Positioning control method and device of Mars landing process verification system

Abstract

The invention discloses a positioning control method and device for a Mars landing process verification system. The method comprises the following steps: establishing a geometric model of an upper platform based on end point coordinates of a tower column and end point coordinates of a feed source cabin, and calculating a steel cable target length of the upper platform based on the geometric model of the upper platform and a target attitude of the feed source cabin; adjusting the actual length of each steel cable based on the target length of the steel cable and the kinetic model of the upper platform to obtain actual attitude data of the feed source cabin; calculating the ideal pose of the feed source based on the actual pose data of the feed source cabin and the geometric model of the lower platform, and calculating the target length of the telescopic rod of the lower platform based on the ideal pose; and adjusting the actual length of each telescopic rod based on the target length of the telescopic rod to obtain the actual attitude data of the feed source, and realizing the positioning control of the feed source based on the actual attitude data of the feed source. The technical problem that the feed source positioning precision is difficult to stably control due to the influence of the flexibility of the steel cable, external wind disturbance and the uncertainty of the model is solved.

Description

Technical Field

[0001] This invention relates to the field of Mars landing control, and more specifically, to a positioning control method and apparatus for a Mars landing process verification system. Background Technology

[0002] The Mars approach and landing process (i.e., the entire process of a Mars probe entering from the orbital segment, descending, and finally landing) is one of the most complex and risky phases in planetary exploration missions. This process involves several key technologies, including aerodynamic deceleration, attitude adjustment, and landing cushioning in a thin atmosphere.

[0003] To conduct dynamic simulations and verifications of the approach and landing process on the ground, it is necessary to build an experimental platform capable of accurately reproducing the probe's trajectory and attitude changes in three-dimensional space. This platform must achieve six-degree-of-freedom attitude control of the simulated cabin and maintain high stability and high response accuracy under disturbed environments.

[0004] Existing ground-based verification systems typically employ a single platform or a sling-type support structure to simulate the motion attitude of a spacecraft. However, the limited range of motion of traditional single platforms makes it difficult to meet the requirements of large-space attitude changes throughout the entire Mars landing process; while sling-type mechanisms, although offering a large range of motion, are highly flexible and susceptible to wind disturbances and vibrations, resulting in lower attitude control accuracy.

[0005] Furthermore, traditional control algorithms (such as PID or adaptive control) are prone to problems such as dynamic response lag, overshoot and steady-state error when faced with nonlinear coupling, time-varying disturbances and system parameter uncertainties, making it difficult to achieve high-precision, real-time tracking control of the probe's landing attitude.

[0006] There is currently no effective solution to the above problems. Summary of the Invention

[0007] This invention provides a positioning control method and apparatus for a Mars landing process verification system, which at least solves the technical problem that the positioning accuracy of the feed source is difficult to control stably due to the influence of the flexibility of the steel cable, external wind disturbance and model uncertainty.

[0008] According to one aspect of the present invention, a positioning control method for a Mars landing process verification system is provided, comprising: establishing a geometric model of an upper platform based on the coordinates of the tower endpoint and the feed cabin endpoint; calculating the target length of the steel cables of the upper platform based on the geometric model of the upper platform and the target attitude of the feed cabin; adjusting the actual length of each steel cable based on the target length of the steel cables and the dynamic model of the upper platform to obtain the actual attitude data of the feed cabin; calculating the ideal attitude of the feed based on the actual attitude data of the feed cabin and the geometric model of the lower platform; calculating the target length of the telescopic rods of the lower platform based on the ideal attitude; adjusting the actual length of each telescopic rod based on the target length of the telescopic rods to obtain the actual attitude data of the feed; and adaptively adjusting the control parameters of the upper platform and the lower platform based on the actual attitude data of the feed to achieve positioning control of the feed.

[0009] In some embodiments, a geometric model of the upper platform is established based on the coordinates of the tower endpoint and the feed cabin endpoint. Based on the geometric model of the upper platform and the target attitude of the feed cabin, the target length of the steel cable of the upper platform is calculated. This includes: acquiring the coordinate data of the tower endpoint in the ground coordinate system and the coordinate data of the connection point at the bottom of the feed cabin in the cabin coordinate system, respectively, as the tower endpoint coordinates and the feed cabin endpoint coordinates; establishing the geometric model of the upper platform based on the tower endpoint coordinates and the feed cabin endpoint coordinates; transforming the target attitude of the feed cabin from the body coordinate system to the ground coordinate system based on the orientation matrix of the upper platform's geometric model, obtaining the transformed target attitude parameters of the feed cabin; and calculating the spatial length of each steel cable based on the transformed target attitude parameters of the feed cabin to obtain the target length of the steel cable.

[0010] In some embodiments, a dynamic model of the upper platform is established based on the mass matrix, damping ratio, natural frequency, and driving force of the steel cable; based on the target length of the steel cable and the dynamic model of the upper platform, an extended state observer in the active disturbance rejection control algorithm is used to estimate external disturbances and system uncertainties in real time, which are then used as steel cable observation results; steel cable control quantities are calculated based on the steel cable observation results, and the length of each steel cable is adjusted based on the steel cable control quantities to obtain the actual length of each steel cable; the actual length of each steel cable is substituted into the inverse kinematics model of the platform to calculate the actual attitude data of the feed cabin in the ground coordinate system.

[0011] In some embodiments, the actual attitude data of the feed cabin is input into the geometric model of the lower platform to determine the spatial positional relationship between the feed plane and the bottom plane of the feed cabin, and the ideal pose of the feed is determined based on the parallel constraint conditions between the feed plane and the bottom plane of the feed cabin; based on the ideal pose, the spatial connection length of the telescopic rod of the lower platform is calculated as the target length of the telescopic rod.

[0012] In some embodiments, a dynamic model of the lower platform is established based on the mass matrix, damping ratio, natural frequency, and driving force of the telescopic rod; based on the target length of the telescopic rod and the dynamic model of the lower platform, an extended state observer in an active disturbance rejection control algorithm is used to estimate external disturbances and system uncertainties in real time to obtain telescopic rod observation results; based on the telescopic rod observation results, the telescopic rod control quantity is calculated, and the length of each telescopic rod is adjusted based on the telescopic rod control quantity to obtain the actual length of each telescopic rod; the actual length of each telescopic rod is substituted into the inverse kinematic model of the lower platform to calculate the actual attitude data of the feed in the ground coordinate system.

[0013] In some embodiments, the actual attitude data of the feed source is compared with its ideal attitude data to obtain an attitude error signal; the control parameters of the upper platform and the lower platform are adaptively adjusted based on the attitude error signal to achieve positioning control of the feed source.

[0014] According to another aspect of the present invention, a positioning control device for a Mars landing process verification system is also provided, comprising: a cable length determination module configured to establish a geometric model of an upper platform based on the coordinates of the tower endpoint and the feed cabin endpoint, and to calculate the target length of the cable of the upper platform based on the geometric model of the upper platform and the target attitude of the feed cabin; an adjustment module configured to adjust the actual length of each cable based on the target length of the cable and the dynamic model of the upper platform to obtain the actual attitude data of the feed cabin; a telescopic rod length determination module configured to calculate the ideal attitude of the feed based on the actual attitude data of the feed cabin and the geometric model of the lower platform, and to calculate the target length of the telescopic rod of the lower platform based on the ideal attitude; and a positioning control module configured to adjust the actual length of each telescopic rod based on the target length of the telescopic rod to obtain the actual attitude data of the feed, and to adaptively adjust the control parameters of the upper platform and the lower platform based on the actual attitude data of the feed to achieve positioning control of the feed.

[0015] According to another aspect of the present invention, a computer-readable storage medium is also provided, the computer-readable storage medium including a stored program, wherein, when the program is executed, it controls the device where the computer-readable storage medium is located to perform the method described in any of the above-described embodiments.

[0016] According to another aspect of the present invention, a computer device is also provided, comprising: a memory and a processor, the memory storing a computer program; the processor being configured to execute the computer program stored in the memory, wherein the computer program, when executed, causes the processor to perform the method described in any of the preceding embodiments.

[0017] According to another aspect of the present invention, a computer program product is also provided, including a computer program that, when executed by a processor, implements the steps of the method described in any of the preceding claims.

[0018] In this embodiment of the invention, a geometric model of the upper platform is established based on the coordinates of the tower end point and the feed cabin end point. Based on the geometric model of the upper platform and the target attitude of the feed cabin, the target length of the steel cable of the upper platform is calculated. Based on the target length of the steel cable and the dynamic model of the upper platform, the actual length of each steel cable is adjusted to obtain the actual attitude data of the feed cabin. Based on the actual attitude data of the feed cabin and the geometric model of the lower platform, the ideal pose of the feed is calculated, and the target length of the telescopic rod of the lower platform is calculated based on the ideal pose. Based on the target length of the telescopic rod, the actual length of each telescopic rod is adjusted to obtain the actual attitude data of the feed. Based on the actual attitude data of the feed, the control parameters of the upper and lower platforms are adaptively adjusted to achieve feed positioning control. This solution solves the technical problem that the feed positioning accuracy is difficult to stably control due to the influence of steel cable flexibility, external wind disturbance, and model uncertainty. Attached Figure Description

[0019] 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:

[0020] Figure 1 This is a flowchart of a positioning control method for an optional Mars landing process verification system according to an embodiment of the present invention;

[0021] Figure 2 This is a flowchart of another optional positioning control method for a Mars landing process verification system according to an embodiment of the present invention;

[0022] Figure 3 This is a schematic diagram of a platform according to an embodiment of the present invention;

[0023] Figure 4 This is a flowchart of an optional positioning control method according to an embodiment of the present invention;

[0024] Figure 5This is a schematic diagram of the positioning control device of an optional Mars landing process verification system according to an embodiment of the present invention;

[0025] Figure 6 A schematic diagram of the structure of a computer device suitable for implementing embodiments of the present disclosure is shown. Detailed Implementation

[0026] 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.

[0027] 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.

[0028] According to an embodiment of the present invention, a method embodiment of a positioning control method for a Mars landing process verification system 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.

[0029] Figure 1 This is a positioning control method for a Mars landing process verification system according to an embodiment of the present invention, such as... Figure 1 As shown, the method includes the following steps:

[0030] Step S102: Based on the coordinates of the tower end point and the feed cabin end point, establish the geometric model of the upper platform, and based on the geometric model of the upper platform and the target attitude of the feed cabin, calculate the target length of the steel cable of the upper platform.

[0031] For example, the coordinate data of the tower end point in the ground coordinate system and the coordinate data of the connection point at the bottom of the feed cabin in the cabin coordinate system are obtained and used as the coordinates of the tower end point and the feed cabin end point, respectively. Based on the coordinates of the tower end point and the feed cabin end point, a geometric model of the upper platform is established. Based on the orientation matrix of the geometric model of the upper platform, the target attitude of the feed cabin is transformed from the body coordinate system to the ground coordinate system to obtain the transformed target attitude parameters of the feed cabin. Based on the transformed target attitude parameters of the feed cabin, the spatial length of each steel cable is calculated to obtain the target length of the steel cable.

[0032] Step S104: Based on the target length of the steel cable and the dynamic model of the upper platform, adjust the actual length of each steel cable to obtain the actual attitude data of the feed cabin.

[0033] Based on the mass matrix, damping ratio, natural frequency, and driving force of the steel cables, a dynamic model of the upper platform is established. Based on the target length of the steel cables and the dynamic model of the upper platform, an extended state observer in the active disturbance rejection control algorithm is used to estimate external disturbances and system uncertainties in real time, which are then used as the observation results of the steel cables. Based on the observation results of the steel cables, the control quantity of the steel cables is calculated, and the length of each steel cable is adjusted based on the control quantity of the steel cables to obtain the actual length of each steel cable. The actual length of each steel cable is substituted into the inverse kinematics model of the platform to calculate the actual attitude data of the feed cabin in the ground coordinate system.

[0034] Step S106: Based on the actual attitude data of the feed cabin and the geometric model of the lower platform, calculate the ideal pose of the feed, and calculate the target length of the telescopic rod of the lower platform based on the ideal pose.

[0035] The actual attitude data of the feed cabin is input into the geometric model of the lower platform to determine the spatial positional relationship between the feed plane and the bottom plane of the feed cabin. Based on the parallel constraint conditions between the feed plane and the bottom plane of the feed cabin, the ideal pose of the feed is determined. Based on the ideal pose, the spatial connection length of the telescopic rod of the lower platform is calculated as the target length of the telescopic rod.

[0036] Step S108: Adjust the actual length of each telescopic rod based on the target length of the telescopic rod to obtain the actual attitude data of the feed source, and adaptively adjust the control parameters of the upper platform and the lower platform based on the actual attitude data of the feed source to achieve the positioning control of the feed source.

[0037] First, the actual lengths of each telescopic rod are adjusted based on the target length of the telescopic rod to obtain the actual attitude data of the feed. For example, a dynamic model of the lower platform is established based on the mass matrix, damping ratio, natural frequency, and driving force of the telescopic rod. Based on the target length of the telescopic rod and the dynamic model of the lower platform, the extended state observer in the active disturbance rejection control algorithm is used to estimate external disturbances and system uncertainties in real time to obtain the telescopic rod observation results. The telescopic rod control quantity is calculated based on the telescopic rod observation results, and the length of each telescopic rod is adjusted based on the telescopic rod control quantity to obtain the actual length of each telescopic rod. The actual lengths of each telescopic rod are substituted into the inverse kinematic model of the lower platform to calculate the actual attitude data of the feed in the ground coordinate system.

[0038] Next, based on the actual attitude data of the feed source, the control parameters of the upper platform and the lower platform are adaptively adjusted to achieve the positioning control of the feed source. For example, the actual attitude data of the feed source is compared with its ideal attitude data to obtain an attitude error signal; based on the attitude error signal, the control parameters of the upper platform and the lower platform are adaptively adjusted to achieve the positioning control of the feed source.

[0039] This application also provides a positioning control method for a Mars landing process verification system, applied on a dual-platform system. The system includes an upper platform and a lower platform. The upper platform consists of six towers, a feed cabin, and six steel cables connecting the towers and the feed cabin. Coarse positioning of the feed cabin in the geodetic coordinate system is achieved by controlling the length of the steel cables. The lower platform consists of the feed cabin, the feed, and six rods connecting the feed cabin and the feed, used to achieve fine positioning of the feed in the feed cabin's coordinate system.

[0040] like Figure 2 As shown, the positioning control method includes the following steps:

[0041] Step S202: Establish the geometric model of the upper platform.

[0042] like Figure 3 As shown, the apex of the six pillars is A. i Let i = 1, 2, ..., 6. Assume these six points lie on a plane and are distributed on a circle centered at A. Consider the plane containing these six points as a fixed surface of a platform. Let C be the six connection points between the feed cabin circumference and the tower column. i The center of the feed cabin is C. There are six points P on the feed circumference. i With the six points B on the circumference of the feed cabin i Connected. The center of the feed source is P.

[0043] The coordinate system at the vertices of the six tower pillars is set as the geodetic coordinate system. The origin O of the geodetic coordinate system Oxyz coincides with A. XO is perpendicular to A1A6, and the angle between OA1 and OA2 is... .

[0044] The body coordinates of the circle containing the feed cabin are O2x2y2z2, with the origin O2 coinciding with point C. X2O2 is perpendicular to C1C6, and the angle between O2C1 and O2C2 is... The angles between O2C1 and O2C3, and between O2C3 and O2C5 are all 120 degrees. The angles between O2C2 and O2C4, O2C4 and O2C6, and O2B are also 120 degrees. i With O2C i The included angle is .

[0045] The feed source is located in the body coordinate system O3x3y3, with the origin O3 coinciding with P. X3O3 is perpendicular to P1P6, and the angle between O3P1 and O3P2 is... The angles between O3P1 and O3P3, O3P3 and O3P5, O3P2 and O3P4, and O3P4 and O3P6 are all 120 degrees. Let OX and OA be... i O2X2 and O2C i O3X3 and O3P i The included angles are respectively , and Among them, A i B i C i and P i The coordinates are as follows:

[0046]

[0047] in, , and These represent the tower column, the feed cabin, and the radius of the circumference where the feed is located, respectively.

[0048] Step S204: Establish a dynamic model.

[0049] First, determine the ideal pose of the feed cabin corresponding to the ideal pose of the feed. The two are related through the fixed geometry of the lower platform, which is a fixed homogeneous transformation matrix determined by the installation position of the lower platform on the feed cabin and the geometry of the feed itself.

[0050] Geodetic coordinate system Next, solve for the vector of the steel cable connecting the top of the tower column and the feed connection point. Vector Representation in the geodetic coordinate system is =[xyz] T subscript Represented in a geodetic coordinate system. Vector It can be expressed by the following formula:

[0051]

[0052] in:

[0053]

[0054]

[0055]

[0056]

[0057] in To be The coordinate transformation to a coordinate system The direction cosine matrix of the mid-coordinate. Vector. length It can be expressed by the following formula:

[0058] or

[0059]

[0060] According to geometric constraints:

[0061]

[0062]

[0063] Based on the orthogonality of the direction cosine matrix:

[0064]

[0065] as well as:

[0066]

[0067]

[0068]

[0069] Simplifying, we get:

[0070]

[0071] The above equation provides the solution to the inverse kinematics problem, which can be used to calculate the required length in practice. ( The geodetic coordinate system is obtained by rotating the body coordinate system three times. The direction matrix obtained by the three-rotation method is:

[0072]

[0073] Step S206: Solve the dynamic model.

[0074] Define the equation:

[0075]

[0076] Where, vector Defined as:

[0077]

[0078] Use the following methods to find vectors Choose an initial value ; calculate using the formula for the direction matrix above elements , ; calculate using the vector formula above , ; calculate using the formula of the equation defined above. and , After that, calculate ,if Stop iteration and with As a solution; otherwise, solve the system of linear equations. , ;if ,Will As a solution; take Repeat the above steps.

[0079] In another embodiment, the forward problem can be defined as a nonlinear least squares optimization problem, and solved using a two-stage hybrid strategy. The first stage uses the CMA-ES algorithm to search within a large range of pose uncertainty to locate the global optimum. The second stage uses the CMA-ES solution as the initial value and switches to an improved regularized LM algorithm for accurate and fast convergence.

[0080] Specifically, in the first stage, the solution to the original six equations is transformed into minimizing a total residual objective function. A normalized distance difference function can be used to improve accuracy.

[0081]

[0082] By normalizing the process, the objective function becomes less sensitive to changes in the length scale of various steel cables, thus improving the numerical stability of the optimization.

[0083] Next, CMA-ES is applied to adaptively update the covariance matrix of the search distribution to effectively navigate the complex search space. Traditional methods rely on an initial setting close to the true solution, while CMA-ES starts the search from a larger initial distribution, not relying on precise initial guesses. This significantly reduces reliance on prior knowledge. During execution, it operates within a set maximum number of iterations or when the objective function value falls below a certain lenient threshold. CMA-ES continues to run during this time. Its output... As the initial value for the next stage.

[0084] In the second stage, local refinement is performed based on regularized LM. Starting at point , the LM algorithm is used for fast local convergence. The LM algorithm is an improvement on the Gauss-Newton method, and its update equation is:

[0085]

[0086] in, It is an equation The Jacobian matrix. It is the damping factor. It is the residual vector. This application uses an adaptive regularization term. Replace the simple identity matrix in the LM equation : , where the regularization matrix It is a diagonal matrix whose diagonal elements With the current solution The uncertainty in the -th degree of freedom is inversely proportional. Using the covariance matrix C obtained at the end of the CMA-ES stage, where C reflects the algorithm's estimate of the uncertainty of the solution in the search space, let:

[0087]

[0088] In the CMA-ES stage, a certain degree of freedom (e.g., rotation about the Z-axis) If the exploration is very certain, then in the LM stage, the step in that direction... The first stage of the algorithm is subject to weaker constraints, allowing for larger update steps. Conversely, the second stage, with its more uncertain direction, is subject to stronger constraints, resulting in smaller update steps. This method quantitatively injects the global exploration knowledge from the first stage into the local search of the second stage, enabling the algorithm to converge more intelligently and stably.

[0089] Step S208: Determine the ideal pose.

[0090] Point on the circumference of the bottom surface of the feed cabin and feed point Connected, and at this time The included angle is The radius of the circle containing the feed source is... The ideal feed pose is ,but In coordinate system The coordinates on are:

[0091]

[0092] Point on the feed plane ideal point The coordinates in the geodetic coordinate system are:

[0093]

[0094] Pass Find the center of the feed compartment bottom plane on a vertical line perpendicular to the ideal feed plane. Ideal location , its in The coordinates on are ,but .

[0095] On the bottom plane of the feed compartment, point ideal value exist The coordinates on are:

[0096] Its coordinates in the geodetic coordinate system are:

[0097]

[0098] in:

[0099]

[0100] Right now,

[0101]

[0102] Feed cabin center The ideal coordinates in the geodetic coordinate system are:

[0103]

[0104] Step S210: Perform positioning control.

[0105] The positioning control system consists of an upper platform cable control subsystem and a lower platform telescopic boom control subsystem. The upper platform is mainly used for coarse positioning of the feed cabin in the ground coordinate system, while the lower platform is mainly used for fine positioning of the feed in the feed cabin coordinate system. The two systems exchange data in real time through attitude feedback and pose calculation modules, forming a dual closed-loop control structure: the outer loop (position loop) macroscopically adjusts the length of the upper platform cable by observing and correcting the attitude error of the feed cabin; the inner loop (attitude loop) dynamically fine-tunes the length of the lower platform telescopic boom through precise attitude feedback from the feed, achieving high-precision positioning.

[0106] First, for the upper platform, each steel cable is controlled independently. The length error is calculated by comparing the target length with the actual length of the cable, and this error is input into a tracking differentiator for smoothing, thus obtaining the rate of change of the error. Subsequently, an extended state observer (ESO) is used to estimate the unknown dynamic model of the system and external disturbances in real time, treating these unknown disturbances as additional states for observation and compensation. In this way, the control system can automatically counteract external disturbances and system uncertainties, achieving precise adjustment of the cable length, thereby gradually bringing the overall attitude of the feed cabin closer to the target attitude.

[0107] Secondly, for the lower platform, the control method for the telescopic booms is similar to that of the upper platform, but the impact of dynamic changes in the feed cabin's attitude on the feed's pose needs to be considered. First, the target length of the telescopic boom is calculated based on the feed's target pose, and then the actual length is compared with the target length for error. Uncertainties and disturbances are estimated using an extended state observer, and nonlinear feedback control is used to finely adjust each telescopic boom. Simultaneously, attitude coupling compensation is introduced, feeding back the feed cabin's attitude change information to the lower platform controller in real time to correct the boom length control, ensuring high-precision positioning of the feed in the feed cabin's coordinate system.

[0108] Furthermore, a dual-closed-loop control structure is formed between the upper and lower platforms. The outer loop calculates the error vector based on the difference between the actual and ideal pose of the feed and feeds it back to the controllers of the upper and lower platforms to adjust control parameters and achieve adaptive control. The inner loop precisely adjusts the length of the steel cable and telescopic rod to execute specific actions. Through this coordination mechanism, the feed can converge quickly under dynamic disturbances and external interference, maintaining a stable position and attitude.

[0109] The specific control methods will be described below.

[0110] The platform's dynamic model is as follows:

[0111]

[0112] in This represents the vector of the elongation length of the steel cable on the upper platform. Indicates driving force. Represents the mass matrix, and for and A nonlinear function matrix.

[0113] This application adopts an independent control strategy for the six steel cables, and the dynamic equation of each steel cable is expressed by a second-order system as follows:

[0114]

[0115] in, No. The length of the steel cable, and They represent The damping ratio and natural frequency, Indicates external interference. Indicates uncertainty. To control the input, The equivalent gain coefficient, It is the equivalent moment of inertia.

[0116] The dynamic equations for each rod on the lower platform can be expressed as a second-order system as follows:

[0117]

[0118] in For the first The length of the root rod, and They represent The damping ratio and natural frequency, Indicates external interference. Indicates uncertainty. To control the input, The equivalent gain coefficient, It is the equivalent moment of inertia.

[0119] For the above nonlinear uncertain model, the following controls are implemented:

[0120] 1) Tracking Differentiator

[0121]

[0122] in and For state variables, For input signal, Step size, For design parameters. Function. The definition is as follows:

[0123]

[0124] 2) Extended State Observer

[0125] The dynamic equations for each steel cable are rewritten as follows:

[0126]

[0127] in ,function

[0128]

[0129] unknown dynamic model As an extended state of the system:

[0130] Using the extended state observer proposed above, the state of the above system can be estimated in real time.

[0131]

[0132] The unknown parts of the feedback system can be automatically compensated for:

[0133]

[0134] Finally, a simple control of a system with two integrators in series:

[0135]

[0136] in To control the input.

[0137] 3) Nonlinear control law

[0138] For the compensated system, design a nonlinear feedback law:

[0139]

[0140] Through the above control methods, the upper platform achieves coarse positioning of the feed cabin, and the lower platform achieves fine positioning of the feed. At the same time, the controller can adaptively compensate for unknown disturbances, achieving high-precision and high-robust positioning control.

[0141] This application also provides another positioning control method for a Mars landing process verification system. The main difference between this method and the above embodiments lies in the different positioning control steps. Therefore, this embodiment will describe the positioning control steps in detail, while other steps will not be repeated.

[0142] The method provided in this embodiment retains the real-time estimation and compensates for the total disturbance, but restructures its architecture. A local adaptive controller is designed for each actuator (cable / telescopic rod), while a global model predictive controller is introduced on the upper platform for collaborative optimization. The lower platform employs fine-tuning based on a disturbance observer, forming a composite control architecture.

[0143] like Figure 4 As shown, the adaptive active disturbance rejection composite control method based on the model predictive control framework provided in this embodiment includes the following steps:

[0144] Step S402: Construct an extended state observer based on parameter adaptation.

[0145] Traditional ESO parameters are fixed, but for parameters like those of FAST cables, which are time-varying (such as equivalent inertia)... Damping For systems whose pose changes, the observation performance will decrease.

[0146] The original system Reconstructed as:

[0147]

[0148] in, , , This is the regression vector. This is the linear parameter vector to be identified online. It is the residual, truly unknown perturbation after parameter adaptation, which is estimated by ESO. ,in It is also used as a slow time-varying parameter for online estimation.

[0149] Step S404: Construct the parameter adaptive law.

[0150] Extended State Observer with Adaptive Parameters:

[0151]

[0152] Simultaneously, the parameters are updated online using either gradient descent or recursive least squares methods.

[0153]

[0154] This application's embodiments no longer combine the entire linear and nonlinear models into a single total disturbance for estimation; instead, they separate the time-varying linear parameters for online identification. This makes the ESO estimation... The dynamic changes are slower and the amplitude is smaller, which greatly improves the estimation accuracy and convergence speed of ESO.

[0155] Step S406: Collaborative optimization on the platform.

[0156] Traditional independent control strategies neglect the dynamic coupling between cables. The method provided in this embodiment introduces an upper-level MPC coordinator based on local disturbance compensation using A-ESO.

[0157] The MPC prediction model utilizes the state estimate provided by A-ESO. and parameter estimation To build a centralized linear time-varying (LTV) prediction model for the entire platform:

[0158]

[0159] in , .matrix Estimated parameters of each channel constitute. It is composed of each channel The disturbance compensation term constitutes the disturbance compensation term.

[0160] In each control cycle, MPC solves the following finite-time optimization problem:

[0161]

[0162]

[0163]

[0164] in, This is the control sequence to be optimized. and It is the prediction time domain and the control time domain.

[0165] The first element of the optimal control sequence obtained by MPC As the feedforward control variable, the final cooperative control law is:

[0166]

[0167] in The active disturbance rejection control quantity (i.e., the active disturbance rejection control quantity calculated from each local A-ESO and the nonlinear feedback law) is... ).

[0168] In this embodiment, the MPC is optimized to actively coordinate the movement of the six steel cables, avoiding the pulling phenomenon that may occur due to independent control, and can significantly suppress overshoot.

[0169] Step S408: Compensate the lower platform based on the interference observer.

[0170] The lower platform, serving as a fine-tuning platform, is more sensitive to high-frequency dynamics and modeling errors. Within the lower platform, a DOB (Domain-Oriented Object) is embedded after the nonlinear feedback law and before the object. The core of the DOB is a nominal model. It can be a simple dual integrator. DOB estimates and compensates for total disturbances, including residual perturbations, by comparing the actual output with the inverse of the nominal model output.

[0171]

[0172] in, , It is a low-pass filter. ESO is used to estimate and compensate for low-frequency, wide-range, slow time-varying disturbances and unmodeled dynamics, while DOB is specifically used to suppress high-frequency unmodeled dynamics and measurement noise. The two complement each other in the frequency domain, together forming a full-band disturbance suppression system, enabling the lower platform to achieve higher control bandwidth and accuracy than traditional suppression techniques.

[0173] In this embodiment, firstly, a parameter-adaptive extended state observer is constructed to estimate the local state and disturbances of each actuator. The model is reconstructed to include a linear parameter vector to be identified online and residual disturbances. Then, based on the observation error of the extended state observer, a parameter-adaptive law is used to update the linear parameter vector and control gain online to separate and identify the time-varying linear dynamics of the system. Next, based on the state and parameter estimates of each actuator, a centralized linear time-varying predictive model is constructed for the upper platform. A model predictive controller is used to calculate the collaboratively optimized feedforward control quantity by solving a finite-time domain optimization problem. Based on the control quantity, the control parameters of the upper and lower platforms are adaptively adjusted to achieve feedforward localization control. Through this method, more accurate feedforward localization control can be achieved.

[0174] This application also provides a positioning control device for a Mars landing process verification system, such as... Figure 5As shown, the system includes: a cable length determination module 52, configured to establish a geometric model of the upper platform based on the coordinates of the tower end point and the feed cabin end point, and to calculate the target cable length of the upper platform based on the geometric model of the upper platform and the target attitude of the feed cabin; an adjustment module 54, configured to adjust the actual length of each cable based on the target cable length and the dynamic model of the upper platform to obtain the actual attitude data of the feed cabin; a telescopic rod length determination module 56, configured to calculate the ideal attitude of the feed based on the actual attitude data of the feed cabin and the geometric model of the lower platform, and to calculate the target length of the telescopic rod of the lower platform based on the ideal attitude; and a positioning control module 58, configured to adjust the actual length of each telescopic rod based on the target length of the telescopic rod to obtain the actual attitude data of the feed, and to adaptively adjust the control parameters of the upper platform and the lower platform based on the actual attitude data of the feed to achieve the positioning control of the feed.

[0175] It should be noted that the positioning control device of the Mars landing process verification system 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 positioning control device of the Mars landing process verification system provided in the above embodiments and the positioning control method of the Mars landing process verification system belong to the same concept. The specific implementation process is detailed in the method embodiment and will not be repeated here.

[0176] 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.

[0177] 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.

[0178] 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.

[0179] 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 positioning control method for a Mars landing process verification system, characterized in that, include: Based on the coordinates of the tower end point and the feed cabin end point, a geometric model of the upper platform is established, and based on the geometric model of the upper platform and the target attitude of the feed cabin, the target length of the steel cable of the upper platform is calculated. Based on the target length of the steel cable and the dynamic model of the upper platform, the actual length of each steel cable is adjusted to obtain the actual attitude data of the feed cabin. Based on the actual attitude data of the feed cabin and the geometric model of the lower platform, the ideal pose of the feed is calculated, and the target length of the telescopic rod of the lower platform is calculated based on the ideal pose. Based on the target length of the telescopic rod, the actual length of each telescopic rod is adjusted to obtain the actual attitude data of the feed source. Based on the actual attitude data of the feed source, the control parameters of the upper platform and the lower platform are adaptively adjusted to achieve the positioning control of the feed source.

2. The method according to claim 1, characterized in that, Based on the coordinates of the tower end point and the feed cabin end point, a geometric model of the upper platform is established. Based on the geometric model of the upper platform and the target attitude of the feed cabin, the target length of the steel cable of the upper platform is calculated, including: The coordinate data of the tower end point in the ground coordinate system and the coordinate data of the connection point at the bottom of the feed cabin in the cabin coordinate system are obtained and used as the coordinates of the tower end point and the feed cabin end point, respectively. The geometric model of the upper platform is established based on the coordinates of the tower end point and the feed cabin end point. Based on the orientation matrix of the geometric model of the upper platform, the target attitude of the feed cabin is transformed from the body coordinate system to the ground coordinate system to obtain the transformed target attitude parameters of the feed cabin. Based on the transformed target attitude parameters of the feed cabin, the spatial length of each steel cable is calculated to obtain the target length of the steel cable.

3. The method according to claim 1, characterized in that, Based on the target length of the steel cables and the dynamic model of the upper platform, the actual lengths of each steel cable are adjusted to obtain the actual attitude data of the feed cabin, including: A dynamic model of the upper platform is established based on the mass matrix, damping ratio, natural frequency, and driving force of the steel cable. Based on the target length of the steel cable and the dynamic model of the upper platform, the extended state observer in the active disturbance rejection control algorithm is used to estimate the external disturbances and system uncertainties in real time, which are then used as the observation results of the steel cable. Based on the observed results of the steel cables, the control quantity of the steel cables is calculated, and the length of each steel cable is adjusted based on the control quantity of the steel cables to obtain the actual length of each steel cable; Substitute the actual lengths of each steel cable into the inverse kinematics model of the platform to calculate the actual attitude data of the feed cabin in the ground coordinate system.

4. The method according to claim 1, characterized in that, Based on the actual attitude data of the feed cabin and the geometric model of the lower platform, the ideal pose of the feed is calculated, and based on the ideal pose, the target length of the telescopic rod of the lower platform is calculated, including: The actual attitude data of the feed cabin is input into the geometric model of the lower platform to determine the spatial positional relationship between the feed plane and the bottom plane of the feed cabin, and the ideal pose of the feed is determined based on the parallel constraint conditions between the feed plane and the bottom plane of the feed cabin. Based on the ideal pose, the spatial connection length of the telescopic rod of the lower platform is calculated and used as the target length of the telescopic rod.

5. The method according to claim 1, characterized in that, Based on the target length of the telescopic rod, the actual length of each telescopic rod is adjusted to obtain the actual attitude data of the feed source, including: A dynamic model of the lower platform is established based on the mass matrix, damping ratio, natural frequency, and driving force of the telescopic rod. Based on the target length of the telescopic pole and the dynamic model of the lower platform, the extended state observer in the active disturbance rejection control algorithm is used to estimate the external disturbance and system uncertainty in real time, and the telescopic pole observation results are obtained. The telescopic pole control amount is calculated based on the observation results of the telescopic pole, and the length of each telescopic pole is adjusted based on the telescopic pole control amount to obtain the actual length of each telescopic pole; Substitute the actual lengths of each telescopic rod into the inverse kinematics model of the lower platform to calculate the actual attitude data of the feed source in the ground coordinate system.

6. The method according to claim 1, characterized in that, Based on the actual attitude data of the feed source, the control parameters of the upper platform and the lower platform are adaptively adjusted to achieve the positioning control of the feed source, including: The actual attitude data of the feed source is compared with its ideal attitude data to obtain the attitude error signal; The control parameters of the upper platform and the lower platform are adaptively adjusted based on the attitude error signal to achieve positioning control of the feed source.

7. A positioning control device for a Mars landing process verification system, characterized in that, include: The cable length determination module is configured to establish a geometric model of the upper platform based on the coordinates of the tower end point and the feed cabin end point, and to calculate the target length of the cable of the upper platform based on the geometric model of the upper platform and the target attitude of the feed cabin. The adjustment module is configured to adjust the actual length of each steel cable based on the target length of the steel cable and the dynamic model of the upper platform to obtain the actual attitude data of the feed cabin. The telescopic boom length determination module is configured to calculate the ideal pose of the feed based on the actual attitude data of the feed cabin and the geometric model of the lower platform, and to calculate the target length of the telescopic boom of the lower platform based on the ideal pose. The positioning control module is configured to adjust the actual length of each telescopic rod based on the target length of the telescopic rod to obtain the actual attitude data of the feed source, and to adaptively adjust the control parameters of the upper platform and the lower platform based on the actual attitude data of the feed source to achieve positioning control of the feed source.

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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