A method, system, medium, and device for controlling rigid body motion in ocean currents.

Abstract

This application provides a method, system, medium, and device for controlling rigid body motion in ocean currents, including: acquiring ocean current data and constructing a layered fluid velocity model based on the ocean current data; obtaining the motion equations of a target rigid body located in the ocean current; the motion equations include translational and rotational equations; determining discrete Lagrange points on the surface of the rigid body based on the motion equations; each Lagrange point contains position information, surface force, and normal vector; discretizing the fluid domain corresponding to the layered fluid velocity model using a Cartesian grid of a set resolution, setting a boundary layer for refinement, and obtaining a fluid grid; the grid nodes of the fluid grid are used to store fluid velocity and pressure; calculating the surface force in the fluid grid and the Lagrange points through interpolation functions, and outputting the motion parameters of the target rigid body upon convergence. This application avoids the need for frequent mesh reconstruction due to the complex shape and large displacement motion of the rigid body, thus avoiding the numerical instability problem caused by mesh distortion in traditional methods.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of deep-sea mining, and in particular to a rigid body motion control method, system, medium and device in ocean current. BACKGROUND

[0002] Currently, deep-sea towed platforms need to withstand ocean current disturbance, tow force fluctuation and other multiple loads. The traditional fluid-solid coupling method (such as ALE method) used in the prior art has low calculation efficiency when dealing with large displacement motion of rigid bodies, and is difficult to handle complex boundary motion. Moreover, the disturbance influence of deep-sea stratified ocean current on the posture of the towed body is not fully considered, and there is also a lack of collaborative modeling of the rigid motion of the towed body and fluid friction and inertial effect. Therefore, how to precisely control the motion of a rigid body in the deep sea is a technical problem that needs to be solved by those skilled in the art. SUMMARY

[0003] The purpose of the present application is to provide a rigid body motion control method, system, computer readable storage medium and electronic device in ocean current, which can accurately calculate the motion tendency of a rigid body in ocean current, thereby effectively realizing rigid body weight adjustment or motion parameter adjustment, and realizing precise motion control of the rigid body.

[0004] To solve the above technical problems, the present application provides a rigid body motion control method in ocean current, and the specific technical solutions are as follows:

[0005] Obtain ocean current data, and construct a stratified fluid velocity model based on the ocean current data;

[0006] Obtain a motion equation of a target rigid body located in the ocean current; the motion equation includes a translation equation and a rotation equation;

[0007] Determine a Lagrange point discretized on the surface of the rigid body based on the motion equation; each Lagrange point contains position information, surface force and normal vector;

[0008] Discretize the fluid domain corresponding to the stratified fluid velocity model using a Cartesian grid with a set resolution, and set a boundary layer encryption to obtain a fluid grid; the grid nodes of the fluid grid are used to store fluid velocity and pressure;

[0009] Couple the surface force in the fluid grid and the Lagrange point through an interpolation function, and output the motion parameters of the target rigid body when convergence is achieved; the motion parameters are used to guide the target weight or motion control parameters of the target rigid body.

[0010] Optionally, the obtaining of the motion equation of the target rigid body located in the ocean current comprises:

[0011] Obtain a three-dimensional model of the target rigid body;

[0012] The translation equations are determined based on the rigid body mass, rigid body center of mass velocity vector, fluid forces, gravitational acceleration, buoyancy, and fluid resistance contained in the three-dimensional model.

[0013] The rotation equation is determined based on the moment of inertia tensor, rigid body angular velocity vector, fluid torque, and control torque.

[0014] Optionally, obtaining the three-dimensional model of the target rigid body includes:

[0015] A three-dimensional model of the target rigid body is established, and the rigid body parameters of the target rigid body are set; the rigid body parameters include length, weight, and buoyancy;

[0016] Accordingly, determining the discrete Lagrange points of the rigid body surface based on the equations of motion includes:

[0017] Based on the equation of motion and the rigid body parameters, the surface of the target rigid body is discretized into Lagrange points.

[0018] Optionally, after obtaining the equations of motion for the target rigid body located in the ocean current, the process also includes:

[0019] The rigid body attitude of the target rigid body is updated using the quaternion method based on the equation of motion.

[0020] The discrete Lagrange points on the rigid body surface are recalculated based on the updated rigid body attitude.

[0021] Optionally, the calculation of the surface forces in the fluid mesh and the Lagrange point by coupling the interpolation function includes:

[0022] The surface forces are distributed to adjacent fluid mesh nodes using a discrete function;

[0023] The four-point interpolation kernel function is invoked to cover the surface force with the four grid nodes around each Lagrange point;

[0024] The fluid velocity is interpolated to the Lagrange point, and the position of the target rigid body is updated.

[0025] The coupled calculation continues until convergence, at which point the motion parameters of the target rigid body are output.

[0026] Optionally, when constructing a stratified fluid velocity model based on the ocean current data, the method further includes:

[0027] A spatiotemporal perturbation function is generated using Gaussian white noise; the spatiotemporal perturbation function is used to simulate the turbulence effect in the ocean current.

[0028] Optionally, interpolating the fluid velocity to the Lagrange point and updating the position of the target rigid body includes:

[0029] The mesh nodes in the fluid mesh are used as communication nodes. Multi-node communication is used to interpolate the fluid velocity to the Lagrange point and update the position of the target rigid body.

[0030] Accordingly, interpolating the fluid velocity to the Lagrange point and updating the position of the target rigid body includes:

[0031] The graphics processor is invoked to interpolate the fluid velocity to the Lagrange point and output the updated position of the target rigid body.

[0032] This application also provides a rigid body motion control system in ocean currents, including:

[0033] The flow splitting model construction module is used to acquire ocean current data and construct a layered fluid velocity model based on the ocean current data.

[0034] The rigid body motion calculation module is used to obtain the motion equations of a target rigid body located in an ocean current; the motion equations include translational equations and rotational equations.

[0035] A rigid body surface discretization module is used to determine discrete Lagrange points on the rigid body surface based on the equation of motion; each Lagrange point contains position information, surface forces, and a normal vector;

[0036] The fluid network generation module is used to discretize the fluid domain corresponding to the layered fluid velocity model using a Cartesian grid of a set resolution, set a boundary layer for refinement, and obtain a fluid grid; the grid nodes of the fluid grid are used to store fluid velocity and pressure.

[0037] A motion parameter output module is used to calculate the surface forces in the fluid mesh and the Lagrange point through interpolation function coupling, and outputs the motion parameters of the target rigid body upon convergence; the motion parameters are used to guide the target counterweight or motion control parameters of the target rigid body. This application also provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the steps of the method described above.

[0038] This application also provides an electronic device, including a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the method described above when it invokes the computer program in the memory.

[0039] This application provides a method for rigid body motion control in ocean currents, comprising: acquiring ocean current data and constructing a layered fluid velocity model based on the ocean current data; acquiring the motion equations of a target rigid body located in the ocean current; the motion equations include translational equations and rotational equations; determining discrete Lagrange points on the surface of the rigid body based on the motion equations; each Lagrange point contains position information, surface force, and normal vector; discretizing the fluid domain corresponding to the layered fluid velocity model using a Cartesian grid of a set resolution, setting a boundary layer for refinement, and obtaining a fluid grid; the grid nodes of the fluid grid are used to store fluid velocity and pressure; calculating the surface force in the fluid grid and the Lagrange points through interpolation function coupling, and outputting the motion parameters of the target rigid body upon convergence; the motion parameters are used to guide the target weight or motion control parameters of the target rigid body.

[0040] This application constructs a layered fluid velocity model based on actual ocean current data, accurately reflecting the true velocity and characteristics of ocean currents at different depths in the deep-sea environment. By combining this with rigid body motion equations considering translation and rotation, and determining discrete Lagrange points on the rigid body surface, subsequent analysis of the target rigid body's motion in the ocean current becomes more accurate and detailed, effectively reducing the prediction error of the towed body's attitude angle and providing more reliable simulation results. Simultaneously, a Cartesian grid is used to discretize the fluid domain, and a boundary layer is set for refinement. An interpolation function couples the fluid grid with the surface forces at the Lagrange points, eliminating the need for frequent mesh reconstruction due to the complex shape and large displacement of the rigid body. This avoids the numerical instability caused by mesh distortion in traditional methods and better handles the interaction between fluid and rigid body under complex boundary conditions. The motion parameters of the target rigid body are output upon convergence. Compared to traditional calculation methods, this effectively improves computational efficiency, reduces computational resource consumption, and can solve large-scale, complex fluid-rigid body coupling problems within a reasonable timeframe, making it more suitable for the computational efficiency requirements of practical engineering scenarios.

[0041] This application also provides a rigid body motion control system, a computer-readable storage medium, and an electronic device in ocean currents, which have the above-mentioned beneficial effects, and will not be elaborated here. Attached Figure Description

[0042] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of this application. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0043] Figure 1 A flowchart of a rigid body motion control method in ocean currents provided as an embodiment of this application;

[0044] Figure 2 A schematic diagram of a rigid body motion control system in an ocean current provided in an embodiment of this application;

[0045] Figure 3 This is a schematic diagram of an electronic device structure provided in an embodiment of this application. Detailed Implementation

[0046] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0047] Please refer to Figure 1 , Figure 1 A flowchart of a rigid body motion control method in ocean currents provided in this application embodiment, the method comprising:

[0048] S101: Acquire ocean current data and construct a layered fluid velocity model based on the ocean current data;

[0049] S102: Obtain the equations of motion for the target rigid body located in the ocean current; the equations of motion include translational and rotational equations.

[0050] S103: Determine discrete Lagrange points on the rigid body surface based on the equation of motion; each Lagrange point contains position information, surface forces, and a normal vector;

[0051] S104: Discretize the fluid domain corresponding to the layered fluid velocity model using a Cartesian grid of a set resolution, set a boundary layer for refinement, and obtain a fluid grid; the grid nodes of the fluid grid are used to store fluid velocity and pressure;

[0052] S105: The surface forces in the fluid mesh and the Lagrange point are calculated by interpolation function coupling, and the motion parameters of the target rigid body are output upon convergence; the motion parameters are used to guide the target counterweight or motion control parameters of the target rigid body.

[0053] The motion of the fluid is described by the Navier-Stokes equations. Let the fluid velocity field be... The density of the fluid is The pressure is The fluid viscosity is External disturbance force is For incompressible fluids, the Navier-Stokes equations are:

[0054] ;

[0055] Inlet: Layered flow rate input;

[0056] Export: Pressure export;

[0057] Rigid body surface: No-slip wall, with boundary forces applied via IBM.

[0058] To adapt to the complex deep-sea environment, ocean currents not only experience external disturbances but also need to consider the stratification effect of current velocities at different depths. In the deep sea, ocean currents are typically divided into multiple distinct layers, each with varying current velocities and turbulence intensities. Therefore, fluid velocity can be represented using a stratification model:

[0059] ;

[0060] in, This is the velocity distribution in layer ii. It is a time- and space-based perturbation function used to represent ocean current dynamics in different hydrospheres.

[0061] The motion of the dragged body is precisely described by the Newton-Euler equations:

[0062] The translational equation, according to Newton's second law, is driven by a net external force. Therefore, the translational equation can be determined based on the rigid body mass, the rigid body's center of mass velocity vector, fluid forces, gravitational acceleration, buoyancy, and fluid resistance contained in the three-dimensional model. The formula is as follows:

[0063] ;

[0064] Where m is the mass of the rigid body (unit: kg); v is the velocity vector of the center of mass of the rigid body (unit: m / s).

[0065] For fluid forces, calculated by integrating pressure and shear force (unit: N);

[0066] =mg, representing gravity (unit: N). .

[0067] = Buoyancy (unit: N) Where is the fluid density and V is the drainage volume.

[0068] = , where represents fluid resistance (unit: N), Cd is the drag coefficient, A is the reference area, and M is the mass of the towing body.

[0069] The rotation equations are determined based on the moment of inertia tensor, the rigid body angular velocity vector, the fluid torque, and the control torque.

[0070] ;

[0071] Where I: moment of inertia tensor (unit: kg·m²), a diagonal matrix in the principal axis coordinate system:

[0072] ;

[0073] : Rigid body angular velocity vector (unit: rad / s);

[0074] Fluid torque, calculated by integrating surface pressure and shear torque (unit: N·m);

[0075] Control torque (such as ballast adjustment torque), for example, proportional control:

[0076] ;

[0077] in, This is the proportionality coefficient (unit: N·m / rad). This represents the attitude angle deviation.

[0078] In one feasible implementation, to avoid the gimbal lock problem of Euler angles, the rigid body attitude of the target rigid body can be updated using the quaternion method based on the motion equations, thereby recalculating the discrete Lagrange points on the rigid body surface based on the updated rigid body attitude:

[0079] ;

[0080] Here is the angular velocity matrix:

[0081] ;

[0082] In the numerical solution, this embodiment employs the Immersed Boundary Method (IBM) to achieve rigid-body-fluid coupling. The Immersed Boundary Method is a numerical method for handling the interaction between fluid and rigid body. It embeds the influence of the rigid body boundary into the fluid equations through virtual force source terms, eliminating the need for dynamic adjustment of the fluid mesh. The specific steps are as follows:

[0083] Step 1: Discretization of the fluid domain: Discretize the fluid domain using a fixed Cartesian grid (Eulerian grid);

[0084] Step 2: Discretization of rigid body boundaries: Discretize the rigid body surface into Lagrangian points.

[0085] Step 3, Force and Displacement Transmission: Achieve bidirectional coupling between rigid body surface forces and fluid mesh through interpolation functions.

[0086] When generating fluid meshes, a uniform Cartesian mesh is used for the fluid domain, with a typical resolution of Δx=Δy=Δz=0.1m. The mesh nodes store the fluid velocity. and pressure .

[0087] When calculating the discretization of a rigid body surface, the surface of the towed body is divided into Lagrange points (interval ≤ 0.05m), and the location of each point is stored. and surface force .

[0088] For example, if the tow body is 3.24m long and 0.95m wide, and its surface is discrete into approximately 2000 Lagrange points.

[0089] In the process of boundary force transmission mechanism, the surface forces of the rigid body are calculated first:

[0090] The forces exerted by a fluid on a rigid body include pressure and viscous shear force:

[0091] ;

[0092] in, Let be the surface normal vector of the rigid body. This refers to the fluid dynamic viscosity.

[0093] Then, the surface forces are interpolated from the Lagrange points to the fluid mesh:

[0094] Discrete Dirac delta function rigid body surface force Assigned to adjacent fluid mesh nodes:

[0095] ;

[0096] In the above formula, Let be the surface area corresponding to the Lagrange point;

[0097] Functional form (taking three dimensions as an example):

[0098] ;

[0099] in For fluid mesh spacing;

[0100] It is a four-point interpolation kernel function that covers four grid nodes around each Lagrange point (in the one-dimensional case), and expands to 4×4×4=64 nodes in the three-dimensional case.

[0101] Four-point interpolation kernel function The expression is a piecewise function, designed to balance interpolation accuracy and computational efficiency:

[0102] ;

[0103] Key features are as follows:

[0104] The support range is such that the force at each Lagrange point affects the surrounding four grid nodes (one-dimensional), ensuring locality.

[0105] Continuity: in The function values ​​are continuous, ensuring smooth interpolation.

[0106] Normalization: satisfies The total force is strictly conserved.

[0107] when When a Lagrange point is close to a grid node, the force is mainly allocated to the nearest node.

[0108] when The force gradually decays to more distant nodes, avoiding numerical oscillations.

[0109] As displacement is transferred from the fluid mesh to the rigid body surface, the fluid velocity is interpolated to the Lagrange point to update the rigid body position.

[0110] ;

[0111] in, The velocity at the Lagrange point is used to update the rigid body position. .

[0112] The bidirectional coupled iterative computation process includes the following steps:

[0113] First, perform initialization to set the initial fluid field. ,pressure and the initial position of the rigid body .

[0114] The iterative process is as follows (nth time step):

[0115] Step 1, Solve the fluid equations:

[0116] Incorporate the rigid body surface force F_boundary into the Navier-Stokes equations;

[0117] The updated velocity was solved using the finite volume method. and pressure .

[0118] Step 2, interpolate the fluid velocity to the rigid body surface:

[0119] according to Calculate the velocity at the Lagrange point. ;

[0120] Update rigid body position ;

[0121] Step 3, Solve the rigid body dynamics equations:

[0122] According to fluid forces Solve the Newton-Euler equations;

[0123] Update rigid body velocity and angular velocity .

[0124] Step 4, determine convergence:

[0125] Calculate the residual based on the flow velocity change. ;

[0126] like Proceed to the next time step; otherwise, repeat steps 1-3.

[0127] By setting a time step limit, convergence is achieved when the CFL (Courant-Friedrichs-Lewy) condition is met:

[0128] ;

[0129] Typical value: Δt = 0.001s.

[0130] It should be noted that during the computation process, the fluid mesh partitioning in this application can be computed in parallel, and MPI is used to achieve multi-node communication. Simultaneously, the rigid body surface force interpolation process can be accelerated on a GPU, improving computational efficiency.

[0131] After convergence, the convergence results can be analyzed. These results typically include the rigid body's motion parameters, such as position, velocity, attitude angles, and angular velocity, as well as the fluid forces and torques acting on the rigid body, reflecting the towed body's motion and force conditions under the current ballast and control parameters. The attitude changes of the towed body in the fluid, such as the fluctuation range of pitch, roll, and yaw angles, should be examined. Large fluctuations in attitude angles indicate insufficient stability of the towed body, which may require adjustment of the ballast or control parameters to improve it. The towed body's velocity, acceleration, and other parameters can also be analyzed to assess its maneuverability and response speed in the fluid. If the towed body's motion performance does not meet expectations, such as slow acceleration or turning, it may be necessary to optimize the ballast distribution or adjust the control strategy.

[0132] When setting the counterweight for the towed vehicle, the ideal center of gravity position can be determined based on the design requirements and motion needs of the towed vehicle. Generally, a reasonable center of gravity position can improve the stability and maneuverability of the towed vehicle. Based on the attitude and motion response of the rigid body in the convergence results, and combined with the deviation between the current center of gravity position and the target center of gravity position, the required counterweight adjustment amount can be calculated. For example, increasing or decreasing the counterweight in certain areas can move the center of gravity towards the target position. Counterweight blocks can be strategically arranged on the towed vehicle to increase or decrease the weight in specific areas to achieve center of gravity adjustment. It is important to note that when adjusting the counterweight, the symmetry of the towed vehicle should be maintained as much as possible to avoid new imbalance problems caused by uneven weight distribution.

[0133] This application's embodiments construct a layered fluid velocity model based on actual ocean current data, accurately reflecting the true velocity and characteristics of ocean currents at different depths in the deep-sea environment. By combining this with rigid body motion equations considering translation and rotation, and determining discrete Lagrange points on the rigid body surface, subsequent analysis of the target rigid body's motion in the ocean current becomes more accurate and detailed, effectively reducing the prediction error of the towed body's attitude angle and providing more reliable simulation results. Simultaneously, a Cartesian grid is used to discretize the fluid domain, and a boundary layer is set for refinement. An interpolation function couples the fluid grid with the surface forces at the Lagrange points, eliminating the need for frequent mesh reconstruction due to the complex shape and large displacement of the rigid body. This avoids the numerical instability problems caused by mesh distortion in traditional methods and better handles the interaction between fluid and rigid body under complex boundary conditions. The motion parameters of the target rigid body are output upon convergence. Compared to traditional calculation methods, this effectively improves computational efficiency, reduces computational resource consumption, and can complete the solution of large-scale, complex fluid-rigid body coupling problems within a reasonable time, making it more suitable for the computational efficiency requirements of practical engineering scenarios.

[0134] The following describes the rigid body motion control method in ocean currents provided in this application using an exemplary calculation process:

[0135] Step 1: Model Building and Parameter Setting

[0136] The towed body geometry model can be created using CAD software (such as SolidWorks) to build a 3D model of the towed body and exported as an STL format; the key parameters are set as follows: length 3.24 m, weight 1158.58 kg, buoyancy 1204.53 kg.

[0137] Fluid domain and mesh generation: Fluid domain size: 500 m × 200 m × 1000 m (length × width × depth); Cartesian mesh generation is used with a resolution of 0.1 m and the boundary layer is refined to 0.01 m.

[0138] Rigid body surface discretization: The surface of the towed body is discretized into Lagrange points (interval ≤ 0.05 m), totaling approximately 2000 points; the location of each point is stored. Surface force and normal vector .

[0139] Step 2: Configuration of Layered Ocean Current Field

[0140] Velocity stratification modeling: Divide the ocean current into N layers (e.g., N=5), with the velocity distribution in each layer as follows:

[0141] ;

[0142] Parameter example:

[0143] Surface layer (0~100 m): u 10 =1.5 m / s, z0=10 m

[0144] Middle layer (100~500 m): u 20 =0.8 m / s, z0=50 m.

[0145] Turbulent disturbances are superimposed, and a spatiotemporal disturbance function is generated using Gaussian white noise. The amplitude is 10% to 20% of the laminar velocity.

[0146] Step 3, Two-way Coupled Simulation Process:

[0147] Let the initialization condition be: the initial velocity of the fluid field, u. 0 =0, pressure p 0 =Hydrostatic pressure; Initial position of towed body: 10 m above the water surface, velocity v0=0, attitude angle θ0=0°.

[0148] Time step iteration (Δt=0.001 s):

[0149] Step 1: In the fluid solution, the rigid body surface force F_boundary is added to the Navier-Stokes equations; the updated solution is solved using the finite volume method. and .

[0150] Step 2: Interpolate the fluid velocity to the Lagrange point and calculate. and update the rigid body position. .

[0151] Step 3: Calculate fluid forces when solving rigid body dynamics. Then solve the Newton-Euler equations and update the speed. and angular velocity .

[0152] Step 4: Perform a convergence check; if the residuals... Proceed to the next time step; otherwise, repeat steps 1-3.

[0153] Termination conditions: Total simulation time is 60 s, or the motion of the towed body tends to stabilize (attitude angle fluctuation < 1°).

[0154] As can be seen, the key to this embodiment lies in using the Immersed Boundary Method (IBM) coupling framework, which achieves efficient fluid-rigid body coupling by fixing the Eulerian mesh and the Lagrange points on the rigid body surface through bidirectional force transmission, thus avoiding the mesh distortion problem of the traditional ALE method.

[0155] Core formula:

[0156] ;

[0157] in, For discrete Dirac functions, Let be the surface area of ​​the micro-element.

[0158] Furthermore, by constructing a stratified ocean current disturbance model, that is, through stratified velocity functions... Quantifying the non-uniform disturbances of ocean currents at different depths significantly improves adaptability to deep-sea environments. Parameter example: surface current velocity u. 10 =1.5 m / s, mid-layer velocity u 20 =0.8 m / s. Based on the Newton-Euler equations, the translation and rotation of the towed body are accurately described. The quaternion method is introduced to update the attitude angles, avoiding the singularity problem of traditional Euler angles.

[0159] See Figure 2 , Figure 2 This is a schematic diagram of a rigid body motion control system in an ocean current, provided as an embodiment of this application. The system includes:

[0160] The flow splitting model construction module is used to acquire ocean current data and construct a layered fluid velocity model based on the ocean current data.

[0161] The rigid body motion calculation module is used to obtain the motion equations of a target rigid body located in an ocean current; the motion equations include translational equations and rotational equations.

[0162] A rigid body surface discretization module is used to determine discrete Lagrange points on the rigid body surface based on the equation of motion; each Lagrange point contains position information, surface forces, and a normal vector;

[0163] The fluid network generation module is used to discretize the fluid domain corresponding to the layered fluid velocity model using a Cartesian grid of a set resolution, set a boundary layer for refinement, and obtain a fluid grid; the grid nodes of the fluid grid are used to store fluid velocity and pressure.

[0164] A motion parameter output module is used to calculate the surface forces in the fluid mesh and the Lagrange point through interpolation function coupling, and outputs the motion parameters of the target rigid body upon convergence; the motion parameters are used to guide the target counterweight or motion control parameters of the target rigid body. This application also provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the steps of the method described above.

[0165] This application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed, can perform the steps provided in the above embodiments. The storage medium may include various media capable of storing program code, such as a USB flash drive, a portable hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0166] This application also provides an electronic device, see [link to document]. Figure 3 The present application provides a structural diagram of an electronic device, such as... Figure 3 As shown, it may include a processor 1410 and a memory 1420.

[0167] The processor 1410 may include one or more processing cores, such as a quad-core processor or an octa-core processor. The processor 1410 may be implemented using at least one hardware form selected from DSP (Digital Signal Processing), FPGA (Field-Programmable Gate Array), and PLA (Programmable Logic Array). The processor 1410 may also include a main processor and a coprocessor. The main processor, also known as a CPU (Central Processing Unit), is used to process data in the wake-up state; the coprocessor is a low-power processor used to process data in the standby state. In some embodiments, the processor 1410 may integrate a GPU (Graphics Processing Unit), which is responsible for rendering and drawing the content to be displayed on the screen. In some embodiments, the processor 1410 may also include an AI (Artificial Intelligence) processor, which is used to handle computational operations related to machine learning.

[0168] The memory 1420 may include one or more computer-readable storage media, which may be non-transitory. The memory 1420 may also include high-speed random access memory and non-volatile memory, such as one or more disk storage devices or flash memory devices. In this embodiment, the memory 1420 is used to store at least the following computer program 1421, which, after being loaded and executed by the processor 1410, is capable of implementing the relevant steps in the methods executed by the electronic device side as disclosed in any of the foregoing embodiments. In addition, the resources stored in the memory 1420 may also include an operating system 1422 and data 1423, etc., and the storage method may be temporary storage or permanent storage. The operating system 1422 may include Windows, Linux, Android, etc.

[0169] In some embodiments, the electronic device may further include a display screen 1430, an input / output interface 1440, a communication interface 1450, a sensor 1460, a power supply 1470, and a communication bus 1480.

[0170] certainly, Figure 3 The structure of the electronic device shown does not constitute a limitation on the electronic device in the embodiments of this application. In practical applications, the electronic device may include more than [other components]. Figure 3 More or fewer components as shown, or combinations of certain components.

[0171] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. As the system provided in the embodiments corresponds to the method provided in the embodiments, the description is relatively simple; relevant parts can be found in the method section.

[0172] This document uses specific examples to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. It should be noted that those skilled in the art can make several improvements and modifications to this application without departing from the principles of this application, and these improvements and modifications also fall within the protection scope of this application.

[0173] It should also be noted that, in this specification, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

Claims

1. A method of controlling the motion of a rigid body in an ocean current, characterized by, The method comprises the following steps: obtaining ocean current data and constructing a layered fluid velocity model based on the ocean current data; obtaining the motion equation of a target rigid body located in the ocean current; the motion equation comprises a translation equation and a rotation equation; determining the Lagrange points discretely distributed on the surface of the rigid body based on the motion equation; each of the Lagrange points contains position information, surface force and a normal vector; discretizing the fluid domain corresponding to the layered fluid velocity model by using a Cartesian grid with a set resolution, and setting a boundary layer encryption to obtain a fluid grid; the grid nodes of the fluid grid are used to store fluid velocity and pressure; coupling and calculating the surface force in the fluid grid and the Lagrange points by using an interpolation function, and outputting the motion parameters of the target rigid body when convergence is achieved; the motion parameters are used to guide the target counterweight or motion control parameters of the target rigid body; wherein determining the Lagrange points discretely distributed on the surface of the rigid body based on the motion equation comprises: updating the rigid body attitude of the target rigid body by using a quaternion method based on the motion equation; calculating the Lagrange points discretely distributed on the surface of the rigid body according to the updated rigid body attitude.

2. The method of claim 1, wherein, The method of obtaining the motion equation of the target rigid body located in the ocean current comprises: obtaining a three-dimensional model of the target rigid body; determining the translation equation according to the rigid body mass, rigid body center of mass velocity vector, fluid acting force, gravitational acceleration, buoyancy and fluid resistance contained in the three-dimensional model; determining the rotation equation according to the moment of inertia tensor, rigid body angular velocity vector, fluid torque and control torque.

3. The method of claim 2, wherein, The method of obtaining a three-dimensional model of the target rigid body comprises: establishing a three-dimensional model of the target rigid body and setting rigid body parameters of the target rigid body; the rigid body parameters include length, weight and buoyancy; correspondingly, determining the Lagrange points discretely distributed on the surface of the rigid body based on the motion equation comprises: discretizing the surface of the target rigid body into Lagrange points based on the motion equation and the rigid body parameters.

4. The method of claim 1, wherein, The method of coupling and calculating the surface force in the fluid grid and the Lagrange points by using an interpolation function comprises: allocating the surface force to adjacent fluid grid nodes by using a discrete function; covering the surface force around four grid nodes around each Lagrange point by calling a four-point interpolation kernel function; interpolating fluid velocity to the Lagrange points and updating the position of the target rigid body; coupling and calculating until the motion parameters of the target rigid body are output when convergence is achieved.

5. The method of claim 4, wherein, When constructing the layered fluid velocity model based on the ocean current data, the method further comprises: generating a space-time disturbance function by using Gaussian white noise; the space-time disturbance function is used to simulate the turbulent effect in the ocean current.

6. The method of claim 4, wherein, The method of interpolating fluid velocity to the Lagrange points and updating the position of the target rigid body comprises: using multi-node communication to interpolate fluid velocity to the Lagrange points and update the position of the target rigid body by taking the grid nodes in the fluid grid as communication nodes; correspondingly, the method of interpolating fluid velocity to the Lagrange points and updating the position of the target rigid body comprises: calling a graphics processing unit to interpolate fluid velocity to the Lagrange points and output the updated position of the target rigid body.

7. A system for controlling the motion of a rigid body in an ocean current, the system comprising: The method comprises the following steps: a current model construction module is configured to obtain ocean current data and construct a layered fluid velocity model based on the ocean current data; A rigid body motion calculation module is configured to obtain a motion equation of a target rigid body in an ocean current; the motion equation comprises a translation equation and a rotation equation; A rigid body surface discretization module is configured to determine Lagrange points of rigid body surface discretization based on the motion equation; each of the Lagrange points comprises position information, a surface force, and a normal vector; A fluid network generation module is configured to discretize a fluid domain corresponding to the layered fluid velocity model using a Cartesian grid with a set resolution, and to obtain a fluid grid by encrypting a boundary layer; a grid node of the fluid grid is configured to store fluid velocity and pressure; A motion parameter output module is configured to calculate surface forces in the fluid grid and the Lagrange points by coupling an interpolation function, and to output motion parameters of the target rigid body when convergence is achieved; the motion parameters are configured to guide target counterweights or motion control parameters of the target rigid body. The rigid body motion calculation module is configured to update a rigid body pose of the target rigid body using a quaternion method based on the motion equation; and to recalculate the Lagrange points of rigid body surface discretization according to the updated rigid body pose.

8. A computer-readable storage medium having stored thereon a computer program, characterized in that, The computer program is executed by a processor to implement the steps of the method according to any one of claims 1-6.

9. An electronic device, comprising: The computer program is stored in a memory and executed by a processor to implement the steps of the method according to any one of claims 1-6.

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