Multi-unmanned ship cooperative multi-target uniform hunting control method

Abstract

The invention discloses a multi-unmanned-ship cooperative multi-target uniform hunting control method, and relates to the technical field of multi-unmanned-ship cooperative multi-target hunting. In order to solve the technical defects that in the prior art, an existing multi-unmanned-ship cooperative hunting technology is low in efficiency, insufficient in hunting precision and stability, complex in gain design and prone to generating overlarge gain, the technical scheme provided by the invention comprises the steps that kinematics models of a multi-unmanned-ship system and a multi-target system are constructed; defining a target state of the hunting task; based on the kinematic model and the target state, establishing a distributed target center estimator; constructing a surrounding controller according to target geometric center information provided by the distributed target center estimator; based on the control strategy of the hunting controller, the angular velocity of the unmanned ship is adjusted to achieve the consistency of phase interval angles; and dynamically adjusting parameters of the hunting controller, and outputting the parameters to the multi-unmanned ship system. The method is suitable for being applied to the cooperative multi-target uniform hunting control work of multiple unmanned ships.

Description

Technical Field

[0001] The invention relates to the technical field of multi-unmanned boat coordinated multi-target encirclement and capture, and specifically to a control method for multi-unmanned boat coordinated multi-target uniform encirclement and capture. Background Art

[0002] In recent years, unmanned boats have been widely used in the fields of marine transportation, resource exploration and environmental monitoring, and their technical research has made significant progress. At present, the research focuses on the path tracking, trajectory planning and target capture of a single unmanned boat. For example, a study proposed a target capture method based on predetermined trajectory planning, which achieves accurate tracking of static or slow-moving targets by optimizing the motion trajectory of a single unmanned boat. In addition, some studies have explored single-target capture strategies combined with sensor networks, enabling unmanned boats to efficiently capture targets through global information. However, the application of a single unmanned boat is limited by the complexity of environmental changes and the high risk of single-point failures, and it is difficult to meet the dynamic requirements of multiple targets in complex mission scenarios.

[0003] In order to improve the efficiency of tasks, research in recent years has gradually turned to multi-unmanned boat collaborative systems. In terms of multi-target capture, there are mainly two research methods. One method is to group multiple unmanned boats and capture their respective targets respectively, thereby simplifying the problem into multiple single-target capture tasks. However, this method lacks global coordination capabilities and is prone to task conflicts or resource waste at the group boundaries. Another method is to pre-plan the capture trajectory so that the unmanned boats form a circular queue and limit the target to the capture area. Although this method can achieve the overall capture of the target, when the target movement is unpredictable, the trajectory needs to be updated frequently, resulting in a sharp increase in computational complexity and even possible failure.

[0004] Although the existing technology has made important progress in the coordinated capture of multiple unmanned boats, the following technical problems still exist: First, the existing center estimator usually relies on global variable information or specific initialization conditions. When a node fails or a new node is added to the system, the system needs to be reinitialized, which is inefficient. Second, the existing capture control method is not adaptable enough to dynamic targets and cannot effectively deal with the free movement of the target. The capture accuracy and stability are greatly limited. Third, the traditional method relies heavily on global consistency, the gain design is complex and prone to excessive gain problems, which affects the robustness of the control system.

[0005] The above problems limit the application of multi-unmanned boat collaborative capture technology in dynamic and complex environments. Therefore, a new method that can overcome global dependence, improve estimation accuracy and adapt to dynamic targets is urgently needed to solve the above technical problems. Summary of the invention

[0006] In order to solve the technical defects existing in the prior art, the existing multi-unmanned boat cooperative capture technology has low efficiency, insufficient capture accuracy and stability, and complex gain design and easy to generate excessive gain, the technical solution provided by the present invention is:

[0007] A multi-unmanned boat coordinated multi-target uniform capture control method, comprising:

[0008] Construct kinematic models of multi-UAV systems and multi-target systems, and define the steps for the target state of the capture mission;

[0009] The step of establishing a distributed target center estimator based on the kinematic model and the target state;

[0010] The step of constructing a capture controller according to the target geometric center information provided by the distributed target center estimator;

[0011] Based on the control strategy of the capture controller, the angular velocity of the unmanned boat is adjusted to achieve the consistency of the phase interval angle;

[0012] The steps of dynamically adjusting the parameters of the capture controller and outputting them to the multi-unmanned boat system.

[0013] Furthermore, a preferred embodiment is provided, wherein the distributed target center estimator eliminates the consistency error of the intermediate state variables through a linear drive term, and combines with a maximum consistency algorithm to allow each unmanned boat to independently calculate the gain based on local information.

[0014] Furthermore, a preferred embodiment is provided, in which the kinematic model of the multi-target system is constructed, including the geometric center of the target and its relative position and phase angle relationship with the unmanned boat.

[0015] Furthermore, a preferred embodiment is provided, in which the linear driving term of the distributed target center estimator achieves consistency based on iterative calculation of local adjacency relations, and is independently calculated based on a maximum consistency algorithm, and is adapted to different initial distribution conditions through dynamic adjustment.

[0016] Furthermore, a preferred embodiment is provided, wherein the linear speed in the capture controller is designed by a proportional gain parameter, and the proportional gain parameter range is dynamically adjusted according to the relative distance between the unmanned boat and the target center.

[0017] Furthermore, a preferred embodiment is provided, wherein the kinematic model of the multi-target system includes a nonlinear trajectory of the target, and the speed and angular velocity of the target are set according to a dynamic function.

[0018] Based on the same inventive concept, the present invention also provides a multi-unmanned boat coordinated multi-target uniform capture control device, comprising:

[0019] Construct kinematic models of multi-UAV systems and multi-target systems, and define modules for target states of capture missions;

[0020] Based on the kinematic model and the target state, a module for establishing a distributed target center estimator is established;

[0021] According to the target geometric center information provided by the distributed target center estimator, a module of the capture controller is constructed;

[0022] A module for adjusting the angular velocity of the unmanned boat to achieve consistency of the phase interval angle based on the control strategy of the capture controller;

[0023] Dynamically adjust the parameters of the capture controller and output them to the module of the multi-unmanned boat system.

[0024] Based on the same inventive concept, the present invention also provides a computer storage medium for storing a computer program. When the computer program is read by a computer, the computer executes the described method.

[0025] Based on the same inventive concept, the present invention also provides a computer, including a processor and a storage medium. When the processor reads a computer program stored in the storage medium, the computer executes the method described.

[0026] Based on the same inventive concept, the present invention also provides a computer program product, which is a computer program. When the computer program is executed, the method described above is implemented.

[0027] Compared with the prior art, the technical solution provided by the present invention is beneficial in that:

[0028] The design of the distributed target center estimator significantly improves the system's robustness to initialization errors by introducing linear terms to drive the intermediate state variables to zero consistency. This design effectively avoids the efficiency reduction caused by the need for specific initialization in traditional methods. Compared with existing research, it achieves stable estimation without reinitializing the network, which is particularly suitable for scenarios with node failures or newly added nodes.

[0029] The application of the maximum consistency algorithm in gain design enables each unmanned boat to independently obtain gain from local information, eliminating the dependence on global variable information. This method avoids the instability problem caused by excessive gain in traditional methods, significantly enhances the robustness of the estimator in practical applications, ensures that the estimation error converges quickly within a limited time, and is more flexible and reliable than methods that rely on global control.

[0030] The multi-target uniform capture controller designed based on the exclusion theory enables the multi-unmanned boat system to capture multiple moving targets, and even if the initial state distribution is different, the stability and uniformity of the capture process can be guaranteed. Compared with the previous single-target strategy, this design not only achieves a uniform distribution between targets, but also solves the dynamic capture problem of freely moving targets, and enhances adaptability in complex environments.

[0031] The control scheme uses a distributed target center estimator combined with a uniform capture controller, which enables the system to achieve efficient capture of multi-target systems without the need for global variables. Compared with existing group capture or predetermined trajectory methods, this scheme significantly reduces the computational complexity while improving the success rate and efficiency of the capture task, verifying its superiority in dynamic and unpredictable environments.

[0032] It is suitable for use in the work of multiple unmanned boats coordinating and controlling multiple targets evenly. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 This is a schematic diagram of the target roundup;

[0034] Figure 2 Schematic diagram of the trajectory of multiple unmanned boats coordinating to capture a target;

[0035] Figure 3 Schematic diagram of the consistency error of the distributed target center estimator;

[0036] Figure 4 Schematic diagram of the estimation error of the distributed target center estimator;

[0037] Figure 5 Schematic diagram of the distance error of multiple unmanned boats coordinating their capture;

[0038] Figure 6 Schematic diagram of phase error of multiple unmanned boats coordinating and encircling;

[0039] Figure 7 Schematic diagram of angle tracking error of multiple unmanned boats coordinated encirclement. DETAILED DESCRIPTION

[0040] In order to make the advantages and benefits of the technical solution provided by the present invention more clearly reflected, the technical solution provided by the present invention is now further described in detail in conjunction with the accompanying drawings:

[0041] Embodiment 1: This embodiment provides a method for controlling the uniform capture of multiple targets by coordinating multiple unmanned boats, including:

[0042] Construct kinematic models of multi-UAV systems and multi-target systems, and define the steps for the target state of the capture mission;

[0043] The step of establishing a distributed target center estimator based on the kinematic model and the target state;

[0044] The step of constructing a capture controller according to the target geometric center information provided by the distributed target center estimator;

[0045] Based on the control strategy of the capture controller, the angular velocity of the unmanned boat is adjusted to achieve the consistency of the phase interval angle;

[0046] The steps of dynamically adjusting the parameters of the capture controller and outputting them to the multi-unmanned boat system.

[0047] The distributed target center estimator eliminates the consistency error of the intermediate state variables through a linear driving term, and combines with the maximum consistency algorithm to allow each unmanned boat to independently calculate the gain based on local information.

[0048] The construction of the kinematic model of the multi-target system includes the geometric center of the target and its relative position and phase angle relationship with the unmanned boat.

[0049] The linear drive item of the distributed target center estimator achieves consistency based on iterative calculation of local adjacency relations, and is independently calculated based on a maximum consistency algorithm, and is adapted to different initial distribution conditions through dynamic adjustment.

[0050] The linear speed in the capture controller is designed by a proportional gain parameter, and the proportional gain parameter range is dynamically adjusted according to the relative distance between the unmanned boat and the target center.

[0051] The kinematic model of the multi-target system includes nonlinear trajectories of the targets, and the speed and angular velocity of the targets are set according to dynamic functions.

[0052] Implementation method 2: This implementation method is a detailed description of the technical solution provided in implementation method 1, specifically:

[0053] Step 1: Build a model and formulate the problem

[0054] Determine the kinematic model of the multi-unmanned boat system and the multi-target system:

[0055] For the unmanned boat, its nonlinear kinematic model is defined to describe its position, yaw angle, forward speed, drift speed and bow angular velocity.

[0056] For the target, its kinematic model is defined to describe its position, yaw angle and motion parameters.

[0057] Define the target geometric center and target distribution characteristics of the multi-target system.

[0058] Describe the multi-target uniform roundup problem:

[0059] The multi-target capture mission is abstracted into the problem of controlling the relative position and angle between the multi-unmanned boat system and the target geometric center.

[0060] The safety radius and uniform distribution conditions of the roundup are defined, and the roundup problem is formalized as a trajectory planning problem that satisfies a set of control constraints.

[0061] Output: The dynamic relationship model between the unmanned boat and the target and the mathematical description of the capture mission are obtained, providing a basis for the subsequent estimator and controller design.

[0062] Step 2 Design a distributed target center estimator

[0063] Introduce intermediate state variables and linear drive terms:

[0064] A distributed target center estimator is designed for each unmanned boat to drive the consistency error of the intermediate state variables to zero.

[0065] The estimator is guaranteed to be robust to initialization errors and can achieve target center estimation without specific initialization.

[0066] Apply the maximum consistency algorithm for gain design:

[0067] The gain is calculated independently based on local information, avoiding the problem of excessive gain caused by relying on global variables in traditional methods.

[0068] Using Lyapunov function analysis, it is proved that the estimation error can quickly converge to a small area within a finite time.

[0069] Output: The unmanned boat can obtain the position information of the target geometric center through the distributed target center estimator, providing input for controller design.

[0070] Step 3 Design a multi-target uniform capture controller

[0071] Formulate control strategies based on distributed estimation results:

[0072] The exclusion theory is used to construct an unmanned boat's control algorithm for capturing targets, ensuring that the targets are evenly distributed within the capture range.

[0073] The control signal of the unmanned boat is divided into a capture signal and a pursuit signal, which are composed of linear velocity and angular velocity respectively, so as to achieve stable capture of the target.

[0074] Ensure round-up stability and phase uniformity:

[0075] The tracking error and phase interval angle of the capture radius are defined, and the corresponding Lyapunov function is designed to analyze the system stability.

[0076] Verify the effectiveness of the capture controller when the target is in free motion and ensure that the phase difference converges to a uniform state of target distribution.

[0077] Output: Based on the results of the target center estimator, the multi-unmanned vehicle system achieves stable capture of multiple targets.

[0078] Step 4: Simulation verification

[0079] Set the simulation parameters and initial conditions:

[0080] Select the initial position, speed and safety radius of the unmanned boat and target for the capture mission.

[0081] Set the design parameters of the distributed estimator and control algorithm, including gain values, speed angles, etc.

[0082] Perform simulation experiments and verify the results:

[0083] Record key indicators such as unmanned boat capture trajectory, target center estimation error, distance error and phase error.

[0084] The simulation results were analyzed to verify the stability and accuracy of the multi-target system being successfully captured by the unmanned boat system.

[0085] Output: The simulation results show that the multi-unmanned boat collaborative control algorithm can effectively achieve uniform capture of multiple targets, verifying the feasibility and stability of the method.

[0086] Implementation Method 3: Combination Figure 1-7 This embodiment is described in detail by using specific examples to further describe the technical solution provided above. Specifically:

[0087] include:

[0088] Step (1): Consider a multi-unmanned boat system consisting of n unmanned boats. The nonlinear kinematic model of the i-th unmanned boat is expressed as

[0089]

[0090] Where (x i ,y i ) represents the position of the i-th unmanned boat, represents the yaw angle, u i , v i , r i Denote the forward speed, the drift speed and the yaw angular velocity respectively. Let η i =[x i ,y i ] T , i =[u i ,vi ] T .set up is the rotation matrix, defined as

[0091]

[0092] Then there is

[0093] Consider a multi-objective system consisting of l objectives, and the kinematic equation of the i-th objective is as follows:

[0094]

[0095] In the formula represents the position of the i-th target, represents the yaw angle, r i t Denote the forward speed, the drift speed and the yaw angular velocity respectively.

[0096] Define the target center as There is a positive constant satisfy Then the relative distance ρ between the i-th unmanned boat and the target center is i and the phase angle φ i It is expressed as:

[0097]

[0098] Multi-target uniform capture: Consider the above-mentioned multi-unmanned boat system and multi-target system. Figure 1 As shown, define ρ d is the pre-designed safe capture radius. If the following relationship is satisfied, the multi-target equal capture is successfully achieved:

[0099]

[0100] Step (2): First, design the distributed target center estimator as follows:

[0101]

[0102] Where i∈V l , θ1 is a positive constant. i is an intermediate state function, c i and represents the center position and speed of the target of the i-th unmanned boat, and then defines The following results are obtained:

[0103] Theorem 1: Consider the distributed target center estimator designed above. Each unmanned boat can estimate the target center of mass, and the estimation error converges to a small area in a finite time.

[0104] Proof: The first step is to define the Lyapunov function as follows:

[0105]

[0106] V e Taking the derivative, we have:

[0107]

[0108] Substituting the above estimator into V1, we have:

[0109]

[0110] In the formula, κ = 0.2785, combined with The definitions are:

[0111]

[0112] It can be further deduced that:

[0113]

[0114]

[0115] It can be written as:

[0116]

[0117] Choose a Lyapunov function The derivative is:

[0118]

[0119] Select a Lyapunov candidate function as V0 = V e +V θ , the derivative of V0 can be written as:

[0120]

[0121] This means Converges to a small region in a finite time, Converges to θ in finite time * .

[0122] In the second step, considering the above distributed target center estimator, we have:

[0123]

[0124] because Then there is And from the first step we can deduce c i =c j , then we have:

[0125]

[0126] Proof completed.

[0127] Then, a uniform capture controller based on a distributed target center estimator is designed. The control scheme of each unmanned boat is designed as follows:

[0128]

[0129] in k is an integer, is an ideal speed angle. and They are the capture signal and the chase signal, designed as follows:

[0130]

[0131] i=1,2,...,n,σ i ,i=1,2,...,n is the designed linear speed, and μ i ,i=1,2,...,n are design parameters. The following results are obtained:

[0132] Theorem 2: Considering the above-mentioned multi-unmanned boat system and multi-objective system, if the control scheme is designed as described above, the control objective of this paper is achieved.

[0133] Proof: Define the radius tracking error ρ e_i =ρ i -ρ d , ρ e_i The time derivative is:

[0134]

[0135] Then, it can be deduced that:

[0136]

[0137] in It can be further written as:

[0138]

[0139] in have:

[0140]

[0141] in Choose the Lyapunov function as V ρ The derivative of is:

[0142]

[0143] in is a positive constant, so:

[0144]

[0145] This means The phase interval angle is defined as:

[0146] γ 12 =φ1-φ2

[0147] γ 23 =φ2-φ3

[0148]

[0149] γ n1 =φ n -φ1+2π

[0150] The angle error can be expressed as:

[0151]

[0152] φ e_i The derivative of is:

[0153]

[0154] Further:

[0155]

[0156] Given the following Lyapunov function:

[0157]

[0158] It can be obtained if and only if φ e_1 =φ e_2 =... =φ e_n hour Using V e and φ e_i The boundedness of Therefore, the conclusion is

[0159] The proof is complete.

[0160] Step (3), numerical simulation is performed to demonstrate the effectiveness of the proposed control algorithm. Consider a multi-unmanned boat system consisting of three unmanned boats V l = {1, 2, 3} and a multi-objective system V t ={1,2,3}. The adjacency matrix between each unmanned boat is defined as The adjacency matrix between the unmanned boat and the target is defined as The initial position of each unmanned boat is expressed as The initial velocity is [u i (0),v i (0),r i (0)] = [0.01, 0, 0] T , i=1,2,3, the target’s trajectory is defined as

[0161]

[0162] The data related to the distributed target center estimator is defined as: θ1 = 1, and the parameter design of the multi-unmanned boat cooperative multi-target uniform capture control algorithm is as follows: ρ d =10, σ i =0.5, μ i =0.6, i=1,2,3. The simulation duration is selected as 300 seconds. Using the above parameter values, a simulation experiment is designed to verify the effectiveness of the proposed method. The simulation results are shown in the attached figure.

[0163] The simulation results of the proposed control algorithm are shown in Figure 2-7 The capture trajectory of the unmanned boat and the moving target is shown in Figure 2 As shown in Figure 2, it can be observed that the multi-target system was successfully captured by the multi-unmanned boat system. The time response of the consistency error of the distributed target center estimator is shown in Figure 2. Figure 3 The time response of the estimation error of the distributed target center estimator is shown as Figure 4 The mean square error of the target center estimation is 0.22. This shows that the algorithm proposed in this paper can effectively estimate the target center. The time response of the distance error is shown in Figure 5 As shown in Figure 1, it can be observed that the relative distance error converges to a small area. In order to show that the phase difference between each pair of unmanned boats converges to 2π / n, the phase difference curve is shown in Figure 1. Figure 6 The feasibility of phase control is verified as shown in Figure 2. The time response of the angle tracking error is shown in Figure 2. Figure 7 In summary, the experimental results demonstrate the effectiveness of the present invention.

[0164] The technical solution provided by the present invention is further described in detail above through several specific implementation modes in order to highlight the advantages and benefits of the technical solution provided by the present invention. However, the several specific implementation modes described above are not intended to be used as limitations on the present invention. Any reasonable modification and improvement of the present invention, combination of implementation modes and equivalent substitution within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for uniformly capturing multiple targets in coordination with multiple unmanned boats, characterized in that: include: Construct kinematic models of multi-UAV systems and multi-target systems, and define the steps for the target state of the capture mission; The step of establishing a distributed target center estimator based on the kinematic model and the target state; The step of constructing a capture controller according to the target geometric center information provided by the distributed target center estimator; Based on the control strategy of the capture controller, the angular velocity of the unmanned boat is adjusted to achieve the consistency of the phase interval angle; The steps of dynamically adjusting the parameters of the capture controller and outputting them to the multi-unmanned boat system.

2. The method for uniformly capturing multiple targets in coordination with multiple unmanned boats according to claim 1 is characterized in that: The distributed target center estimator eliminates the consistency error of the intermediate state variables through a linear driving term, and combines with the maximum consistency algorithm to allow each unmanned boat to independently calculate the gain based on local information.

3. The method for controlling the uniform capture of multiple targets by coordinating multiple unmanned boats according to claim 1 is characterized in that: The construction of the kinematic model of the multi-target system includes the geometric center of the target and its relative position and phase angle relationship with the unmanned boat.

4. The method for controlling the uniform capture of multiple targets by coordinating multiple unmanned boats according to claim 1 is characterized in that: The linear drive item of the distributed target center estimator achieves consistency based on iterative calculation of local adjacency relations, and is independently calculated based on a maximum consistency algorithm, and is adapted to different initial distribution conditions through dynamic adjustment.

5. The method for controlling the uniform capture of multiple targets by coordinating multiple unmanned boats according to claim 1 is characterized in that: The linear speed in the capture controller is designed by a proportional gain parameter, and the proportional gain parameter range is dynamically adjusted according to the relative distance between the unmanned boat and the target center.

6. The method for controlling the uniform capture of multiple targets by coordinating multiple unmanned boats according to claim 1 is characterized in that: The kinematic model of the multi-target system includes nonlinear trajectories of the targets, and the speed and angular velocity of the targets are set according to dynamic functions.

7. A multi-unmanned boat coordinated multi-target uniform capture control device, characterized in that: include: Construct kinematic models of multi-UAV systems and multi-target systems, and define modules for target states of capture missions; Based on the kinematic model and the target state, a module for establishing a distributed target center estimator is established; According to the target geometric center information provided by the distributed target center estimator, a module of the capture controller is constructed; A module for adjusting the angular velocity of the unmanned boat to achieve consistency of the phase interval angle based on the control strategy of the capture controller; Dynamically adjust the parameters of the capture controller and output them to the module of the multi-unmanned boat system.

8. A computer storage medium for storing a computing program, characterized in that: When the computer program is read by a computer, the computer executes the method of claim 1 .

9. A computer, comprising a processor and a storage medium, characterized in that: When the processor reads the computer program stored in the storage medium, the computer executes the method of claim 1 .

10. A computer program product, being a computer program, characterized in that When the computer program is executed, the method of claim 1 is implemented.

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