Control methods, devices, electronic equipment and storage media for underwater autonomous vehicles

Abstract

This application discloses a control method, device, electronic device, and storage medium for an underwater autonomous vehicle (AUV). The method includes: constructing an AUV kinematic model; assigning a virtual target point to each AUV, wherein the virtual target point is the center of a tangential circle formed by the AUV's orbit, and the AUV forms a surrounding encirclement posture with the virtual target point as the center and the distance from the virtual target point being the radius of the tangential circle; when an AUV loses target information, generating a virtual target point by projecting and mapping the position information of neighboring AUVs; and driving multiple AUVs to cooperate in motion based on a kinematic controller according to the AUV kinematic model and the virtual target points. The embodiments of this application solve the problem of efficient and stable multi-AUV cooperative encirclement control under conditions of ocean current disturbance and lack of target information for some AUVs.

Description

Technical Field

[0001] This application relates to a control method, device, electronic equipment, and storage medium for an underwater autonomous vehicle, belonging to the field of multi-AUV three-dimensional cooperative surround and capture control. Background Technology

[0002] With the increasing demand for marine resource development, marine environmental exploration and resource utilization have become key areas of scientific and economic development. Autonomous underwater vehicles (AUVs), with their autonomous navigation, obstacle avoidance, and target detection capabilities, play a crucial role in marine exploration and environmental monitoring. However, single AUV systems have significant limitations in long-term, large-scale, or complex environments: limited detection range and susceptibility to single-point failures leading to mission interruptions, severely restricting system reliability. Therefore, multi-AUV cooperative control technology has become a current research hotspot, demonstrating great application potential in marine exploration and target search. However, existing research methods have significant shortcomings: they typically assume that all AUVs can acquire complete target information, failing to fully consider the impact of missing information on the system, leading to reduced efficiency in cooperative tasks in practical applications. Summary of the Invention

[0003] In view of this, this application provides a control method, device, electronic device and storage medium for underwater autonomous vehicles. The embodiments of this application solve the problem of efficient and stable multi-AUV cooperative capture and control under the conditions of ocean current disturbance and lack of target information for some AUVs.

[0004] The first aspect of this application discloses a control method for an underwater autonomous vehicle, the method comprising:

[0005] Constructing an AUV kinematic model;

[0006] A virtual target point is assigned to each AUV. The virtual target point is the center of the tangential circle formed by the AUV's orbit. The AUV forms a surrounding encirclement and capture pattern with the virtual target point as the center and the distance from the virtual target point as the radius of the tangential circle of the AUV.

[0007] When an AUV loses target information, a virtual target point is generated by projection mapping based on the location information of neighboring AUVs.

[0008] Based on the kinematic controller, multiple AUVs are driven to move in a coordinated manner according to the AUV kinematic model and the virtual target point.

[0009] Furthermore, the construction of the AUV kinematic model includes:

[0010] By introducing the disturbed ocean current velocity along each axis of the inertial coordinate system into the AUV kinematic model, an AUV kinematic model containing ocean current disturbances is obtained.

[0011] Further, the allocation of virtual target points for each AUV includes:

[0012] For each AUV, the longitude and polar angles are calculated using a spherical coordinate grid method and the longitude and polar angles are uniformly distributed on the sphere.

[0013] The corresponding virtual target point is obtained based on the coordinates of the actual target in the inertial coordinate system and the longitude and polar angles.

[0014] Furthermore, the step of generating virtual target points by projection mapping based on neighbor AUV location information includes:

[0015] Construct a neighbor relationship graph for the multi-AUV system, where the neighbor AUV of the i-th AUV is the (i+1)-th AUV, where i does not include N; the neighbor AUV of the N-th AUV is the 1st AUV; i represents the i-th AUV, i = 1, 2, ..., N, where N is the total number of AUVs participating in the cooperative capture.

[0016] If the i-th AUV cannot detect the target, the three-dimensional coordinates of the neighboring AUVs are mapped to the orbit of the i-th AUV to form the coordinates of the virtual target point.

[0017] Furthermore, the method also includes:

[0018] Define the extended state observer as follows:

[0019]

[0020] in, This represents the rate of change in the location estimate. This represents the rate of change of the estimated ocean current disturbance. These are the estimated positions of the i-th AUV in the x, y, and z directions, respectively, in the inertial coordinate system. Let λ1 and λ2 be the estimated ocean current velocities experienced by the i-th AUV in the x, y, and z directions, respectively, in the inertial coordinate system. Let λ1 and λ2 be the observation gains, satisfying λ2 > λ1, [x...]. i ,y i ,z i ] represents the coordinates of the i-th AUV in the inertial coordinate system; θ i Let ψ be the heading angle of the i-th AUV in the inertial coordinate system; i Let v be the pitch angle of the i-th AUV in the inertial coordinate system; i The forward speed designed for the i-th AUV;

[0021] Adjusting the control gain k based on adaptive law p Make the current position of the AUV close to the virtual target point, and ensure that the distance between the AUV and the target point is equal to the radius of the sphere.

[0022] Furthermore, the kinematic controller is as follows:

[0023]

[0024] Where, k v >0, k ω >0, k μ >0 represents the controller parameter, a i Indicates relative position and Previous weight, 0 i <1;[v i ,ω i ,μ i ] T For the kinematic controller input, v i ,ω i ,μ i These represent the forward speed, yaw rate, and pitch rate of the i-th AUV design, respectively.

[0025]

[0026] in, Let [x0, y0, z0] be the rotation matrix, [x'] be the target's coordinates in the inertial coordinate system, and [x'] be the rotation matrix. n ,y' n ,z' n To create a virtual target point coordinate system by mapping the 3D coordinates of neighboring AUVs onto the orbit of the i-th AUV;

[0027] Flag = [f1, f2, f3…f N ]

[0028] Among them, f N To determine whether the Nth AUV can observe the target, not all elements in Flag are 0.

[0029] Furthermore, the gain k p As shown in the following formula:

[0030]

[0031] Where η is the learning rate;

[0032] e r =||[x0-x i ;y0-y i ;z0-z i ]|||-R

[0033] Where ||·|| represents the Euclidean distance, and R represents the radius of the sphere.​

[0034] A second aspect of this application discloses a control device for an underwater autonomous vehicle, the device comprising:

[0035] Modules for building AUV kinematic models;

[0036] The allocation module is used to allocate a virtual target point to each AUV. The virtual target point is the center of the tangential circle formed by the AUV's track. The AUV forms a surrounding encirclement and capture posture with the virtual target point as the center and the distance from the virtual target point as the radius of the tangential circle of the AUV.

[0037] The generation module is used to generate virtual target points based on the location information of neighboring AUVs when the AUV loses target information.

[0038] A drive module is used to drive the cooperative motion of multiple AUVs based on the kinematic controller, the kinematic model of the AUV, and the virtual target point.

[0039] A third aspect of this application discloses a computer-readable storage medium comprising a stored program, wherein the program, when running, controls the execution of the underwater autonomous vehicle control method of the above embodiments in the processor of the device.

[0040] A fourth aspect of this application discloses an electronic device, which includes one or more processors; a storage device for storing one or more programs; and when the one or more programs are executed by the one or more processors, the one or more processors execute the underwater autonomous vehicle control method of the above embodiments.

[0041] Compared with the prior art, the embodiments of this application have the following beneficial effects:

[0042] By fully considering ocean current disturbances and incomplete local information, stable three-dimensional encirclement control of a multi-AUV system was achieved, significantly reducing the reliance on global precise positioning and high-bandwidth communication. Adaptive observation and gain adjustment mechanisms improved the controller's robustness to ocean current disturbances. Relative information was used in the distributed control strategy design to avoid task failures caused by single-point faults. Relative information and ESO ocean current compensation methods were utilized to achieve three-dimensional cooperative encirclement control of multiple AUVs under ocean current disturbances, ensuring system stability. Attached Figure Description

[0043] 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 some embodiments of this application. For those skilled in the art, other drawings can be obtained based on the structures shown in these drawings without creative effort.

[0044] Figure 1 , Figure 8 , Figure 15 These are schematic diagrams of the three-dimensional trajectories of each AUV in the multi-AUV three-dimensional collaborative encirclement (0-200s) in embodiments 1, 2, and 3 of the present invention.

[0045] Figure 2 , Figure 9 , Figure 16 These are schematic diagrams of the trajectories of each AUV in the three-dimensional collaborative encirclement and capture of multiple AUVs from the XY plane perspective (0-200s) in embodiments 1, 2, and 3 of the present invention.

[0046] Figure 3 , Figure 10 , Figure 17 These are schematic diagrams of the trajectories of each AUV in the three-dimensional collaborative encirclement and capture of multiple AUVs from the XZ plane perspective (0-200s) in embodiments 1, 2, and 3 of the present invention.

[0047] Figure 4 , Figure 11 , Figure 18 These are graphs showing the difference between the distance between each AUV and the target in the three-dimensional collaborative encirclement and trapping of multiple AUVs (0-200s) in embodiments 1, 2, and 3 of the present invention and the radius R of the sphere formed during spherical encirclement and trapping.

[0048] Figure 5 , Figure 12 , Figure 19 These are the graphs showing the changes in the separation angle β of each adjacent AUV relative to the target during the three-dimensional collaborative encirclement and capture of multiple AUVs (0-200s) in embodiments 1, 2, and 3 of the present invention.

[0049] Figure 6 , Figure 13 , Figure 20 These are the ESO parameters of each AUV in Embodiments 1, 2, and 3 of the present invention, representing the multi-AUV three-dimensional collaborative encirclement (0-200s). Change diagram;

[0050] Figure 7 This is a schematic diagram of the three-dimensional ocean current distribution in embodiments 2 and 3 of the present invention;

[0051] Figure 14 , Figure 21These are the ESO parameters of the first and fifth AUVs in the multi-AUV three-dimensional collaborative encirclement (0-200s) in embodiments 2 and 3 of the present invention. Change diagram;

[0052] Figure 22 This is a flowchart of a control method for an underwater autonomous vehicle provided by the present invention. Detailed Implementation

[0053] 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.

[0054] 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.

[0055] The technical concept of this invention is to ensure that multiple AUVs form a stable and uniformly distributed spherical encirclement structure in three-dimensional space by dynamically allocating virtual target points. The kinematic controller of the multi-AUV system consists of two parts. First, to address the situation where some AUVs cannot acquire target information due to detection distance or sensor limitations, a method of calculating virtual target points by projecting and mapping neighbor position information is introduced. This yields the relative position of the virtual coordinates calculated based on the position information of neighbors in the local coordinate system, as well as the relative position control part with the target in the local coordinate system. This allows all AUVs to achieve spherical encirclement of the target even under limited measurement and communication conditions. Second, an online estimation and compensation of ocean currents is added using an extended state observer (ESO) and an adaptive gain adjustment strategy to ensure that AUVs can still accurately track and encircle the target when subjected to uncertain ocean current disturbances. This method significantly reduces the dependence on global positioning and communication, improves the robustness of the system under ocean current disturbances, and provides reliable technical support for marine environmental monitoring and countermeasures.

[0056] This invention utilizes the relative positions of virtual coordinates calculated from the positional information of neighbors in a local coordinate system, as well as the relative positions of the virtual coordinates with the target in the local coordinate system. Addressing issues such as uncertain ocean current disturbances and missing information about some AUV targets in a three-dimensional ocean environment, this invention designs a kinematic controller based on a real-time ocean current disturbance observation-compensation mechanism and a local neighbor information mapping strategy. This achieves stable spherical encirclement control of multiple AUVs in three-dimensional space. This method significantly reduces the dependence on global positioning and communication, improves the system's robustness under asymmetric ocean current disturbances, and provides reliable technical support for ocean environmental monitoring and countermeasures missions.

[0057] Example 1:

[0058] refer to Figures 1-22 A three-dimensional cooperative trapping and control method for multiple AUVs under ocean current disturbance includes the following steps:

[0059] Step 1: Establish the kinematic model of the AUV and the kinematic model with ocean current disturbance, and initialize the system state;

[0060] 1.1 The kinematic model of an AUV is expressed as follows:

[0061]

[0062] Where the subscript i represents the i-th AUV, i = 1, 2, ..., N, and N is the total number of AUVs participating in the coordinated capture; [x i ,y i ,z i [x] represents the coordinates of the i-th AUV in the inertial coordinate system. i y is the x-axis. i z is the ordinate. i (where θ is the vertical coordinate); i Let ψ be the heading angle of the i-th AUV in the inertial coordinate system; i Let [v] be the pitch angle of the i-th AUV in the inertial coordinate system; i ,ω i ,μ i ] T For the kinematic controller input, v i ,ω i ,μ i These represent the forward speed, yaw rate, and pitch rate of the i-th AUV design, respectively; [C x C y C z ] T To disturb the ocean current velocity, C x C y C z These represent the velocities of the disturbed ocean currents along the x, y, and z axes of the inertial coordinate system, respectively.

[0063] 1.2 In this control method, the AUV target encirclement employs a virtual target pursuit method. That is, a virtual coordinate is set for each AUV, and the AUV moves around this virtual coordinate as the target, thereby achieving a spherical encirclement with the target as the center and the distance to the target as the radius of the sphere. For the sphere centered on the actual target, a given longitude angle is used. (Horizontal rotation around the z-axis, ranging from 0 to 2π) and polar angle φ i (Measured downwards along the positive z-axis, ranging from 0 to π), the longitude angle is calculated using a spherical coordinate grid. and polar angle φ i To make it evenly distributed on the sphere, longitude angle and polar angle φ i The expression is:

[0064]

[0065] Where t is the orbital time, at the polar angle φ i Introducing a small offset in the settings makes the calculated φ i It will not fall exactly on the poles (i.e., the North and South Poles), ensuring that all AUVs are evenly distributed on the sphere, from the North Pole (φ). i =0) to Antarctica (φ) i Between π and θ. i The settings include a rotation angle that changes over time, so that the azimuth angle of each AUV is not fixed, but dynamically changes around the center of the sphere. This ensures that the AUV rotates along the sphere around the Z-axis at a uniform angular velocity over time, completing one full 2π rotation every 50 time units.

[0066] 1.3 Longitude angles obtained using the spherical coordinate grid method and polar angle φ i Calculate the virtual target point for each AUV. The virtual target point for each AUV is:

[0067]

[0068] Where [x] t ,y t ,z t [x] represents the coordinates of the virtual target point pursued by the i-th AUV. t y is the x-axis. t z is the ordinate. t [x0, y0, z0] are the coordinates of the target in the inertial coordinate system (x0 is the horizontal coordinate, y0 is the vertical coordinate, and z0 is the vertical coordinate), and R represents the radius of the sphere formed when the AUV forms a spherical encirclement of the target.

[0069] Step 2: Considering that some AUVs may be unable to obtain target information during the actual operation of a multi-AUV system, this situation may be caused by: limited sensor sensitivity and detection range; some AUVs being equipped with advanced sensors; information measurement loss due to obstruction by obstacles, etc., a projection mapping method based on neighbor location information is proposed to realize target acquisition and control of a multi-AUV system when some AUVs lack target information.

[0070] 2.1 Define the neighbor AUVn of the i-th AUV as the (i+1)-th AUV, where the neighbor AUVn of the N-th AUV is the 1st AUV. The neighbor relationship graph of the entire multi-AUV system forms a unidirectional loop.

[0071] 2.2 If the i-th AUV cannot detect the target, then use the three-dimensional coordinates [x] of the neighboring AUV n. n ,y n ,z n ](x n y is the x-axis. n z is the ordinate. n The coordinates of the virtual target point [x', where x' is the vertical coordinate) are mapped onto the orbital path of the i-th AUV to form the coordinates of the virtual target point. n ,y' n ,z' n ].

[0072] Specifically, for the vertical coordinate of a neighboring AUV, if it is the Nth AUV, then its neighbor n is the 1st AUV; if the i-th AUV is not the Nth AUV, then its neighbor n is the (i+1)-th AUV. The vertical coordinate z of the virtual coordinate point... ' n The calculation formula is as follows:

[0073]

[0074] Where z ' n Z represents the vertical coordinate of the virtual target point. n The vertical coordinate of the nth AUV. Polar angle. Polar angle

[0075] For the x' of the virtual target point n and the vertical coordinate y' n The x-coordinate of the neighbor AUVn can be... n and the vertical coordinate y n Perform a polar coordinate transformation to obtain the radius coordinate r n With angular coordinates θ n

[0076]

[0077] x is obtained by calculating the transformation relationship. ' n and y ' n The specific formula is as follows:

[0078]

[0079] Where [r' n ,θ' n ] represents the polar coordinates (r') of the virtual target point. n Let θ' be the radius coordinate. n (where x is the angular coordinate), [x N-i+1 ,y N-i+1 ] represents the rectangular coordinates (x, y) of the (N-i+1)th AUV. N-i+1 y is the x-axis. N-i+1 (where y is the vertical axis), this indicates when When the radius of the i-th AUV relative to the target [x0, y0] is the same as the radius of the (N-i+1)-th AUV, and when N is odd and At this time, the orbital radius of the i-th AUV is the radius R of the sphere formed when the AUV surrounds the target, and r' n You can also use r' n =Rsinφ i It can be obtained directly.

[0080] The polar coordinates [r'] of the virtual target point n ,θ' n Convert [x'] to Cartesian coordinates [x'] n ,y' n ]

[0081]

[0082] Combining formulas (7) and (12), the virtual coordinate point [x'] can be obtained. n ,y' n ,z' n ].

[0083] Step 3 addresses the asymmetric disturbance caused by time-varying ocean currents in a three-dimensional ocean environment to the coordinated encirclement of multiple AUVs, proposing an adaptive dynamic compensation strategy based on an Extended State Observer (ESO). Ocean current disturbances are coupled to the x, y, and z velocity components of the AUVs through kinematic equations, leading to formation instability and target tracking deviation. To address this, the ESO introduces [various parameters] in the x, y, and z directions for each AUV. Used to estimate the position of the i-th AUV in the x, y, z directions. To estimate the impact of ocean current disturbances, the disturbed dynamic system is transformed into an extended state model. The components of the ocean current velocity in the x, y, and z directions are estimated in real time and incorporated as feedforward terms into the backstep control law design. Adaptive gain adjustment is then used to suppress ocean current disturbances. This scheme relies solely on observations of the AUV's own motion state, eliminating the need for precise pre-setting of ocean current field model parameters. Dynamic cancellation of unsteady flow field disturbances is achieved through online adjustment of the compensation gain.

[0084] 3.1 For the motion of each AUV in three-dimensional space affected by ocean currents, the Extended State Observer (ESO) is defined as follows:

[0085]

[0086] in In ESO, the rate of change of position estimate is represented by kinematic model, perturbation compensation, and observation error correction. This represents the rate of change of the ocean current disturbance estimate, which is driven by observation error and whose convergence speed is adjusted by the gain β2. These are the estimated positions of the i-th AUV in the x, y, and z directions, respectively, in the inertial coordinate system. λ1 and λ2 are the estimated velocities of the ocean currents acting on the current i-th AUV in the x, y, and z directions in the inertial coordinate system, respectively. λ1 and λ2 are the observation gains of ESO, respectively. Under normal circumstances, λ2 >> λ1 is satisfied to improve the accuracy of disturbance estimation.

[0087] 3.2 Adjusting the control gain k using an adaptive law p This allows the kinematic controller to automatically adapt to disturbances in the intensity and direction of ocean currents, employing an error-based adaptive law to update the gain. The goal is to make the AUV's current position approximate the virtual target point position [x]. t ,y t ,z t ], and the position of the target point is maintained at the spherical radius R.

[0088] Define the deviation e between the current AUV's distance from the target point and the desired encirclement radius. r for

[0089] e r =||[x0-x i ;y0-y i ;z0-z i ]||-R (11)

[0090] Where ||·|| represents the Euclidean distance, which is the distance between the AUV and the target point in three-dimensional space.

[0091] Next, the gain is dynamically adjusted based on the error. The rate of change of the adaptive gain. Given by the following formula

[0092]

[0093] Here, η is the learning rate, which controls the rate of gain change. When the error is large, the gain change will also be large, thus making the control system respond faster; when the error decreases, the gain adjustment gradually decreases to avoid over-adjustment.

[0094] Based on rate of change Adaptive gain k p The update formula can be expressed as

[0095]

[0096] in The adaptive gain k obtained at time t p , To calculate the adaptive gain k at time t+1 p .

[0097] Velocity estimation of ocean currents using an extended state observer (ESO) and adaptive gain k p The settings allow the system to automatically adjust the control input according to the current environmental conditions as the error between the AUV and the target changes, thus improving the system's robustness.

[0098] Step 4: Considering the problems of inaccurate underwater GPS positioning and limited detection distance during movement, a multi-AUV kinematic controller based on local information is proposed. The controller is designed by utilizing the relative position information between AUV neighbors and the relative position information between the AUV that can detect the target and the target, making it more suitable for underwater working environment.

[0099] 4.1 Define the relative positions of the i-th AUV and its neighboring n-th AUV in the local coordinate system using the virtual coordinate points obtained in step 2. The relative position between the i-th AUV and the target in the local coordinate system They are respectively

[0100]

[0101] in Let β be the rotation matrix, and define the separation angle β = arctan2(y) of two adjacent AUVs relative to the target in the XY plane. i+1 -y0,x i+1 -x0)-arctan2(y i -y0,x i -x0), where arctan2 is the arctangent function;

[0102] 4.2 Define the requirements that the target encirclement and capture task must meet as follows:

[0103]

[0104] in, It is a constant. R is the distance between the AUV and the target in the i-th AUV target capture mission, and it is also the radius of the sphere formed by the AUV around the target;

[0105] 4.3 The state f is defined as whether the i-th AUV can observe the target. i When f i When f = 0, it means that the i-th AUV cannot observe the target. i When = 1, it means that the i-th AUV can observe the target. The determinant Flag represents the set of states where all AUVs can or cannot observe the target.

[0106] Flag = [f1, f2, f3…f N (17)

[0107] Where N is the total number of AUVs participating in the target capture mission, and f1, f2, and f3 are the states of whether the 1st, 2nd, and 3rd AUVs can observe the target, respectively. In the application, at least one AUV can observe the target, that is, not all elements in Flag are 0.

[0108] 4.4 Design the kinematic controller for a multi-AUV system, with the expression as follows:

[0109]

[0110] Where k v >0, k ω >0, k μ >0 represents the controller parameter, a i Indicates relative position and Previous weight, 0 i <1,k p To compensate for the adaptive gain of the control section of the Extended State Observer (ESO).

[0111] Step 5: To simulate the impact of ocean currents on autonomous underwater vehicles (AUVs) in a real marine environment, a spatially distributed ocean current disturbance model is established. This model assumes that the velocity field of the ocean current is non-uniform in three-dimensional space and changes with position. Because the AUV's target acquisition time is short, the ocean current does not change significantly over time; therefore, the model assumes that the ocean current does not change over time. [C] x C y C​z ] T The velocity of the ocean current in the x, y, z directions is expressed as follows:

[0112]

[0113] Where A represents the maximum velocity amplitude of the ocean current, making the velocity range between [-A, A], α, β, and γ are the spatially varying wavenumbers used to control the spatial distribution characteristics of the ocean current in different directions; x, y, and z are the positions of the AUV in the inertial coordinate system; and phase offsets π / 3 and π / 4 are used to simulate the asymmetry of the ocean current, causing it to have different distribution patterns in different regions. This ocean current field modeling method can be used to test the adaptability of AUVs in complex water flow environments and provide a foundation for the design of subsequent control algorithms.

[0114] Step 6: Using the kinematic controller designed in Step 4, the AUVs are used to perform three-dimensional collaborative encirclement and capture control of the target (taking 5 AUVs as an example) to encircle and capture the target in a spherical manner, in order to meet the requirements of the encirclement and capture mission and to verify the effectiveness of the present invention.

[0115] In some embodiments, the dynamic orbit radius iterative method designed in step 2 is designed to address the dynamic changes in the target information. Once the target detection information changes, the orbit radius of each AUV is re-determined through iterative steps 2.1 and 2.2.

[0116] To more effectively illustrate the effectiveness of the method of this invention, all parameter settings are consistent. The initialization of system parameters and controller parameters are shown in Table 1, and the initial positions of the N AUVs performing the encirclement task are set to random positions.

[0117] Table 1 Parameter Initialization

[0118]

[0119] Implementation method 1: Multi-AUV three-dimensional collaborative encirclement and capture control with no ocean current disturbance and all AUVs capable of detecting the target.

[0120] In this example, the ocean current speed is set to 0, meaning the AUVs are not affected by the current, and all AUVs can detect the target. The determinant is set to Flag = [1,1,1,1,1]. Figure 1 This diagram illustrates the 3D cooperative encirclement and capture process of multiple AUVs targeting a target in 3D space. Different line types distinguish the orbital trajectories of each AUV. Solid circles represent the initial positions of the AUVs, asterisks (*) indicate the final positions of the AUVs at t = 200s (the end of the simulation time), and triangles represent the target positions [x0, y0, z0]. Figure 1It can be clearly seen that multiple AUVs can complete the task of spherically encircling and capturing targets from any initial position. Figure 2 and Figure 3 The images show the encirclement process of multiple AUVs from the XY and XZ planes, respectively. Figure 2 Each AUV, viewed from the XY plane, has a circle centered on the target, with Rsinφ i N concentric circles are formed with a radius of 1. Figure 3 This indicates that the distance between the orbits of each AUV is relatively uniform, and the x-coordinate of the midpoint of the line segment formed by the trajectory under the XZ plane view is the same as the x-coordinate x0 of the target. Figure 4 This graph shows the variation of the error value between the distance between the AUV and the target and the encirclement radius R. Figure 5 This graph shows the variation of the separation angle β between two adjacent AUVs relative to the target in the XY plane. From... Figure 4 It can be seen that the error values ​​of the distance between each AUV and the target and the encirclement radius R basically stabilize at t=45s, with a stable value of 0, which is consistent with... The requirements for the encirclement and capture target; from Figure 5 It can be seen from this that the separation angle β reaches a stable value of 72° at t = 25s, which is consistent with... The requirements for the encirclement and capture. Figure 6 This represents the estimated velocity of ocean currents in the ESO estimator. The change graph shows that the ESO estimator accurately estimates the ocean current velocity. In summary, this invention provides a three-dimensional cooperative encirclement and control method for multiple AUVs operating without ocean current disturbances and where all AUVs can detect the target.

[0121] Implementation method 2: Multi-AUV three-dimensional collaborative encirclement and control with the addition of ocean current disturbance and the ability of all AUVs to detect the target.

[0122] To verify the effectiveness of the invention, without changing the control parameters, the influence of ocean current disturbance was added, specifically the position-varying ocean current set in step 5. The result is as follows. Figures 7-14 As shown, Figure 7 This represents the distribution of ocean currents in three-dimensional space. The direction of the arrow indicates the direction of the current, the length of the arrow indicates the size of the current, and the longer the arrow, the greater the speed of the current. Figure 8 , Figure 9 , Figure 10 The diagrams show the three-dimensional cooperative encirclement process of multiple AUVs targeting a target in three-dimensional space under the influence of ocean current disturbance, as well as the encirclement process of multiple AUVs from the XY plane and XZ plane perspectives. It can be seen that although there is the influence of ocean current, the trajectory of the AUV is still basically the same as that of the AUV in Example 1, indicating that the ESO state observer's estimation and compensation of ocean current is accurate and timely. Figure 11It can be seen that when t=20s, the error value of the distance between each AUV and the target and the capture radius R is stable at around 0, but there are still fluctuations after stabilization, with the maximum offset being 0.2m. Figure 12 As can be seen, the separation angle β reaches a stable value of 72° at t = 25s, which is consistent with... The requirements for the encirclement and capture. Figure 13 This represents the estimated velocity of ocean currents in the ESO estimator. The graph shows the changes in the estimated ocean current velocity obtained by each AUV due to their different orbital paths. They are also different. Figure 14 Estimated current velocities for the 1st and 5th AUVs The change graph, combined with formula (19) in step 5, shows the estimated velocity of the ocean current. Similar to the established ocean currents, this demonstrates that the ESO state observer's estimation of ocean currents is accurate.

[0123] Implementation method 3: Multi-AUV three-dimensional cooperative encirclement and capture control with the addition of ocean current disturbance and only the first AUV being able to detect the target.

[0124] In this example, the ocean current parameters are the same as in Example 2. The determinant Flag = [1,1,1,1,1] is modified so that only the first AUV can detect the target. Figures 15-17 The diagrams show the three-dimensional coordinated encirclement process of multiple AUVs against a target, as well as the encirclement process from the XY and XZ planes. It can be observed that compared to Example 2, the movement trajectories of the AUVs are more scattered, meaning that the AUVs took longer to complete the spherical encirclement of the target. Furthermore, the trajectory of the AUVs in the XY plane is not a regular circle, but it is still a concentric circle with the target coordinates as the center. From the XZ plane perspective, the x-coordinate of the midpoint of the line segment formed by the trajectory is basically the same as the x-coordinate x0 of the target, indicating that the encirclement control is still effective. Figure 18 The error values ​​of the distance between each AUV and the target and the encirclement radius R are shown. It can be seen that the error value basically stabilizes at t=50s, but the stable value of each AUV is not 0, but is near 0. The fluctuation after stabilization is quite obvious, with the maximum offset being 0.6m. Figure 19 This indicates the change in the separation angle between adjacent AUVs. At t = 80s, the separation angle β basically reaches a stable value. However, the separation angles calculated for the first and second AUVs deviate significantly from those of other adjacent AUVs. This may be because the average value of all the set separation angles is not considered. The calculations resulted in this. Figure 20 and Figure 21 Estimated velocity of the Midsea Current As in Example 2, this indicates that the ESO state observer's estimation of ocean currents remains accurate, and the multi-AUV three-dimensional coordinated encirclement and capture of the target by only the first AUV has basically fulfilled the control requirements.

[0125] The embodiments and simulation results described above fully verify the proposed multi-AUV three-dimensional cooperative encirclement control method, which still exhibits good encirclement performance under complex ocean current disturbance conditions and in environments where some AUVs cannot acquire target information. However, it should be noted that in embodiment 3, when only one AUV can directly observe the target, although the encirclement task is ultimately achieved, the encirclement trajectory exhibits certain irregularities and stability errors compared to when all AUVs can observe the target. This phenomenon is mainly due to insufficient information leading to a decrease in the accuracy of virtual target point mapping, thereby affecting the overall encirclement efficiency and accuracy. Therefore, in practical applications, this method can be further improved by increasing information interaction between AUVs, optimizing the neighbor information mapping algorithm, or improving sensor performance. Obviously, this invention is not limited to the specific details of the above embodiments. Without departing from the basic spirit and scope of protection of this invention, those skilled in the art can make further improvements and adjustments to this invention according to the actual situation, and these adjustments and improvements should also be considered to fall within the scope of protection of this invention.

[0126] Example 2:

[0127] This application provides a control device for an underwater autonomous vehicle, which may include the following modules:

[0128] Modules for building AUV kinematic models;

[0129] The allocation module is used to allocate a virtual target point to each AUV. The virtual target point is the center of the tangential circle formed by the AUV's track. The AUV forms a surrounding encirclement and capture posture with the virtual target point as the center and the distance from the virtual target point as the radius of the tangential circle of the AUV.

[0130] The generation module is used to generate virtual target points based on the location information of neighboring AUVs when the AUV loses target information.

[0131] A drive module is used to drive the cooperative motion of multiple AUVs based on the kinematic controller, the kinematic model of the AUV, and the virtual target point.

[0132] Example 3:

[0133] Embodiments of this application also provide an electronic device, including: a memory storing an executable program; and a processor for running the program, wherein the program executes the methods in various embodiments of the present invention during runtime.

[0134] The aforementioned memory can refer to devices inside a computer used to store data and programs, including RAM, hard disks, etc. RAM can be used to temporarily store running programs and data, while hard disks can be used to store programs and data long-term. Memory enables the computer to read and write data and execute programs. The aforementioned processor is responsible for executing instructions in computer programs and performing data processing. It can also be responsible for controlling and executing various operations, including arithmetic operations, logical operations, and data transmission.

[0135] Example 4:

[0136] Embodiments of this application also provide a computer-readable storage medium including a stored executable program, wherein, when the executable program is running, it controls the device where the computer-readable storage medium is located to perform the methods of various embodiments of the present invention.

[0137] The aforementioned computer storage media can refer to the media used in computer memory to store certain discontinuous physical quantities. Computer storage media mainly include semiconductors, magnetic cores, magnetic drums, magnetic tapes, laser discs, etc. Computer-readable storage media include stored programs, which can be a set of instructions that a computer can recognize and execute, running on an electronic computer to meet certain information needs.

[0138] Example 5:

[0139] Embodiments of this application also provide a computer program product, including a computer program that, when executed by a processor, implements the methods of various embodiments of the present invention.

[0140] The aforementioned computer program products can refer to software programs that have been written, tested, and released, and can run on computers or other devices. Computer program products can include application programs, operating systems, utility software, etc., used to achieve specific functions or solve specific problems.

[0141] Example 6:

[0142] Embodiments of this application also provide a computer program product, including a non-volatile computer-readable storage medium for storing a computer program that, when executed by a processor, implements the methods in various embodiments of the present invention.

[0143] The aforementioned non-volatile computer-readable storage medium can refer to a medium for storing data. Non-volatile computer-readable storage media can retain data without loss when power is off and can be used to store long-term data, such as operating systems, applications, and user files. Non-volatile storage media can include hard disk drives, solid-state drives, optical disks, and flash memory storage devices, etc.

[0144] Example 7:

[0145] Embodiments of this application also provide a computer program that, when executed by a processor, implements the methods described in the various embodiments of the present invention.

[0146] The aforementioned computer program can refer to a set of instructions used to tell the computer to perform specific tasks or operations. Computer programs can be written by programmers using specific programming languages ​​and can include algorithms, data structures, logic, and control flow. Computer programs can be used for a variety of purposes, including application software, operating systems, etc.

[0147] In the above embodiments of the present invention, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0148] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units can be a logical functional division, and in actual implementation, there may be other division methods. For instance, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual coupling, direct coupling, or communication connection may be through some interfaces; the indirect coupling or communication connection between units or modules may be electrical or other forms.

[0149] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0150] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0151] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0152] In summary, to overcome the technical challenges of existing multi-AUV systems, such as inaccurate underwater positioning, limited measurement and communication distances, and insufficient target acquisition capabilities under complex conditions like ocean current disturbances or the inability of some AUVs to acquire target information, this invention provides a three-dimensional cooperative acquisition control method for multiple AUVs under ocean current disturbances. This method considers the influence of ocean current disturbances in the AUV kinematic model and, for different situations involving observable and unobservable targets, the information used by the controller only includes the relative position of the virtual coordinates calculated from the position information of the neighboring targets in the local coordinate system and the relative position of the target in the local coordinate system. This enables multi-AUVs to perform spherical acquisition tasks in three-dimensional space under ocean current disturbances, ensuring system stability and providing new technical means and theoretical foundations for marine environmental monitoring, resource development, marine combat, and disaster relief.

[0153] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method of controlling an underwater autonomous vehicle, characterized by, The method comprises the following steps: constructing an AUV kinematic model; allocating a virtual target point for each AUV, the virtual target point being the center of a tangent circle formed by the orbit of the AUV, and the AUV forming a surrounding hunting posture with the virtual target point as the center and the distance from the virtual target point being the radius of the tangent circle where the AUV is located; when the AUV loses target information, projecting and mapping based on neighbor AUV position information to generate a virtual target point; driving multi-AUV cooperative motion based on a kinematic controller according to the AUV kinematic model and the virtual target point; defining an extended state observer as follows: wherein, represents the rate of change of the position estimate, represents the rate of change of the current disturbance estimate, are the estimated positions of the current i-th AUV in x, y, z directions in the inertial coordinate system, respectively, are the estimated velocities of the current i-th AUV in x, y, z directions in the inertial coordinate system, respectively, and λ1 and λ2 are observation gains, satisfying λ2 > λ1, [x i ,y i ,z i ] are the coordinates of the i-th AUV in the inertial coordinate system; θ i is the heading angle of the i-th AUV in the inertial coordinate system; ψ i is the pitch angle of the i-th AUV in the inertial coordinate system; v i is the designed forward velocity of the i-th AUV; Adjusting control gain k based on adaptive law p The current position of the AUV is forced to approach the virtual target point and the distance to the target point is ensured to be a spherical radius.

2. The underwater autonomous vehicle control method of claim 1, wherein, The method for constructing an AUV kinematic model comprises the following steps: In the AUV kinematic model, the disturbance current velocity of each axis of the inertial coordinate system is introduced to obtain an AUV kinematic model containing sea current disturbance.

3. The underwater autonomous vehicle control method of claim 1, wherein, The method for allocating a virtual target point for each AUV comprises the following steps: For each AUV, the longitude angle and the polar angle are calculated using a spherical coordinate grid point method and the longitude angle and the polar angle are uniformly distributed on the sphere; Based on the coordinates of the actual target in the inertial coordinate system and the longitude angle and the polar angle, the corresponding virtual target point is obtained.

4. The underwater autonomous vehicle control method of claim 1, wherein, The method for projecting and mapping based on neighbor AUV position information to generate a virtual target point comprises the following steps: A neighbor relationship graph of the multi-AUV system is constructed, wherein the neighbor AUV of the ith AUV is the i+1th AUV, at this time i does not include N; the neighbor AUV of the Nth AUV is the 1st AUV; i represents the ith AUV, i = 1, 2, …, N, and N is the total number of AUVs participating in cooperative hunting; If the ith AUV cannot detect the target, the three-dimensional coordinates of the neighbor AUV are mapped into the surrounding orbit where the ith AUV is located to form a virtual target point coordinate.

5. The underwater autonomous vehicle control method of claim 1, wherein, The kinematic controller is as follows: where k v > 0, k ω > 0, k μ > 0 are controller parameters, a i denotes relative position and previous weights, 0 < a i < 1;[v i , ω i , μ i ] T are kinematic controller inputs, v i , ω i , μ i represent forward speed, yaw rate and pitch rate of the ith AUV design, respectively. wherein, is a rotation matrix, [x0, y0, z0] is the coordinate of the target in the inertial coordinate system, and [x' n ,y' n ,z' n ] is the virtual target point coordinate formed by mapping the three-dimensional coordinates of the neighbor AUV into the surrounding orbit in which the ith AUV is located. Flag = [f1, f2, f3... f N ] where f N is the state of the Nth AUV can observe the target, the elements of Flag are not all 0.

6. The underwater autonomous vehicle control method of claim 5, wherein, Gain k p As follows: wherein η is a learning rate; e r =||[x0-x i ;y0-y i ;z0-z i ]|||-R wherein ||·|| represents the Euclidean distance, and R represents the radius of the sphere.

7. An underwater autonomous vehicle control device, characterized by, The method comprises the following steps: constructing an AUV kinematic model; allocating a virtual target point for each AUV, the virtual target point being the center of a tangent circle formed by the orbit of the AUV, and the AUV forming a surrounding hunting posture with the virtual target point as the center and the distance from the virtual target point being the radius of the tangent circle where the AUV is located; generating a virtual target point based on neighbor AUV position information when the AUV loses target information; driving multi-AUV cooperative motion based on a kinematic controller according to the AUV kinematic model and the virtual target point; defining an extended state observer as follows: wherein, represents the rate of change of the position estimate, represents the rate of change of the current disturbance estimate, are the estimated positions of the current i-th AUV in x, y, z directions in the inertial coordinate system, respectively, are the estimated velocities of the current i-th AUV in x, y, z directions in the inertial coordinate system, respectively, and λ1 and λ2 are observation gains, satisfying λ2 > λ1, [x i ,y i ,z i ] are the coordinates of the i-th AUV in the inertial coordinate system; θ i is the heading angle of the i-th AUV in the inertial coordinate system; ψ i is the pitch angle of the i-th AUV in the inertial coordinate system; v i is the designed forward velocity of the i-th AUV; Adjusting control gain k based on adaptive law p The current position of the AUV is forced to approach the virtual target point and the distance to the target point is ensured to be a spherical radius.

8. A computer-readable storage medium, characterized in that, The computer readable storage medium comprises a stored program, wherein when the program is executed, the processor of the device is controlled to execute the underwater autonomous vehicle control method in any one of claims 1 to 6.

9. An electronic device, comprising: The device comprises the following: one or more processors; a storage device for storing one or more programs; when the one or more programs are executed by the one or more processors, the one or more processors execute the underwater autonomous vehicle control method in any one of claims 1 to 6.

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