practical engineering applications, it is urgent to design vibration suppression strategies for the switching process to ensure a smooth transition, suppress oscillations, and ensure the safety and reliability of the entire capture operation. Summary of the Invention

[0007] In view of the shortcomings of the prior art described above, the purpose of this invention is to provide an enhanced force potential control method, system and electronic device for switching non-cooperative targets in space, which can smoothly transition, suppress oscillations and ensure the safety and reliability of capture operations for non-cooperative targets in space.

[0008] The first aspect of this invention provides a space non-cooperative target switching enhanced force potential control method, comprising:

[0009] A dynamic model of a flexible-base space manipulator was constructed, and a hybrid force-potential switching controller for non-cooperative targets in space was designed.

[0010] Before contact, non-cooperative targets in space are visually identified, and each target is classified into rigid and flexible categories based on prior knowledge to obtain the corresponding contact model. The results of the rigid-flexibility classification include at least: rigid targets, weakly rigid targets, and flexible targets.

[0011] Based on the obtained contact model, parameter identification is performed to obtain the identified parameters corresponding to each target;

[0012] The identified parameters are fed back to the switching enhanced force-potential hybrid controller, which drives the switching enhanced force-potential hybrid controller to execute the corresponding vibration suppression strategy for each target, so as to achieve adaptive force-potential hybrid control for non-cooperative targets in space.

[0013] As an optional implementation, the construction of a flexible-base space manipulator dynamics model and the design of a switching enhanced force-potential hybrid controller for non-cooperative space targets includes:

[0014] Establish a kinematic chain model for a flexible-base space robotic arm;

[0015] Based on the kinematic chain model of the flexible base space manipulator and the Lagrange method, a dynamic model of the flexible base space manipulator is constructed:

[0016] Based on the aforementioned dynamic model of the flexible base space manipulator, a switching-enhanced force-potential hybrid controller is designed for non-cooperative space targets with unknown environmental constraints; wherein:

[0017] For non-cooperative targets in space with unknown environmental constraints, a selection matrix is ​​designed to determine whether force control or position control is applied to each degree of freedom, based on the idea of ​​switching enhanced force-potential hybrid control.

[0018] By comparing the measured contact force or torque with the corresponding preset threshold, the contact state between each degree of freedom and the target is determined, thereby selecting position control or force control; wherein: only one control method is performed on a single degree of freedom; if it is a free motion state, position control is performed, and if it is a constrained motion state, force control is performed.

[0019] As an optional implementation, the driving torque of the switching enhanced force-position hybrid controller... Torque generated by position control , Torque generated by force control , Composition, the expression is: ;in:

[0020] The position control section employs decomposed acceleration control, consisting of two torque components: one is the torque generated by the joint position PD controller. The other is the joint acceleration feedforward torque. The expressions are as follows:

[0021] ;

[0022] ;

[0023] in, S To select a matrix, and These are the proportional gain and derivative gain of the position controller, respectively. For the desired end position, For the desired terminal velocity, For the desired terminal acceleration, This is the forward kinematics transformation matrix for the robotic arm. Let Jacobian matrix be the value of the robotic arm. Let be the time derivative of the Jacobian matrix of the robotic arm. For the joint angle of the robotic arm, The angular velocity of the robotic arm joints;

[0024] The force control section employs feedforward explicit force control, consisting of a proportional controller based on the force error signal and a speed-related damping gain generating the control torque. The other is the feedforward torque calculated from the selected desired force. The expressions are as follows:

[0025] ;

[0026] ;

[0027] in, STo select a matrix, For the proportional gain of the force controller, For adjustable damping gain, For the power of expectation, The interaction force between the robotic arm and the environment, It is the identity matrix. Let Jacobian matrix be the value of the robotic arm. Let be the force Jacobian matrix of the robotic arm. Let be the joint angular velocity of the robotic arm.

[0028] As an optional implementation, the visual identification of non-cooperative targets in space before contact includes:

[0029] Before contact with non-cooperative targets in space, precise identification of target satellite parts can be achieved by using monocular / multi-view cameras, lidar, and lightweight vision algorithms suitable for aerospace chips onboard servicing satellites.

[0030] As an optional implementation, the step of combining prior knowledge to classify each target into rigid and flexible targets and obtain corresponding contact models includes: based on a pre-stored prior knowledge base, mapping and classifying the identified parts according to their stiffness levels, wherein, for a failed satellite, the main structure of the satellite is classified as a rigid target, the thruster nozzle and satellite antenna are classified as weakly rigid targets, and easily deformable parts are classified as flexible targets.

[0031] Using the visual grading results as input, the identified target parts are mapped to the corresponding contact model library to obtain the corresponding contact model.

[0032] As an optional implementation, feeding back the identified parameters to the switching enhanced force-potential hybrid controller, driving the switching enhanced force-potential hybrid controller to execute corresponding vibration suppression strategies for each target, thereby achieving adaptive force-potential hybrid control for non-cooperative targets in space, includes:

[0033] In the force-position hybrid control, the damping gain of the force control part is set to the sum of the real-time damping gain and the fixed damping gain.

[0034] For rigid targets, the real-time damping gain is adjusted using force signals; for weakly rigid or flexible targets, the real-time damping gain is adjusted using position signals.

[0035] As an optional implementation, the step of parameter identification based on the acquired contact model to obtain the identified parameters corresponding to each target includes:

[0036] The corresponding contact models are identified using the exponentially weighted recursive least squares method to obtain the identification parameters for the rigid target and the weakly rigid target, respectively, wherein:

[0037] For rigid targets, stiffness coefficients are obtained based on the K-model and used as the parameters to be identified for the rigid targets;

[0038] For weakly rigid targets, the equivalent stiffness and equivalent damping are obtained based on the Kelvin-Voigt model as the parameters to be identified for the weakly rigid targets.

[0039] As an optional implementation, the step of parameter identification based on the acquired contact model to obtain the identified parameters corresponding to each target includes:

[0040] The nonlinear contact model of the flexible target is linearized based on the assumption of low-speed end motion to obtain the identification parameters of the flexible target, wherein:

[0041] Obtain and linearize the Hunt-Crossley model formula;

[0042] The equivalent stiffness, equivalent damping, and Hertzian nonlinear exponent are obtained from the linearized Hunt-Crossley model as the parameters to be identified for the flexible target.

[0043] A second aspect of the present invention provides a space non-cooperative target switching enhanced force potential control method, comprising:

[0044] A design unit is constructed to build and design a switching enhanced force-position hybrid controller for non-cooperative targets in space based on the dynamic model of the flexible base space manipulator.

[0045] The visual grading unit is used to visually identify non-cooperative targets in space before contact, and to classify each target into rigidity and flexibility based on prior knowledge and obtain the corresponding contact model. The results of rigidity and flexibility grading include at least: rigid targets, weakly rigid targets, and flexible targets.

[0046] The parameter identification unit is used to identify parameters based on the acquired contact model and obtain the identified parameters corresponding to each target.

[0047] The vibration suppression control unit is used to feed back the identified parameters to the switching enhanced force-position hybrid controller, and drive the switching enhanced force-position hybrid controller to execute the corresponding vibration suppression strategy for each target, so as to realize adaptive force-position hybrid control for non-cooperative targets in space.

[0048] A third aspect of the present invention provides an electronic device suitable for on-orbit servicing satellites, comprising: at least one processor; and at least one memory communicatively connected to the processor, wherein: the memory stores program instructions executable by the processor, and the processor invokes the program instructions to perform the steps of the space non-cooperative target switching enhanced force potential control method as described in the first aspect of the present invention.

[0049] In summary, compared with existing technologies, this invention, after establishing and simplifying the dynamic model of the flexible base space manipulator, designs a switching enhanced force-position hybrid control method for non-cooperative space targets with unknown environmental constraints. Based on visual recognition results and a pre-stored prior knowledge base, it achieves stiffness classification of various parts of the non-cooperative space target, designs adaptive vibration suppression strategies for each type of target, and realizes refined compliant capture of non-cooperative space targets, providing reliable technical support for large-scale on-orbit servicing and space debris removal missions. Attached Figure Description

[0050] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0051] Figure 1 This is a flowchart of a space non-cooperative target switching enhanced force position control method according to an embodiment of the present invention.

[0052] Figure 2 This is a schematic flowchart of a space non-cooperative target switching enhanced force position control method according to an embodiment of the present invention.

[0053] Figure 3 This is a schematic diagram of a kinematic chain model of a flexible base space robotic arm according to an embodiment of the present invention.

[0054] Figure 4 This is a flowchart illustrating another method for enhancing the force potential control of non-cooperative target switching in space, according to an embodiment of the present invention.

[0055] Figure 5 This is a flowchart illustrating another method for enhancing the force potential control of non-cooperative target switching in space according to an embodiment of the present invention.

[0056] Figure 6 This is a control logic diagram of a single degree of freedom for the visually graded switching enhanced force-position hybrid control according to an embodiment of the present invention.

[0057] Figure 7 This is a comparison of the switching vibration suppression control effects for rigid targets according to a specific embodiment of the present invention. Figure I .

[0058] Figure 8 This is a comparison of the switching vibration suppression control effects for rigid targets according to a specific embodiment of the present invention. Figure II .

[0059] Figure 9This is a comparison of the switching vibration suppression control effects for rigid targets according to a specific embodiment of the present invention. Figure III .

[0060] Figure 10 This is a curve diagram showing the equivalent stiffness identification of a rigid target according to an embodiment of the present invention.

[0061] Figure 11 This is a graph showing the change in damping gain parameters of the rigid target switching vibration suppression control algorithm according to an embodiment of the present invention.

[0062] Figure 12 This is a comparison of the switching vibration suppression control effects for weakly rigid targets according to a specific embodiment of the present invention. Figure I .

[0063] Figure 13 This is a comparison of the switching vibration suppression control effects for weakly rigid targets according to a specific embodiment of the present invention. Figure II .

[0064] Figure 14 This is a comparison of the switching vibration suppression control effects for weakly rigid targets according to a specific embodiment of the present invention. Figure III .

[0065] Figure 15 This is an equivalent stiffness identification curve of a weakly rigid target according to an embodiment of the present invention.

[0066] Figure 16 This is a graph showing the change in damping gain parameters of the switching vibration suppression control algorithm for weakly rigid targets according to an embodiment of the present invention.

[0067] Figure 17 This is a comparison of the switching vibration suppression control effects for flexible targets according to a specific embodiment of the present invention. Figure I .

[0068] Figure 18 This is a comparison of the switching vibration suppression control effects for flexible targets according to a specific embodiment of the present invention. Figure II .

[0069] Figure 19 This is a comparison of the switching vibration suppression control effects for flexible targets according to a specific embodiment of the present invention. Figure III .

[0070] Figure 20 This is a curve diagram showing the equivalent stiffness identification of a flexible target according to an embodiment of the present invention.

[0071] Figure 21 This is the flexible target Hertz nonlinear exponent identification curve according to an embodiment of the present invention.

[0072] Figure 22 This is a graph showing the change in damping gain parameters of the flexible target switching vibration suppression control algorithm according to an embodiment of the present invention.

[0073] Figure 23 This is a block diagram of a space non-cooperative target switching enhanced force-position control system according to an embodiment of the present invention.

[0074] Figure 24 This is a schematic diagram of the structure of an electronic device according to an embodiment of the present invention. Detailed Implementation

[0075] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application. Furthermore, it should be understood that the specific embodiments described herein are only for illustration and explanation of this application and are not intended to limit this application.

[0076] It should be noted that the order of description of the following embodiments is not intended to limit the preferred order of the embodiments of this application. Furthermore, the descriptions of each embodiment in the following embodiments have their own emphasis; for parts not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0077] like Figure 1 and Figure 2 As shown, the first aspect of the present invention provides a space non-cooperative target switching enhanced force potential control method, which mainly includes the following contents.

[0078] Step S100: Construct and design a hybrid force-position switching controller for non-cooperative targets in space based on the dynamic model of the flexible base space manipulator.

[0079] Step S200: Visually identify non-cooperative targets in space before contact, and classify each target into rigid and flexible categories based on prior knowledge and obtain the corresponding contact model. The results of the rigid and flexible classification include at least: rigid targets, weakly rigid targets, and flexible targets.

[0080] Specifically, "before contact" refers to the stage before the robotic arm's end effector makes physical contact with the non-cooperative target in space; the contact model specifically refers to the relationship between force, position, stiffness, and / or damping when the robotic arm's end effector makes physical contact with the non-cooperative target in space.

[0081] Step S300: Based on the acquired contact model, perform parameter identification to obtain the identified parameters corresponding to each target.

[0082] Specifically, the corresponding contact models are identified based on the exponentially weighted recursive least squares method to obtain the identification parameters of the rigid target and the weakly rigid target respectively; and the nonlinear contact model of the flexible target is linearized based on the end-effector low-speed motion assumption to obtain the identification parameters of the flexible target.

[0083] Here, the present invention automatically switches between position control and force control in each degree of freedom based on the real-time contact state, so as to achieve compliant adaptation to unknown non-cooperative targets.

[0084] Step S400: Feed back the identified parameters to the switching enhanced force-potential hybrid controller, and drive the switching enhanced force-potential hybrid controller to execute the corresponding vibration suppression strategy for each target, so as to realize adaptive force-potential hybrid control for non-cooperative targets in space.

[0085] Specifically, the vibration suppression strategy is an adaptive control strategy proposed to address the stability issues in the adaptive switching process of the enhanced force-position hybrid control under unknown spatial environment constraints, particularly the unavoidable overshoot, vibration, and potential escape risks when switching from position control mode to force control mode.

[0086] Here, the present invention achieves refined compliant capture of non-cooperative targets in space by performing on-orbit visual recognition and stiffness classification, and corresponding contact modeling, formulating type-specific vibration suppression strategies and parameter identification.

[0087] Please continue reading. Figure 3 and Figure 4 In one embodiment of the present invention, constructing a dynamic model of a flexible base space manipulator includes:

[0088] A dynamic model of a flexible-base space manipulator is established and simplified based on the Lagrange method and constraint assumptions, wherein:

[0089] Step S110: Establish a kinematic chain model for the flexible base space robotic arm;

[0090] Step S120: Establish the dynamic model of the flexible base space manipulator based on the kinematic chain model and the Lagrange method:

[0091] ;

[0092] in, , These are the generalized inertia matrices of the base and the robotic arm, respectively; This is the coupling inertia matrix between the robotic arm and the base; , These are the nonlinear forces related to the base motion and the robotic arm motion, including centripetal force and Coriolis force; The forces acting on the base in six dimensions include the forces acting on the base in the translational degree of freedom and the torques acting on the base in the rotational degree of freedom. This refers to the driving torque of the robotic arm joints; The six-dimensional interaction forces between the robotic arm and the environment include the interaction forces in the translational degree of freedom and the interaction torques in the rotational degree of freedom; For the base acceleration; This refers to the joint angular acceleration of the robotic arm; and These are the force-Jacobi matrices for the robotic arm and the base, respectively.

[0093] Step S130: Simplify the dynamic model of the flexible base space manipulator based on constraint assumptions.

[0094] Specifically, the dynamic model of the flexible base space manipulator established and simplified based on the Lagrange method and constraint assumptions includes: assuming that the external force and torque applied to the base are both zero (i.e., the six-dimensional spatial force acting on the base). If the base pose is completely uncontrolled (zero), and the overall linear momentum and angular momentum of the system remain constant, then the above dynamic model can be simplified to:

[0095] ;

[0096] In the formula:

[0097] ;

[0098] ;

[0099] ;

[0100] ;

[0101] in, Let be the equivalent generalized inertia matrix of the robotic arm; , These are the generalized inertia matrices of the base and the robotic arm, respectively; This is the coupling inertia matrix between the robotic arm and the base; , These are the nonlinear forces related to the base motion and the robotic arm motion, including centripetal force and Coriolis force; The equivalent nonlinear force related to the movement of the robotic arm; To switch the equivalent driving torque of the enhanced force-position hybrid controller; Let be the equivalent Jacobian matrix of the robotic arm.

[0102] Specifically, the kinematic chain model of the flexible base space manipulator is used to describe the multibody dynamics and kinematic modeling of the space manipulator system in a free-floating state.

[0103] like Figure 3 As shown, the kinematic chain model of the flexible base space robot arm treats the entire system as an open-chain multibody structure. The base has flexible characteristics, and the robot arm is composed of multiple links connected in series through rotating joints. , Representing the inertial coordinate system and the terminal coordinate system respectively; vector , These represent the displacement vectors from the origin of the inertial coordinate system to each centroid and each link, respectively. Representing each joint; Representative links of the base and robotic arm; The center of mass of each link in the base and robotic arm; , These represent the parameters of each link. In this invention, the kinematic chain model of the flexible base space manipulator is the foundation of multibody dynamics and kinematic modeling, and the kinematic chain model is established differently for each scenario or working environment.

[0104] Specifically, , These are the generalized inertia matrices of the base and the robotic arm, respectively; This is the coupling inertia matrix between the robotic arm and the base; , These are the nonlinear forces related to the base motion and the robotic arm motion, including centripetal force and Coriolis force; The forces acting on the base in six dimensions include the forces acting on the base in the translational degree of freedom and the torques acting on the base in the rotational degree of freedom. This refers to the driving torque of the robotic arm joints; The six-dimensional interaction forces between the robotic arm and the environment include interactive forces in the translational degree of freedom and interactive torques in the rotational degree of freedom.

[0105] In one embodiment of the present invention, a switching-enhanced force-potential hybrid controller for non-cooperative spatial targets with unknown environmental constraints is designed based on a dynamic model:

[0106] Force / position hybrid control consists of two relatively independent control loops: a position control loop and a force control loop, using a selection matrix. S Determine whether to apply force control or position control to each degree of freedom. S It is a 6×6 diagonal matrix, with diagonal elements being either 1 or 0.

[0107] For non-cooperative targets in space with unknown environmental constraints, an improved force / position hybrid control method is designed, incorporating a force / position switching control approach. This method uses a switchable selection matrix S. By comparing measured contact forces / torques with set thresholds, the contact status between each degree of freedom and the target is determined, thus selecting between position control and force control. The selection matrix... S The expression is:

[0108] ;

[0109] ;

[0110] in: ( i =1,2,...,6) are selection coefficients. The force / torque exerted on the robotic arm by the measured external environment. To set the force / torque threshold.

[0111] Specifically, only one control method is used for each degree of freedom; if it is a free motion state, position control is used, and if it is a constrained motion state, force control is used; the control methods for different degrees of freedom can be the same or different.

[0112] In one embodiment of the present invention, the design of a switching-enhanced force-potential hybrid controller for non-cooperative space targets with unknown environmental constraints based on a dynamic model includes:

[0113] Switching the drive torque of the enhanced force-position hybrid controller Torque generated by position control , Torque generated by force control , Composition, the expression is:

[0114] .

[0115] Specifically, the position control section employs decomposed acceleration control, consisting of two torque components: one is the joint torque generated by the proportional-derivative controller (PD). The other is the joint acceleration feedforward torque. The expressions are as follows:

[0116] ;

[0117] ;

[0118] in, S To select a matrix, and These are the proportional gain and derivative gain of the position controller, respectively. For the desired end position, For the desired terminal velocity, For the desired terminal acceleration, This is the forward kinematics transformation matrix for the robotic arm. For the joint angle of the robotic arm, Let Jacobian matrix be the value of the robotic arm. For the angular velocity of the robotic arm joints, Let be the time derivative of the Jacobian matrix of the robotic arm.

[0119] Specifically, the force control section employs feedforward display force control, which consists of a force error signal proportional controller and a speed-related damping gain generating the control torque. The other is the feedforward torque calculated from the selected desired force. The expressions are as follows:

[0120] ;

[0121] ;

[0122] in, S To select a matrix, For the proportional gain of the force controller, Let be the force Jacobian matrix of the robotic arm. For adjustable damping gain, For the angular velocity of the robotic arm joints, Let Jacobian matrix be the value of the robotic arm. For the power of expectation, The interaction force between the robotic arm and the environment, It is an identity matrix.

[0123] Specifically, for non-cooperative targets in space with unknown environmental constraints, a selection matrix is ​​designed to determine whether to apply force control or position control for each degree of freedom by combining the switching enhanced force-position hybrid control approach. Specifically, by comparing the relationship between the measured contact force or torque and the corresponding preset threshold, the contact situation between each degree of freedom and the target is determined, thereby selecting whether to perform position control or force control.

[0124] The method provided by this invention no longer pre-fixes the control modes for each degree of freedom, but dynamically switches between position control and force control based on the real-time contact state. When the system has not yet established stable contact, position control is used first to ensure proximity accuracy; once effective contact is detected, it gradually or instantaneously switches to force control to achieve compliant interaction. This adaptive switching mechanism significantly improves the adaptability to unknown non-cooperative targets, enabling force / position switching control to be effectively applied in uncertain environments.

[0125] In one embodiment of the present invention, the step of visually recognizing non-cooperative targets in space before contact includes:

[0126] Before contact with non-cooperative targets in space, fine-grained identification of target satellite parts can be achieved by using monocular cameras, multi-view cameras, and / or lidar onboard service satellites and lightweight vision algorithms suitable for aerospace chips (such as an improved target detection algorithm based on the lightweight baseline model YOLO11n).

[0127] Specifically, during the visual recognition process, the images of the target satellite are processed in real time to identify key components, including but not limited to solar panels, thruster nozzles, the main structure of the satellite, and satellite antennas. Furthermore, image features are extracted and classified into multiple categories using convolutional neural networks to ensure accurate identification of the geometry and surface characteristics of each part under complex spatial lighting and attitude change conditions.

[0128] like Figure 5 As shown, in one embodiment of the present invention, a visual system based on an on-orbit service satellite and a visual algorithm suitable for aerospace chips is used to visually identify non-cooperative targets in space before contact. The system combines prior knowledge to classify each target into rigid and flexible categories and obtain the corresponding contact model. The method includes: Step S210: Visual identification of non-cooperative targets in space before contact is achieved based on an on-orbit service satellite and a visual algorithm suitable for aerospace chips.

[0129] Step S220: Based on the pre-stored prior knowledge base, the identified parts are mapped and graded according to stiffness level. Using the visual grading results as input, the identified target parts are mapped to the corresponding contact model library to obtain the corresponding contact model.

[0130] Specifically, based on a pre-existing knowledge base including historical satellite design data and databases of material mechanical properties, the identified components are mapped and classified according to their stiffness level. For example, for a failed satellite, high-stiffness components such as the main satellite structure are classified as rigid targets, medium-stiffness components such as thruster nozzles and satellite antennas are classified as weakly rigid targets, and easily deformable components such as solar panels are classified as flexible targets.

[0131] This classification process is completed automatically through the association mapping between categories and prior knowledge, providing accurate target type input for subsequent switching enhanced force-potential hybrid control strategies, ensuring accurate matching of control switching vibration suppression strategies, thereby improving the safety and accuracy of on-orbit operations.

[0132] In one embodiment of the present invention, a vision system based on an on-orbit servicing satellite and a vision algorithm suitable for aerospace chips are used to visually identify non-cooperative targets in space before contact. This involves classifying each target into rigidity / flexibility levels based on prior knowledge and obtaining corresponding contact models, including:

[0133] After completing the visual classification of non-cooperative targets in space, an adaptive contact model is used to perform interactive modeling for target parts with different stiffness types in order to optimize the subsequent switching enhanced force-position hybrid control strategy.

[0134] Specifically, by using visual grading results as input, the identified target parts are mapped to the corresponding contact model library to ensure that the modeling process is highly matched with the mechanical properties of the target, thereby reducing uncertainty and potential damage risks during the contact process.

[0135] For parts classified as rigid targets, the K-model is used for modeling. This model assumes that the contact interface is ideally rigid and that the contact force is mainly generated by elastic deformation. The expression is:

[0136] ;

[0137] Where K is the stiffness matrix. , , These represent the positions of the endpoints in each degree of freedom. , , These represent the initial environmental positions for each degree of freedom. , , These are the force components of the external force acting on the robotic arm in the translational degree of freedom.

[0138] For parts classified as weakly rigid targets, the Kelvin-Voigt model is used for modeling. This model treats contact as viscoelastic behavior and combines a parallel combination of springs and dampers to effectively capture the energy dissipation and time-dependent response of weakly rigid materials. The expression is as follows:

[0139] ;

[0140] in, K Here is the stiffness matrix. B Here is the damping matrix. , , These represent the positions of the robotic arm's end effector in each degree of freedom. , , These represent the initial environmental positions of the robotic arm's end effector in each degree of freedom. , , These represent the velocities of the robotic arm's end effector in each degree of freedom.

[0141] For parts classified as flexible targets, the Hunt-Crossley nonlinear contact model is used for modeling. This model extends Hertz contact theory by introducing nonlinear damping to simulate the dynamic response of flexible materials. It considers the nonlinear deformation and velocity-dependent dissipation of the material, providing a more realistic force-deformation relationship in flexible contact and avoiding overestimation or underestimation in linear models. The expression is as follows:

[0142] ;

[0143] in, K Here is the stiffness matrix. B Here is the damping matrix. , , These are the Hertzian nonlinear exponents for each degree of freedom. , , These represent the positions of the endpoints in each degree of freedom. , , These represent the initial environmental positions for each degree of freedom. , , These represent the velocities of the end effector in each degree of freedom.

[0144] Furthermore, the above describes the modeling of the contact force in the translational degree of freedom. The process of modeling the contact torque in the rotational degree of freedom is based on the normal forces in each of the aforementioned degrees of freedom, and the radius vector of the contact point relative to the geometric center of the robotic arm's end effector. The cross product is calculated and expressed as:

[0145] ;

[0146] The contact force and contact torque during the contact process between the robotic arm's end effector and the environment can be calculated using the above model formulas. For external torques acting on the rotational degree of freedom, It is positive pressure.

[0147] In one embodiment of the present invention, a corresponding vibration suppression strategy is designed for each target, including:

[0148] In the force-position hybrid control, the damping gain of the force control part is set to the sum of the real-time damping gain and the fixed damping gain.

[0149] For rigid targets, the real-time damping gain is adjusted using force signals; for weakly rigid or flexible targets, the real-time damping gain is adjusted using position signals.

[0150] Specifically, the damping gain of the force control portion of the force-position hybrid control. The design is in the following form:

[0151] ;

[0152] in: This is the real-time damping gain that can be calculated based on the feedback signal and the identified impedance parameters. The damping gain is fixed. It should be noted that in this invention, the parameters represented by lowercase letters can be understood as scalars, matrices, or vectors depending on the actual scenario, such as the damping gain in a switching enhanced force-position hybrid controller. It is a matrix.

[0153] In designing corresponding vibration suppression strategies for different types of targets, the switching transition buffer is achieved by adjusting the damping gain of the force control part. Specifically, a targeted vibration suppression control algorithm is selected according to the target type, and closed-loop feedback is used to ensure smooth and stable switching.

[0154] Rigid targets have high stiffness, experience rapid changes in environmental forces, and exhibit minimal environmental deformation. They require high accuracy in position measurement but low accuracy in force measurement, making force signal-based damping suitable for adjustment. Weakly rigid and flexible targets have lower stiffness, require high accuracy in force measurement but low accuracy in position measurement, making position signal-based damping adjustment preferable. Control mode switching occurs at a single degree of freedom; therefore, the vibration suppression strategy is designed at the single-degree-of-freedom level. All physical quantities in the corresponding expressions are scalars, with symbols and meanings consistent with those in the aforementioned multi-degree-of-freedom systems. The designed vibration suppression strategies for rigid, weakly rigid, and flexible targets are as follows:

[0155] ;

[0156] ;

[0157] ;

[0158] in: This is the damping saturation value, and its function is to prevent the damping value from being too large and affecting the control. This refers to the actual position of the robotic arm's end effector. The desired end position; It has a clear physical meaning, for rigid and weakly rigid targets, This represents the initial damping value; for flexible targets, This represents the damping value during the steady-state phase. The parameters have different effects on different types of targets; for rigid and weakly rigid targets, The magnitude of the damping value affects the rate of change of the feedback signal; for flexible models, The standard deviation is used to control the position where high damping is applied. Due to the use of position signal adjustment, the desired end position is required in both weakly rigid and flexible target adjustment methods. This parameter cannot be obtained directly; it requires the formulas of the Kelvin-Voigt model and the Hunt-Crossley model, as well as the set expected force and the identified impedance parameter, to calculate. The expressions are as follows:

[0159] ;

[0160] ;

[0161] in: The expected force set; Equivalent stiffness; For Hertzian nonlinear exponent.

[0162] In one embodiment of the present invention, the step of identifying the corresponding contact models based on the exponentially weighted recursive least squares method to obtain the identification parameters of the rigid target and the weakly rigid target respectively includes:

[0163] For rigid targets, stiffness coefficients are obtained based on the K-model and used as the parameters to be identified for the rigid targets;

[0164] For weakly rigid targets, the equivalent stiffness and equivalent damping are obtained based on the Kelvin-Voigt model as the parameters to be identified for the weakly rigid targets.

[0165] Specifically, for rigid targets, using the K-model, the only parameter to be identified is its equivalent stiffness. The recurrence relation is identified as follows:

[0166] ;

[0167] ;

[0168] ;

[0169] in: The Kalman gain for exponentially weighted recursive least squares. The number of recursion steps, The covariance matrix of the exponentially weighted recursive least squares method. The equivalent stiffness parameter is the regression value obtained by exponentially weighted recursive least squares method. For the displacement of the end effector, The force sensor measures the interaction force between the robotic arm and its environment. These are the weighting coefficients for the exponentially weighted recursive least squares method.

[0170] For weakly stiff targets, the Kelvin-Voigt model is used, and the parameters to be identified have equivalent stiffness. and equivalent damping The recurrence relation is identified as follows:

[0171] ;

[0172] in: The parameter vector consists of the estimated equivalent stiffness and equivalent damping, and the regression vector is obtained by the exponentially weighted recursive least squares method. Displacement by end effector and speed composition, The force sensor measures the interaction force between the robotic arm and the environment.

[0173] In one embodiment of the present invention, the linearization of the nonlinear contact model of the flexible target based on the end-effector low-speed motion assumption to obtain the parameters to be identified of the flexible target includes: obtaining and linearizing the Hunt-Crossley model formula.

[0174] The equivalent stiffness, equivalent damping, and Hertzian nonlinear exponent are obtained from the linearized Hunt-Crossley model as the parameters to be identified for the flexible target.

[0175] Specifically, for the Hunt-Crossley model, the parameters to be identified include equivalent stiffness. Equivalent damping and Hertzian nonlinear exponent n However, since the Hunt-Crossley model formula is nonlinear, parameter identification cannot be performed directly. Therefore, an approximation method is used to linearize the Hunt-Crossley model formula.

[0176] Taking the natural logarithm of both sides of the equation in the model formula, we get:

[0177] ;

[0178] in: For the environmental forces in the Hunt-Crossley model, The equivalent stiffness of the Hunt-Crossley model is given. For the equivalent damping of the Hunt-Crossley model, The Hertzian nonlinear exponent of the Hunt-Crossley model. For environmental deformations, For environmental deformation rate;

[0179] Taking the Taylor expansion of the Lagrange remainder in the nonlinear term, we get:

[0180] ;

[0181] in: The Lagrange median after Taylor expansion;

[0182] Assumption If it is small enough, we can obtain:

[0183] ;

[0184] In fact, as long as the conditions are met The above approximation will not have a significant impact on parameter identification. In practice, the flexible target is equivalent to the equivalent stiffness of the Hunt-Crossley model. Often much greater than the equivalent damping Furthermore, the speed of the end effector when it first contacts the target is generally not very high, so it can meet the requirements. conditions.

[0185] Therefore, the Hunt-Crossley model formula can be simplified to:

[0186] ;

[0187] The parameter identification recursive equation for the above formula is:

[0188] ;

[0189] ;

[0190] ;

[0191] In the formula, The estimated equivalent stiffness, equivalent damping, and Hertzian nonlinear exponent form a parameter vector. Displacement of the end effector and speed The resulting regression vector. After the recursion is complete, the parameter identification result is obtained by inverse solving the following formula:

[0192] .

[0193] in: , , Sequential corresponding parameter vector The present invention uses the exponentially weighted recursive least squares method to accurately identify the contact model parameters of rigid and weakly rigid targets, and combines the low-speed assumption at the end point to linearize the nonlinear contact model of flexible targets. This effectively improves the accuracy and efficiency of parameter identification for targets with different rigidity and flexibility, reduces the control computation load in complex spatial environments, and enhances the stability and compliance of the robotic arm in contact with the target.

[0194] In one embodiment of the present invention, as Figures 6-22 As shown, the designed control switching vibration suppression strategy is used to control different types of targets. The control effect is reflected by force tracking accuracy, force tracking convergence speed, impedance parameter identification accuracy, impedance parameter identification convergence speed, and damping gain energy consumption. The higher the force tracking accuracy, the faster the force tracking convergence speed, the faster the impedance parameter identification convergence speed, the more accurate the impedance parameter identification accuracy, and the less the damping gain energy consumption, the better the control effect.

[0195] Specifically, Figure 6 A control flow diagram for vision-based hierarchical switching enhancement hybrid control in a single degree of freedom.

[0196] Position control is performed during the precise approach phase before target contact. During this phase, a vision system acquires and processes images of the non-cooperative target in space, performing target classification, feature extraction, and multi-feature fusion. Based on a prior knowledge base, the contact area of ​​the target is then classified into rigid, weakly rigid, or flexible categories. According to the current contact state and classification results, the system dynamically switches between a position controller and a force controller. During the switching transient phase, the corresponding vibration suppression control algorithm is adaptively activated based on the rigidity / flexibility category. During this phase, force sensor and encoder feedback data are used to estimate the stiffness and damping parameters of the contact interface in real time through an online environmental impedance parameter identification algorithm. This is used to adjust the vibration suppression control parameters, thereby achieving adaptive control throughout the entire process of safe approach, compliant contact, and stable capture of unknown non-cooperative targets.

[0197] Specifically, Figures 7-11 The figures show a comparison of vibration suppression control effects during control switching, impedance parameter identification curves, and semi-active damping variation graphs for a rigid target with an equivalent stiffness of 10000 N / m. Figures 7-9 It can be seen that, in terms of control effect, compared with fixed low-damping control, the designed vibration suppression strategy for rigid targets can completely suppress overshoot and vibration; compared with fixed high-damping control, the vibration suppression control force tracking convergence speed is faster and the damping gain energy consumption is less; such as Figure 10 As shown, in terms of impedance parameter identification, the equivalent stiffness identification is accurate and converges quickly; for example... Figure 11 As shown, regarding the change in damping gain parameter value, the change in damping gain adjusted according to the force signal is as expected, being larger in the initial contact stage and smaller near the steady state.

[0198] Figures 12-16 The diagram shows the compliance control correlation for a weakly rigid target with an equivalent stiffness of 1000 N / m and an equivalent damping of 2 Nm / s. Figures 12-14 It can be seen that, similar to the compliant control effect for rigid targets, the vibration suppression control for weakly rigid targets can accelerate force tracking convergence speed and reduce damping energy consumption while completely suppressing overshoot and vibration; for example... Figure 15 As shown, in terms of impedance parameter identification, the equivalent stiffness identification is accurate and converges quickly; for example... Figure 16 As shown, the damping change adjusted according to the position signal is as expected in terms of the change in the damping gain parameter value.

[0199] Figures 17-22 This is a graph showing the compliance control correlation for a flexible target with an equivalent stiffness of 100 N / m, an equivalent damping of 5 Nm / s, and a Hertzian nonlinear exponent of 1.6. Figures 17-19 It can be seen that, in terms of control effect, compared with fixed low-damping control, vibration suppression control can completely suppress overshoot and vibration without affecting the ascent speed; compared with fixed high-damping control, vibration suppression control has a faster convergence speed. For example... Figure 20 and Figure 21 As shown, the equivalent stiffness and Hertzian nonlinear exponent are accurately identified in terms of impedance parameter identification. Figure 22 As shown, regarding the change in damping gain parameter value, the damping change adjusted according to the position signal is as expected, being smaller in the initial contact stage and larger near steady state.

[0200] like Figure 23 As shown, a second aspect of the present invention provides a space non-cooperative target switching enhanced force potential control system, comprising:

[0201] Design unit 500 is constructed to build and design a switching enhanced force-position hybrid controller for non-cooperative targets in space based on the dynamic model of the flexible base space manipulator.

[0202] The visual grading unit 600 is used to visually identify non-cooperative targets in space before contact, and to classify each target into rigidity and flexibility based on prior knowledge and obtain the corresponding contact model. The results of rigidity and flexibility grading include at least: rigid targets, weakly rigid targets and flexible targets.

[0203] The parameter identification unit 700 is used to identify parameters based on the acquired contact model and obtain the identified parameters corresponding to each target.

[0204] The vibration suppression control unit 800 is used to feed back the identified parameters to the switching enhanced force-position hybrid controller, and drive the switching enhanced force-position hybrid controller to execute the corresponding vibration suppression control strategy for each target, so as to realize adaptive force-position hybrid control for non-cooperative targets in space.

[0205] In one embodiment of the present invention, the construction design unit further includes a dynamic model construction subunit and a hybrid controller design subunit. The dynamic model construction unit is at least used to construct a dynamic model of a flexible base space manipulator, and the hybrid controller design unit is at least used to design a switching enhanced force position hybrid controller for a non-cooperative space target based on the dynamic model of the flexible base space manipulator.

[0206] like Figure 23 As shown, a third aspect of the present invention provides an electronic device suitable for on-orbit servicing satellites, comprising: at least one processor; and at least one memory communicatively connected to the processor, wherein: the memory stores program instructions executable by the processor, and the processor invokes the program instructions to perform the steps of the space non-cooperative target switching enhanced force potential control method as described in any of the above embodiments.

[0207] In one embodiment of the present invention, the electronic device includes a visual acquisition module, a memory, a processor, and a computer program stored in the memory and executable on the processor. The visual acquisition module is used to acquire image data of a target satellite before contact with a non-cooperative target in space, including but not limited to high-resolution cameras and image sensors, supporting real-time imaging under complex space lighting and attitude changes. The memory stores software programs, modules, visual algorithm models, and a priori knowledge bases. The processor executes various functional applications and data processing by running the software programs and modules stored in the memory, including image processing, stiffness grading, contact model parameter identification, and control strategy execution. The electronic device adopts a hierarchical bus architecture design. The memory and processor are connected to the I / O bus via a system bus, memory bus, and I / O bridge. Visual data acquired by the visual acquisition module is transmitted to the processor for real-time processing via the I / O bus.

[0208] Any process or method description in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or more executable instructions for implementing a particular logical function or process, and the scope of the preferred embodiments of the invention includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as will be understood by those skilled in the art to which embodiments of the invention pertain.

[0209] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus or device (such as a computer-based system, a system including a processing module or other system that can fetch and execute instructions from, an instruction execution system, apparatus or device).

[0210] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for enhancing force potential control by switching non-cooperative targets in space, characterized in that, include: A dynamic model of a flexible-base space manipulator was constructed, and a hybrid force-potential switching controller for non-cooperative targets in space was designed. Before contact, non-cooperative targets in space are visually identified, and each target is classified into rigid and flexible categories based on prior knowledge to obtain the corresponding contact model. The results of the rigid-flexibility classification include at least: rigid targets, weakly rigid targets, and flexible targets. Based on the obtained contact model, parameter identification is performed to obtain the identified parameters corresponding to each target; The identified parameters are fed back to the switching enhanced force-potential hybrid controller, which drives the switching enhanced force-potential hybrid controller to execute the corresponding vibration suppression strategy for each target, so as to achieve adaptive force-potential hybrid control for non-cooperative targets in space.

2. The space non-cooperative target switching enhanced force potential control method according to claim 1, characterized in that, The constructed and designed dynamic model of the flexible base space manipulator, along with the design of a switching enhanced force-potential hybrid controller for non-cooperative space targets, includes: Establish a kinematic chain model for a flexible-base space robotic arm; Based on the kinematic chain model of the flexible base space manipulator and the Lagrange method, a dynamic model of the flexible base space manipulator is constructed: Based on the aforementioned dynamic model of the flexible base space manipulator, a switching-enhanced force-potential hybrid controller is designed for non-cooperative space targets with unknown environmental constraints; wherein: For non-cooperative targets in space with unknown environmental constraints, a selection matrix is ​​designed to determine whether force control or position control is applied to each degree of freedom, based on the idea of ​​switching enhanced force-potential hybrid control. By comparing the measured contact force or torque with the corresponding preset threshold, the contact state between each degree of freedom and the target is determined, thereby selecting position control or force control; wherein: only one control method is performed on a single degree of freedom; if it is a free motion state, position control is performed, and if it is a constrained motion state, force control is performed.

3. The space non-cooperative target switching enhanced force potential control method according to claim 2, characterized in that, The driving torque of the switching enhanced force position hybrid controller Torque generated by position control , Torque generated by force control , Composition, the expression is: ;in: The position control section employs decomposed acceleration control, consisting of two torque components: one is the torque generated by the joint position PD controller. The other is the joint acceleration feedforward torque. The expressions are as follows: ； ； in, S To select a matrix, and These are the proportional gain and derivative gain of the position controller, respectively. For the desired end position, For the desired terminal velocity, For the desired terminal acceleration, This is the forward kinematics transformation matrix for the robotic arm. Let Jacobian matrix be the value of the robotic arm. Let be the time derivative of the Jacobian matrix of the robotic arm. For the joint angle of the robotic arm, The angular velocity of the robotic arm joints; The force control section employs feedforward explicit force control, consisting of a proportional controller based on the force error signal and a speed-related damping gain generating the control torque. The other is the feedforward torque calculated from the selected desired force. The expressions are as follows: ； ； in, S To select a matrix, For the proportional gain of the force controller, For adjustable damping gain, For the power of expectation, The interaction force between the robotic arm and the environment, It is the identity matrix. Let Jacobian matrix be the value of the robotic arm. Let be the force Jacobian matrix of the robotic arm. This refers to the angular velocity of the robotic arm joints.

4. The space non-cooperative target switching enhanced force potential control method according to claim 1, characterized in that, The aforementioned visual identification of non-cooperative targets in space before contact includes: Before contact with non-cooperative targets in space, precise identification of target satellite parts can be achieved by using monocular / multi-view cameras, lidar, and lightweight vision algorithms suitable for aerospace chips onboard servicing satellites.

5. The space non-cooperative target switching enhanced force potential control method according to claim 4, characterized in that, The step of classifying each target into rigid and flexible categories and obtaining corresponding contact models by combining prior knowledge includes: mapping and classifying the identified parts according to stiffness level based on a pre-stored prior knowledge base. For a failed satellite, the main structure of the satellite is classified as a rigid target, the thruster nozzle and satellite antenna are classified as weakly rigid targets, and easily deformable parts are classified as flexible targets. Using the visual grading results as input, the identified target parts are mapped to the corresponding contact model library to obtain the corresponding contact model.

6. The space non-cooperative target switching enhanced force potential control method according to claim 1, characterized in that, The step of feeding back the identified parameters to the switching enhanced force-potential hybrid controller, driving the switching enhanced force-potential hybrid controller to execute corresponding vibration suppression strategies for each target, in order to achieve adaptive force-potential hybrid control for non-cooperative targets in space, includes: In the force-position hybrid control, the damping gain of the force control part is set to the sum of the real-time damping gain and the fixed damping gain. For rigid targets, the real-time damping gain is adjusted using force signals; for weakly rigid or flexible targets, the real-time damping gain is adjusted using position signals.

7. The space non-cooperative target switching enhanced force potential control method according to claim 1, characterized in that, The parameter identification based on the acquired contact model, obtaining the identified parameters corresponding to each target, includes: The corresponding contact models are identified using the exponentially weighted recursive least squares method to obtain the identification parameters for the rigid target and the weakly rigid target, respectively, wherein: For rigid targets, stiffness coefficients are obtained based on the K-model and used as the parameters to be identified for the rigid targets. For weakly rigid targets, the equivalent stiffness and equivalent damping are obtained based on the Kelvin-Voigt model as the parameters to be identified for the weakly rigid targets.

8. The space non-cooperative target switching enhanced force potential control method according to claim 1, characterized in that: The parameter identification based on the acquired contact model, obtaining the identified parameters corresponding to each target, includes: The nonlinear contact model of the flexible target is linearized based on the assumption of low-speed end motion to obtain the identification parameters of the flexible target, wherein: Obtain and linearize the Hunt-Crossley model formula; The equivalent stiffness, equivalent damping, and Hertzian nonlinear exponent are obtained from the linearized Hunt-Crossley model as the parameters to be identified for the flexible target.

9. A space non-cooperative target switching enhanced force-position control system, characterized in that, include: A design unit is constructed to build and design a switching enhanced force-position hybrid controller for non-cooperative targets in space based on the dynamic model of the flexible base space manipulator. The visual grading unit is used to visually identify non-cooperative targets in space before contact, and to classify each target into rigidity and flexibility based on prior knowledge and obtain the corresponding contact model. The results of rigidity and flexibility grading include at least: rigid targets, weakly rigid targets, and flexible targets. The parameter identification unit is used to identify parameters based on the acquired contact model and obtain the identified parameters corresponding to each target. The vibration suppression control unit is used to feed back the identified parameters to the switching enhanced force-position hybrid controller, and drive the switching enhanced force-position hybrid controller to execute the corresponding vibration suppression strategy for each target, so as to realize adaptive force-position hybrid control for non-cooperative targets in space.

10. An electronic device suitable for on-orbit servicing satellites, characterized in that, include: At least one processor; And at least one memory communicatively connected to the processor, wherein: the memory stores program instructions executable by the processor, and the processor invokes the program instructions to perform the steps of the space non-cooperative target switching enhanced force potential control method as described in any one of claims 1-8.

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