Low-gravity simulation follow-up control method and device for deep space exploration landing test

Abstract

This invention discloses a low-gravity simulation servo control method and apparatus for deep space exploration landing experiments. The method includes: acquiring the structural parameters of the low-gravity simulation test platform and establishing a spatial structural model of the parallel cable drive system based on the structural parameters; establishing a force-displacement characteristic model of the parallel cable drive system based on the spatial structural model, and obtaining mapping relationship data between platform displacement data and cable tension data based on the force-displacement characteristic model; acquiring the motion trajectory data of the deep space probe during the landing process, determining the target servo trajectory of the servo platform based on the motion trajectory data, and calculating the target cable tension data required to achieve the target servo trajectory based on the mapping relationship data; and controlling the drive device in the parallel cable drive system to adjust the tension of each cable based on the target cable tension data to drive the servo platform to move according to the target servo trajectory. This invention solves the technical problem of poor servo platform control performance in the prior art.

Description

Technical Field

[0001] This invention relates to the field of deep space exploration, and more specifically, to a low-gravity simulation servo control method and apparatus for deep space exploration landing experiments. Background Technology

[0002] With the development of deep space exploration technology, landing and exploration on celestial bodies such as the Moon and Mars has become an important research direction in the aerospace field. During the development of deep space probes, corresponding simulation experiments are usually conducted on the ground to verify the probe's dynamic performance and control strategies during the landing phase. However, because the gravitational environment of celestial bodies such as the Moon and Mars is significantly lower than Earth's gravity, direct experiments on Earth cannot accurately reflect the probe's motion characteristics under low-gravity conditions. Therefore, it is necessary to utilize low-gravity simulation test platforms to verify the relevant processes on the ground.

[0003] Currently, common low-gravity simulation methods include air-floating simulation platforms, drop tower test devices, and rope-suspended simulation systems. Among these, rope-suspended low-gravity simulation systems suspend the test object from a supporting structure using multiple ropes, and adjust the rope length or tension via a drive device to partially compensate for the object's gravity. Due to its advantages such as large workspace, long test time, and flexible structural design, this type of system has been widely used in deep space probe landing test research.

[0004] In existing technologies, some low-gravity simulation test platforms employ parallel cable-driven structures, achieving spatial motion control of the servo platform through the coordinated action of multiple cables. However, in practical applications, existing systems still have certain shortcomings in areas such as cable tension calculation, tension distribution, and servo control accuracy. For example, some systems do not fully consider factors such as cable elastic deformation during modeling, leading to deviations between the calculated tension and the actual situation. Furthermore, under multi-rope redundant drive conditions, without a reasonable tension distribution method, uneven cable tension or insufficient stability can easily occur, thus affecting the control performance of the servo platform.

[0005] Therefore, it is necessary to propose an improved low-gravity simulation servo control method to improve the control accuracy and stability of the parallel cable drive system, thereby better meeting the needs of deep space probe landing tests. Summary of the Invention

[0006] This invention provides a low-gravity simulation servo control method and apparatus for deep space exploration landing tests, which at least solves the technical problem of poor control effect of servo platforms in the prior art.

[0007] According to one aspect of the present invention, a low-gravity simulation servo control method for deep space exploration landing experiments is provided, comprising: acquiring structural parameters of a low-gravity simulation test platform, and establishing a spatial structural model of a parallel cable drive system based on the structural parameters; establishing a force-displacement characteristic model of the parallel cable drive system based on the spatial structural model, and obtaining mapping relationship data between platform displacement data and cable tension data based on the force-displacement characteristic model; acquiring motion trajectory data of a deep space probe during landing, determining a target servo trajectory of the servo platform based on the motion trajectory data, and calculating target cable tension data required to achieve the target servo trajectory based on the mapping relationship data; and controlling a drive device in the parallel cable drive system to adjust the tension of each cable based on the target cable tension data, so as to drive the servo platform to move according to the target servo trajectory.

[0008] According to another aspect of the present invention, a low-gravity simulation servo control device for deep space exploration landing experiments is also provided, comprising: a structural modeling module configured to acquire structural parameters of a low-gravity simulation test platform and establish a spatial structural model of a parallel cable drive system based on the structural parameters; a mechanical modeling module configured to establish a force-displacement characteristic model of the parallel cable drive system based on the spatial structural model and obtain mapping relationship data between platform displacement data and cable tension data based on the force-displacement characteristic model; a tension solving module configured to acquire motion trajectory data of a deep space probe during landing, determine a target servo trajectory of the servo platform based on the motion trajectory data, and calculate the target cable tension data required to achieve the target servo trajectory based on the mapping relationship data; and a servo control module configured to control the drive device in the parallel cable drive system to adjust the tension of each cable based on the target cable tension data, so as to drive the servo platform to move according to the target servo trajectory.

[0009] In this embodiment of the invention, structural parameters of a low-gravity simulation test platform are acquired, and a spatial structural model of a parallel cable-driven system is established based on these parameters. A force-displacement characteristic model of the parallel cable-driven system is established based on the spatial structural model, and mapping relationship data between platform displacement data and cable tension data is obtained based on the force-displacement characteristic model. Motion trajectory data of a deep space probe during landing is acquired, and a target servo trajectory of the servo platform is determined based on the motion trajectory data. The target cable tension data required to achieve the target servo trajectory is calculated based on the mapping relationship data. The drive device in the parallel cable-driven system is controlled to adjust the tension of each cable based on the target cable tension data, thereby driving the servo platform to move according to the target servo trajectory. This solution solves the technical problem of poor control effect of the servo platform in the prior art. Attached Figure Description

[0010] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this application, illustrate exemplary embodiments of the invention and, together with their description, serve to explain the invention and do not constitute an undue limitation thereof. In the drawings:

[0011] Figure 1 This is a flowchart of an optional low-gravity simulation servo control method for a deep space exploration landing test according to an embodiment of the present invention;

[0012] Figure 2 This is a structural diagram of an optional parallel cable drive system according to an embodiment of the present invention;

[0013] Figure 3 This is a structural diagram of an optional fast servo system according to an embodiment of the present invention;

[0014] Figure 4 This is a flowchart of another optional low-gravity simulation servo control method for deep space exploration landing tests according to an embodiment of the present invention;

[0015] Figure 5 This is a schematic diagram of the structure of an optional low-gravity simulation servo control device for a deep space exploration landing test according to an embodiment of the present invention;

[0016] Figure 6 A schematic diagram of the structure of a computer device suitable for implementing embodiments of the present disclosure is shown. Detailed Implementation

[0017] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0018] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0019] According to an embodiment of the present invention, a method embodiment of a low gravity simulation servo control method for deep space exploration landing experiments is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0020] Figure 1 This is a low-gravity simulation servo control method for deep space exploration landing tests according to embodiments of the present invention, such as... Figure 1 As shown, the method includes the following steps:

[0021] Step S102: Obtain the structural parameters of the low gravity simulation test platform, and establish a spatial structural model of the parallel cable drive system based on the structural parameters.

[0022] For example, the structural parameters of the tower, the servo platform, and the parallel cable drive device in the low gravity simulation test platform are obtained. The tower structural parameters include tower height, tower beam position, and tower installation point distribution. A global coordinate system for the test platform is established based on the tower structural parameters, and a local coordinate system for the servo platform is established based on the servo platform structural parameters. Coordinate transformation calculations are then performed on the fixed cable connection points on the tower side and the movable cable connection points on the servo platform side based on the global and local coordinate systems. The spatial coordinate relationships of each cable connection point are determined based on the coordinate transformation calculation results. A spatial geometric topology of the parallel cable drive system is established based on the spatial coordinate relationships, and a spatial structural model of the parallel cable drive system is constructed based on the spatial geometric topology.

[0023] Step S104: Establish a force-displacement characteristic model of the parallel cable drive system based on the spatial structure model, and obtain the mapping relationship data between platform displacement data and cable tension data based on the force-displacement characteristic model.

[0024] For example, based on the spatial structure model, the spatial position data of each rope connection point is extracted, and the unit direction vector of each rope is calculated according to the spatial position data; based on the unit direction vector, the component expression relationship of each rope tension in the global coordinate system is established, and the expression matrix of the force of the rope tension on the servo platform is constructed according to the component expression relationship of each rope tension; the force balance equation of the servo platform is established according to the expression matrix, and the force-displacement characteristic model is constructed based on the force balance equation.

[0025] The process of obtaining the mapping relationship between platform displacement data and rope tension data based on the force-displacement characteristic model includes: acquiring the displacement input data of the servo platform during the test; calculating the rope tension distribution required to achieve the displacement input data by solving the force balance equation; and establishing a correspondence between platform displacement data and rope tension data based on the rope tension distribution, which serves as the mapping relationship data.

[0026] Step S106: Obtain motion trajectory data of the deep space probe during the landing process, determine the target servo trajectory of the servo platform based on the motion trajectory data, and calculate the target rope tension data required to realize the target servo trajectory based on the mapping relationship data.

[0027] For example, real-time position, velocity, and acceleration data of a deep space probe during a landing test are acquired, and a three-dimensional motion trajectory model of the probe is constructed based on the position, velocity, and acceleration data. Based on the three-dimensional motion trajectory model, trajectory interpolation processing is performed on the position changes of the probe at different time points to generate continuous probe motion trajectory data. The target servo trajectory to be executed by the servo platform is determined based on the probe motion trajectory data. Target displacement data corresponding to the servo platform at each time point is extracted based on the target servo trajectory. The corresponding tension relationship in the mapping relationship data is found based on the target displacement data. The tension values ​​of each rope required to achieve the target displacement are calculated using the found tension relationship, and this is used as the target rope tension data.

[0028] Step S108: Based on the target rope tension data, control the drive device in the parallel cable drive system to adjust the tension of each rope, so as to drive the follower platform to move according to the target follower trajectory.

[0029] For example, the motor parameters of each drive motor and the drum mechanism parameters of the parallel cable drive system are obtained; the required drum rotation amount for each rope is calculated based on the target rope tension data; the target drive angular displacement of each drive motor is calculated based on the drum rotation amount; and drive motor control commands are generated based on the target drive angular displacements. The follower platform is driven to move according to the target follower trajectory based on the drive motor control commands.

[0030] During ground verification for deep space exploration missions, the gravitational environments of celestial bodies such as the Moon and Mars are significantly lower than those on Earth. Therefore, it is necessary to use a low-gravity simulation test platform to reproduce the dynamic behavior of the probe during the landing phase on the ground. Addressing the issues of insufficient servo accuracy and unstable cable tension distribution in traditional low-gravity simulation platforms, this embodiment proposes a low-gravity simulation servo control method based on a parallel cable drive system. This method constructs a spatial structure model and a force-displacement characteristic model, establishes a mapping relationship between platform displacement data and cable tension data, and achieves precise control of the servo platform accordingly.

[0031] In this embodiment, the low gravity simulation test platform mainly includes a tower structure, a parallel cable drive system, and a servo platform. The parallel cable drive system is as follows: Figure 2 As shown, the platform is connected to a follow-up platform via multiple ropes, with the other end of each rope fixed to the top structure of the tower. Tension adjustment is achieved by a drive device. By coordinating and controlling the tension of each rope, the following can be realized: Figure 3 The shown servo platform performs three-dimensional motion in space, thereby enabling real-time tracking of the motion during the landing process of a deep space probe.

[0032] This application provides another low-gravity simulation servo control method for deep space exploration landing experiments, applied to the low-gravity simulation test platform described above, such as... Figure 4 As shown, the method includes the following steps:

[0033] Step S402: Obtain the structural parameters of the low gravity simulation test platform and establish a spatial structure model.

[0034] In this step, the structural parameters of the low-gravity simulation test platform are first obtained, and a spatial structural model of the parallel cable-driven system is established accordingly. This process is the foundation of the entire control method, and its modeling accuracy will directly affect the subsequent tension calculation and motion control performance.

[0035] In the specific implementation process, the structural parameters of the tower, the servo platform, and the parallel cable drive device in the test platform are first obtained. The tower structural parameters include the tower height, the crossbeam installation position, and the spatial distribution information of the cable installation points. Let the tower height be... The number of crossbeams at the top of the tower is Several rope fixing points are set on each crossbeam, and their spatial coordinates can be represented as follows:

[0036]

[0037] in, , indicating the first The anchor point on the tower side of the rope; These represent the three-dimensional coordinates of the fixed point in the global coordinate system.

[0038] To uniformly describe the positional relationships of the various structures on the test platform, a global coordinate system for the test platform is established at the center of the tower base:

[0039]

[0040] in, Represents the origin of the global coordinate system; The axis points vertically towards the top of the tower; , The axis lies in the horizontal plane.

[0041] Next, based on the structural parameters of the servo platform, a local coordinate system is established at the geometric center of the servo platform:

[0042]

[0043] in, The central point of the servo platform; These are the local coordinate axes of the servo platform.

[0044] Several rope connection points are also set on the servo platform. The positions of these connection points relative to the local coordinate system of the servo platform can be represented as follows: When the servo platform undergoes spatial motion, its attitude and position can be described by a homogeneous transformation matrix. Let the platform's pose in the global coordinate system be...

[0045]

[0046] in for The rotation matrix is ​​used to describe the platform's attitude. This is the position vector of the platform center in the global coordinate system.

[0047] This transformation matrix can be used to transform the coordinates of connection points in the local coordinate system of the servo platform to the global coordinate system:

[0048] In the formula Indicates the first The position of each platform connection point in the global coordinate system.

[0049] Obtain the coordinates of the fixed point on the side of the tower. Coordinates of the connection point with the platform side Then, the spatial geometric relationships of each rope can be determined. The spatial vector of the root rope can be represented as

[0050]

[0051] Its length is

[0052]

[0053] in This represents the Euclidean norm.

[0054] The above calculations yield the geometric distribution of all ropes in space. Furthermore, a topological graph is constructed representing all rope connection points and their relationships:

[0055]

[0056] in Represents a set of nodes; This indicates the connection between ropes.

[0057] Step S404: Calculate the rope direction vector based on the spatial structure model.

[0058] After completing the spatial structure modeling, the directional information of each rope is calculated in order to establish the relationship between rope tension and platform forces.

[0059] Based on the rope space vector obtained in step S402 Its unit direction vector can be calculated:

[0060]

[0061] in Indicates the first The unit direction vector of the rope.

[0062] When the rope tension is At that time, the force exerted by the rope on the servo platform can be expressed as:

[0063]

[0064] in Indicates the first The tension value of the rope.

[0065] To facilitate matrix representation, all rope direction vectors are combined to form a direction matrix:

[0066]

[0067] The corresponding tension vector is represented as

[0068] Therefore, the resultant force exerted on the platform by the tension of each rope can be written as:

[0069]

[0070] in This represents the total tensile force experienced by the servo platform.

[0071] Step S406: Construct the force balance equation of the servo platform and establish the force-displacement characteristic model.

[0072] After obtaining the rope direction information, the mechanical equilibrium relationship of the servo platform is established. This relationship describes the coupling between platform displacement and rope tension, and is an important basis for subsequent tension calculations.

[0073] In the low-gravity simulation experiment, the servo platform is subjected to the tension of the ropes, its own weight, and the equivalent weight of the simulated detector. Let the equivalent mass of the platform and load be... Earth's gravitational acceleration is Then the gravity that the system needs to compensate for is

[0074]

[0075] When the platform is in a static or quasi-static motion state, its force equilibrium condition can be expressed as follows:

[0076]

[0077] in This indicates other external disturbances, such as air resistance or equipment friction.

[0078] After sorting, we get

[0079]

[0080] This equation is the basic force balance model of the parallel cable drive system.

[0081] The tension mapping model for rope flexibility compensation will be described below.

[0082] In traditional parallel cable-driven systems, the ropes are typically treated as ideal rigid cables. However, in large low-gravity simulation platforms, the rope lengths often reach tens of meters, and their elastic elongation and sag effects can significantly impact system accuracy. If this factor is ignored, the tension distribution calculated based on the geometric model may deviate significantly from the actual system.

[0083] Therefore, this embodiment introduces a rope flexibility compensation matrix into the force displacement characteristic model to improve the accuracy of tension calculation.

[0084] Let the first The equivalent elastic modulus of the rope is The cross-sectional area is The original length is In tension Under the action, its elastic elongation can be expressed as

[0085]

[0086] Considering the influence of rope sag on the direction vector, a sag correction factor is introduced:

[0087]

[0088] in Let be the linear density of the rope. Therefore, the corrected direction vector can be expressed as:

[0089]

[0090] Further construct the corrected direction matrix Thus, the improved force equilibrium equations are obtained:

[0091]

[0092] This improved model can automatically compensate for rope elasticity and sag during tension calculation, thereby significantly improving the control accuracy of the servo platform.

[0093] Step S408: Establish the mapping relationship between platform displacement data and rope tension data.

[0094] During low-gravity simulation experiments, the servo platform needs to track the trajectory of the deep space probe in real time during the landing phase. Therefore, the control system needs to calculate the corresponding cable tension distribution scheme based on the platform's target displacement and attitude changes, thereby driving the parallel cable system to achieve the corresponding movement.

[0095] Based on the structural model and force balance model established in steps S402 to S406, the following force relationships can be obtained:

[0096]

[0097] in This represents the direction matrix after rope flexibility compensation; Represents the rope tension vector; Represents the gravity vector of the platform and its load; This indicates external disturbance force.

[0098] However, in parallel cable-driven systems, the number of cables typically exceeds the platform's degrees of freedom. For example, when the system uses eight cables to drive the platform, but the platform only has three translational degrees of freedom or six kinematic degrees of freedom, the system is considered a redundant drive system. In this case, the above equations are generally underdetermined or overdetermined, requiring optimization methods to solve for tension distribution.

[0099] Therefore, in this embodiment, the platform pose vector is defined as follows:

[0100] in The coordinates of the platform's location; These respectively represent the platform's orbit. The attitude angle of the axis.

[0101] Changes in platform pose will cause changes in rope length. The length function of the rope can be expressed as: Differentiating this function yields the rate of change of the rope length:

[0102]

[0103] By combining all the relationships between the rope length changes, we can obtain...

[0104]

[0105] in

[0106] The Jacobian matrix of a parallel cable system is of the form:

[0107]

[0108] in For the platform center to the first A vector connecting points.

[0109] Furthermore, based on the principle of virtual work, a relationship can be established between the rope tension and the generalized force of the platform:

[0110]

[0111] in Let be the generalized force vector acting on the platform.

[0112] If the equivalent control required by the platform is expressed as Then the tension problem can be transformed into

[0113]

[0114] Since ropes can only withstand tension, they also need to meet tension constraints:

[0115]

[0116] in The minimum tension required to keep the rope taut at all times.

[0117] To obtain a stable and smooth tension distribution, this embodiment uses a least-squares optimization method to establish a displacement-tension mapping relationship:

[0118]

[0119] in Represents the generalized inverse matrix; This represents the prestress vector.

[0120] This mapping relationship can meet the platform's stress requirements while adjusting the rope tension distribution through redundant degrees of freedom, thereby avoiding excessive or insufficient tension in a single rope.

[0121] Step S410: Generate a target tracking trajectory based on the landing trajectory of the deep space probe.

[0122] After establishing the tension mapping relationship, the system needs to acquire the motion trajectory of the deep space probe during the landing process and convert it into the target trajectory that the servo platform needs to track.

[0123] Let the spatial trajectory of the deep space probe during the landing phase be...

[0124] in Indicates time.

[0125] To simulate a low-gravity environment in ground-based experiments, gravity compensation is required for the trajectory. Let the gravitational acceleration of the target celestial body be... Then the dynamic equation of the detector in the real environment is:

[0126]

[0127] in This indicates the landing thrust.

[0128] In a ground-based simulation environment, due to the acceleration due to gravity... Therefore, a parallel cable drive system is needed to compensate for the difference:

[0129]

[0130] in It is a unit vector in the vertical direction.

[0131] Based on this compensation relationship, the target trajectory of the servo platform can be obtained:

[0132]

[0133] in Displacement is compensated for by gravity difference.

[0134] By discretely sampling the target trajectory, a series of target pose points can be obtained:

[0135]

[0136] These discrete pose data constitute the target motion trajectory sequence of the servo platform.

[0137] Step S412: Calculate the target rope tension data based on the target trajectory.

[0138] After obtaining the target trajectory, the control system needs to calculate the corresponding rope tension at each moment in order to drive the platform to achieve precise follow-up.

[0139] Let the target pose be Its velocity and acceleration are respectively .

[0140] According to the platform dynamics equations:

[0141]

[0142] in This is the quality matrix; Here is the damping matrix; This is the equivalent stiffness matrix.

[0143] Therefore, the required generalized control force is

[0144]

[0145] Substituting this into the tension mapping relationship obtained in step S408, the target tension can be calculated:

[0146]

[0147] By calculating the entire trajectory sequence, the target tension data that varies with time can be obtained:

[0148] These tension data will serve as control inputs for the drive system, used to adjust the individual rope drive motors, thereby achieving motion control of the follower platform.

[0149] The tension smoothing optimization algorithm will be described below.

[0150] To avoid abrupt changes in tension between adjacent time steps, this embodiment further introduces a tension change rate constraint. Let the time step size be... Then the rate of change of tension can be expressed as

[0151]

[0152] System Requirements

[0153]

[0154] Therefore, the tension problem can be transformed into a constrained quadratic optimization problem:

[0155]

[0156] in For smoothing weighting coefficients; This is the tension vector from the previous moment.

[0157] This optimization method can make the rope tension change more stable, thereby improving the stability of the platform's follow-up control and reducing the impact load on the drive device.

[0158] Step S414: Execute drive control based on the target rope tension data.

[0159] In this step, the control system controls each drive unit in the parallel cable drive system according to the target tension data calculated in step S412, so that the cable tension is gradually adjusted to the target tension, thereby driving the follower platform to achieve target movement.

[0160] In practice, each rope is equipped with an independent drive unit, which typically consists of a servo motor, a reduction gear, and a rope winding mechanism. Let the first... The angular velocity of the drive motor corresponding to the rope is The radius of the rope winding mechanism is The relationship between the rate of change of rope length and the angular velocity of the motor can be expressed as:

[0161]

[0162] Based on the Jacobian relation established in step S408:

[0163]

[0164] The relationship between the motor angular velocity and the platform motion can be obtained:

[0165]

[0166] in

[0167]

[0168]

[0169] R is the radius matrix of the coiled rope.

[0170] However, in low-gravity simulation experiments, the system control objective is not only position control, but more importantly, ensuring that the rope tension meets the calculation results. Therefore, this embodiment adopts a tension-driven control strategy.

[0171] Let the real-time tension measured by the tension sensor be... The target tension is Then the tension error is

[0172]

[0173] By adjusting the motor drive current through the tension controller, the rope tension is gradually brought closer to the target value.

[0174] Step S416: Construct a closed-loop control model for rope tension.

[0175] To improve tension control accuracy, this embodiment introduces a tension closed-loop control algorithm into the drive system. Each rope is constructed with an independent closed-loop control circuit, the control structure of which includes a tension sensor, a controller, and a motor driver.

[0176] In one implementation, the tension controller employs a proportional-integral-derivative (PI-DE) control algorithm, and its control law can be expressed as follows:

[0177]

[0178] in This indicates the motor drive control signal; These are the proportional, integral, and derivative control coefficients, respectively.

[0179] After the control signal is input to the servo driver, the output torque of the motor can be adjusted, thereby changing the rope length and thus the rope tension.

[0180] The dynamics of a servo motor can be expressed as:

[0181]

[0182] in This refers to the moment of inertia of the motor. It is the viscous damping coefficient; This refers to the output torque of the motor.

[0183] The relationship between motor torque and control signal is as follows:

[0184]

[0185] in Let be the motor torque coefficient. Solving the above equations simultaneously yields the dynamic model of the tension control system.

[0186] The adaptive tension compensation control algorithm will be described below.

[0187] In large-scale low-gravity simulation platforms, due to the long rope lengths, high structural flexibility, and uncertainties such as air disturbances and friction changes during the experiment, relying solely on traditional PID control may be insufficient to guarantee long-term stable control accuracy. Therefore, this embodiment further proposes an adaptive tension compensation control algorithm.

[0188] First, define the system disturbance term: This disturbance term includes changes in rope elasticity, frictional disturbances, and the influence of the external environment. The system tension model can be expressed as follows:

[0189] To estimate this disturbance term, an adaptive estimator is introduced:

[0190] in This is the estimated value of the disturbance; This is the adaptive gain coefficient.

[0191] The control law is modified to

[0192]

[0193] By estimating and compensating for system disturbances in real time, the accuracy of rope tension control can be significantly improved, thereby further enhancing the trajectory tracking performance of the servo platform.

[0194] Step S418 realizes the trajectory tracking control of the follow-up platform.

[0195] After completing the tension closed-loop control, the control system continuously repeats the following process according to the predetermined control cycle: acquiring the current position and attitude information of the servo platform; calculating the current target pose based on the target trajectory; calculating the target rope tension; executing tension closed-loop control; and updating the tension data.

[0196] Let the current position of the platform be The target location is The trajectory tracking error is

[0197]

[0198] To further improve tracking accuracy, a position controller can be introduced at the trajectory layer:

[0199]

[0200] in Position control gain; This is for speed control gain.

[0201] The calculated generalized control force is then converted into rope tension control quantity through the tension mapping relationship in step S408, thus forming a trajectory control-tension control dual-layer control structure.

[0202] Through the above steps, the low-gravity simulation servo control method based on a parallel cable drive system proposed in this embodiment first obtains the structural parameters of the low-gravity simulation test platform and establishes a spatial structural model of the parallel cable drive system; based on this, it calculates the spatial direction vector of each cable and constructs a force-displacement characteristic model of the servo platform; then, it establishes a mapping relationship between platform displacement data and cable tension data, and generates the target motion trajectory of the servo platform according to the landing trajectory of the deep space probe; further, it calculates the target cable tension data and adjusts the tension of each cable in real time through the drive control system; finally, it achieves high-precision trajectory tracking of the servo platform through tension closed-loop control and adaptive compensation algorithm.

[0203] Compared with existing technologies, this embodiment has the following advantages: by establishing an accurate spatial structure model and force-displacement characteristic model of the parallel cable drive system, an accurate mapping relationship between platform displacement and cable tension can be achieved; by introducing a cable flexibility compensation model, the influence of cable elasticity and sag effect on system accuracy can be effectively reduced; by constructing tension closed-loop control and adaptive compensation algorithm, the tension control accuracy can be improved, thereby ensuring the stability and reliability of the servo platform in low gravity simulation tests.

[0204] This application also provides a low-gravity simulation servo control device for deep space exploration landing tests, such as... Figure 5 As shown, the system includes: a structural modeling module 52, configured to acquire the structural parameters of the low gravity simulation test platform and establish a spatial structural model of the parallel cable drive system based on the structural parameters; a mechanical modeling module 54, configured to establish a force-displacement characteristic model of the parallel cable drive system based on the spatial structural model and obtain mapping relationship data between platform displacement data and cable tension data based on the force-displacement characteristic model; a tension solving module 56, configured to acquire motion trajectory data of the deep space probe during the landing process, determine the target servo trajectory of the servo platform based on the motion trajectory data, and calculate the target cable tension data required to achieve the target servo trajectory based on the mapping relationship data; and a servo control module 58, configured to control the drive device in the parallel cable drive system to adjust the tension of each cable based on the target cable tension data, so as to drive the servo platform to move according to the target servo trajectory.

[0205] It should be noted that the low-gravity simulation servo control device for deep space exploration landing tests provided in the above embodiments is only an example of the division of the above functional modules. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. In addition, the low-gravity simulation servo control device for deep space exploration landing tests provided in the above embodiments and the low-gravity simulation servo control method embodiments for deep space exploration landing tests belong to the same concept, and the specific implementation process is detailed in the method embodiments, which will not be repeated here.

[0206] Figure 6 A schematic diagram of a computer device suitable for implementing embodiments of the present disclosure is shown. It should be noted that... Figure 6 The computer device shown is merely an example and should not be construed as limiting the functionality and scope of use of the embodiments disclosed herein.

[0207] like Figure 6 As shown, the computer device includes a central processing unit (CPU) 1001, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 1002 or a program loaded from a storage section 1008 into a random access memory (RAM) 1003. The RAM 1003 also stores various programs and data required for system operation. The CPU 1001, ROM 1002, and RAM 1003 are interconnected via a bus 1004. An input / output (I / O) interface 1005 is also connected to the bus 1004.

[0208] The following components are connected to I / O interface 1005: an input section 1006 including a keyboard, mouse, etc.; an output section 1007 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and speakers, etc.; a storage section 1008 including a hard disk, etc.; and a communication section 1009 including a network interface card such as a LAN card, modem, etc. The communication section 1009 performs communication processing via a network such as the Internet. A drive 1010 is also connected to I / O interface 1005 as needed. A removable medium 1011, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed on drive 1010 as needed so that computer programs read from it can be installed into storage section 1008 as needed.

[0209] The above description is only a preferred embodiment of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A low-gravity simulation servo control method for deep space exploration landing experiments, characterized in that, include: Obtain the structural parameters of the low gravity simulation test platform, and establish a spatial structural model of the parallel cable drive system based on the structural parameters; Based on the aforementioned spatial structure model, a force-displacement characteristic model of the parallel cable drive system is established, and based on the force-displacement characteristic model, the mapping relationship data between platform displacement data and cable tension data is obtained. Acquire motion trajectory data of the deep space probe during the landing process, determine the target servo trajectory of the servo platform based on the motion trajectory data, and calculate the target rope tension data required to realize the target servo trajectory based on the mapping relationship data; Based on the target rope tension data, the drive device in the parallel cable drive system is controlled to adjust the tension of each rope, so as to drive the follower platform to move according to the target follower trajectory.

2. The method according to claim 1, characterized in that, Obtain the structural parameters of the low gravity simulation test platform, and establish a spatial structural model of the parallel cable-driven system based on the structural parameters, including: Obtain the structural parameters of the tower, the servo platform, and the parallel cable drive device in the low gravity simulation test platform. The tower structural parameters include tower height parameters, tower beam position parameters, and tower installation point distribution parameters. A global coordinate system for the test platform is established based on the tower structure parameters. A local coordinate system for the follower platform is established based on the follower platform structure parameters. Coordinate transformation calculations are performed on the fixed connection points of the ropes on the tower side and the moving connection points of the ropes on the follower platform side based on the global coordinate system and the local coordinate system. The spatial coordinate relationship of each rope connection point is determined based on the coordinate transformation calculation results. The spatial geometric topology of the parallel cable drive system is established based on the spatial coordinate relationship. The spatial structure model of the parallel cable drive system is constructed based on the spatial geometric topology.

3. The method according to claim 1, characterized in that, Based on the aforementioned spatial structure model, a force-displacement characteristic model of the parallel cable-driven system is established, including: Based on the spatial structure model, the spatial position data of each rope connection point is extracted, and the unit direction vector of each rope is calculated based on the spatial position data. Based on the unit direction vector, establish the component expression relationship of each rope tension in the global coordinate system, and construct the expression matrix of the force of the rope tension on the follower platform according to the component expression relationship of each rope tension; The force balance equation of the servo platform is established based on the expression matrix, and the force-displacement characteristic model is constructed based on the force balance equation.

4. The method according to claim 3, characterized in that, Based on the force-displacement characteristic model, the mapping relationship between platform displacement data and rope tension data is obtained, including: The displacement input data of the servo platform during the test is obtained, and the rope tension distribution required to achieve the displacement input data is calculated by solving the force balance equation. The correspondence between platform displacement data and rope tension data is established based on the rope tension distribution, and this correspondence is used as the mapping relationship data.

5. The method according to claim 1, characterized in that, Acquire motion trajectory data of the deep space probe during the landing process, and calculate the target rope tension data required to achieve the target follow-up trajectory based on the motion trajectory data and the mapping relationship data, including: The system acquires real-time position, velocity, and acceleration data of the deep space probe during the landing test, and constructs a three-dimensional motion trajectory model of the probe based on the position, velocity, and acceleration data. Based on the three-dimensional motion trajectory model, trajectory interpolation processing is performed on the position change of the detector at different time nodes to generate continuous detector motion trajectory data, and the target follow-up trajectory to be executed by the follow-up platform is determined based on the detector motion trajectory data. Based on the target tracking trajectory, extract the target displacement data of the tracking platform at each moment. Based on the target displacement data, find the corresponding tension relationship in the mapping relationship data. Use the found tension relationship to calculate the tension values ​​of each rope required to achieve the target displacement, and use them as the target rope tension data.

6. The method according to claim 1, characterized in that, Based on the target rope tension data, the drive device in the parallel cable drive system is controlled to adjust the tension of each rope to drive the follower platform to move according to the target follower trajectory, including: The motor parameters of each drive motor and the drum mechanism parameters of the parallel cable drive system are obtained. The required drum rotation amount for each rope is calculated based on the target rope tension data. The target drive angular displacement of each drive motor is calculated based on the drum rotation amount. The drive motor control command is generated based on the target drive angular displacement. The drive motor control command drives the follow-up platform to move along the target follow-up trajectory.

7. A low-gravity simulation servo control device for deep space exploration landing tests, characterized in that, include: The structural modeling module is configured to acquire the structural parameters of the low gravity simulation test platform and establish a spatial structural model of the parallel cable drive system based on the structural parameters. The mechanical modeling module is configured to establish a force-displacement characteristic model of the parallel cable drive system based on the spatial structure model, and to obtain the mapping relationship data between platform displacement data and cable tension data based on the force-displacement characteristic model. The tension calculation module is configured to acquire motion trajectory data of the deep space probe during the landing process, determine the target servo trajectory of the servo platform based on the motion trajectory data, and calculate the target rope tension data required to realize the target servo trajectory based on the mapping relationship data. The follow-up control module is configured to control the drive device in the parallel cable drive system to adjust the tension of each cable based on the target cable tension data, so as to drive the follow-up platform to move according to the target follow-up trajectory.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored program, wherein, when the program is executed, it controls the device on which the computer-readable storage medium is located to perform the method according to any one of claims 1 to 6.

9. A computer device, characterized in that, include: Memory and processor The memory stores computer programs; The processor is configured to execute a computer program stored in the memory, wherein when the computer program is executed, the processor performs the method according to any one of claims 1 to 6.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

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