A safe consistent tracking method under distributed adaptive fault-tolerant control of heterogeneous multi-unmanned ship

Abstract

This invention discloses a safe and consistent tracking method for heterogeneous multi-unmanned surface vessels (USVs) under distributed adaptive fault-tolerant control, comprising the following steps: Step 1: Constructing an uncertain nonlinear system model of the heterogeneous multi-USVs; Step 2: Constructing a dynamic model of the heterogeneous multi-USVs under actuator failure and attack conditions; Step 3: Designing a distributed tracking estimator; Step 4: Designing a distributed tracking controller; Step 5: Using the distributed tracking estimator and distributed tracking controller to perform safe and consistent tracking of the heterogeneous multi-USVs under adaptive fault-tolerant control. This invention overcomes the shortcomings of existing control methods, effectively resisting the adverse effects of actuator failure and attacks, and enabling the tracking errors of the heterogeneous multi-USVs to converge to a small neighborhood near zero, providing crucial technical support for the stable operation and safe and consistent tracking of heterogeneous multi-USVs.

Description

Technical Field

[0001] This invention relates to the field of intelligent control, specifically to a safe and consistent tracking method under distributed adaptive fault-tolerant control of heterogeneous multi-unmanned vessel. Background Technology

[0002] Unmanned surface vessels (USVs) play a vital role in marine exploration, maritime rescue, and maritime transportation. Compared to a single USV, multiple USVs can significantly improve efficiency and combat capabilities when performing tasks. Consistent tracking refers to multiple USVs communicating with each other to ultimately achieve a unified goal, which can be applied to the control of multiple USV swarms to complete tasks such as patrol and search and rescue. Common control strategies include distributed control and centralized control. Distributed control assigns control tasks to individual USVs, and each USV controls itself based on the state information of its neighbors; centralized control uses a central controller to control the movement of all USVs. Compared to centralized control, distributed control methods have better system reliability and robustness, and can reduce communication burden, but they also need to overcome some difficulties, such as how to design appropriate control strategies and how to conduct information exchange and communication.

[0003] In practical applications, the control and navigation of unmanned surface vessels (USVs) face numerous challenges, such as changes in sea state, equipment failures, and external attacks. External disturbances like wind, waves, and ocean currents can affect the movement of USVs; aging actuators or other mechanical failures can lead to decreased control precision; and threats from external attacks, such as cyberattacks and physical attacks, can cause USVs to lose control. These challenges require solutions through advanced control algorithms and technologies.

[0004] Currently, there are very few results on the safe and consistent tracking and control of heterogeneous multi-unmanned vessels, especially considering the actual situation of sea state changes, equipment failures, external attacks, etc. Therefore, it remains an important issue in this field. Summary of the Invention

[0005] The purpose of this invention is to provide a safe and consistent tracking control method under distributed adaptive fault-tolerant control for heterogeneous multi-unmanned surface vessels. The proposed controller can guarantee that the tracking errors of heterogeneous multi-unmanned surface vessels converge to a small neighborhood near zero. By considering heterogeneity, nonlinear uncertainty, external disturbances, actuator failures, and external attacks, it has broad applicability.

[0006] This invention first provides a safe and consistent tracking method under distributed adaptive fault-tolerant control for heterogeneous multi-unmanned surface vessels, including:

[0007] Step 1: Construct an uncertain nonlinear system model of heterogeneous multi-unmanned vessels; the system model includes a dynamic model and a kinematic model of heterogeneous multi-unmanned vessels.

[0008] Step 2: Construct a heterogeneous multi-unmanned vessel dynamics model under actuator failure and attack conditions based on the uncertain nonlinear system model;

[0009] Step 3: Based on the communication topology of heterogeneous multi-unmanned vessel, construct a distributed tracking estimator, which is used to generate the expected trajectory of each unmanned vessel;

[0010] Step 4: Based on the heterogeneous multi-unmanned vessel dynamics model and distributed tracking estimator under actuator failure and attack, a distributed tracking controller is constructed. The distributed tracking controller is used to control each unmanned vessel and make the unmanned vessel track the corresponding desired trajectory.

[0011] Step 5: Use the distributed tracking estimator and distributed tracking controller to perform safe and consistent tracking of the heterogeneous multi-unmanned vessel under adaptive fault-tolerant control.

[0012] The present invention also provides a control device for the above-described secure consistency tracking method, comprising:

[0013] The first building block is used to construct an uncertain nonlinear dynamic model of heterogeneous multi-unmanned vessels;

[0014] The second building module is used to construct a heterogeneous multi-unmanned vessel dynamics model under actuator failure and attack based on an uncertain nonlinear system model.

[0015] The third building module is used to build a distributed tracking estimator based on the communication topology of heterogeneous multi-unmanned vessels;

[0016] The fourth building block is used to construct a distributed tracking controller based on the heterogeneous multi-unmanned vessel dynamics model and distributed tracking estimator under actuator failure and attack conditions;

[0017] The control module is used to perform safe and consistent tracking control of the heterogeneous multi-unmanned vessel under adaptive fault-tolerant control using the distributed tracking estimator and the decentralized tracking controller.

[0018] The present invention also provides an electronic device, comprising:

[0019] Memory, used to store programs;

[0020] A processor is used to execute programs stored in memory;

[0021] When the program is executed by the processor, it implements the aforementioned safe and consistent tracking method under the distributed adaptive fault-tolerant control of heterogeneous multi-unmanned vessel.

[0022] The present invention further provides a computer-readable storage medium storing computer instructions that, when executed by a processor, implement the above-described safe and consistent tracking method under distributed adaptive fault-tolerant control for heterogeneous multi-unmanned vessels.

[0023] Compared with the prior art, the present invention has the following beneficial effects:

[0024] 1) This invention considers the uncertain nonlinear system modeling of heterogeneous multi-unmanned surface vessels (USVs) and takes into account the impact of environmental disturbances, actuator failures, and external attacks. Based on the communication topology, a distributed tracking estimator is designed to generate the desired trajectory for each USV, and a distributed tracking controller is designed to enable each USV to track its own desired trajectory. This controller has adaptive and fault-tolerant characteristics, exhibiting extremely high robustness and reliability. Adaptability means that the controller can automatically adjust the control strategy to maintain system stability according to changes in the external environment and can adapt to changes and intensities of external disturbances. Fault tolerance means that the controller can still maintain system control capability in the event of actuator failure and attacks, ensuring system stability and security, thereby improving the distributed, safe, and consistent tracking capability of heterogeneous multi-USVs.

[0025] 2) The distributed control method of this invention enables the system to have better reliability and robustness, and can reduce the communication burden. At the same time, it can effectively resist the adverse effects of actuator failure and attacks, and can realize that the tracking errors of heterogeneous unmanned vessels can all converge to a small neighborhood near zero, providing key technical support for the stable operation and safe and consistent tracking of heterogeneous unmanned vessels.

[0026] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and do not limit this application. Attached Figure Description

[0027] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0028] Figure 1 This is a flowchart illustrating a safe and consistent tracking method under distributed adaptive fault-tolerant control for heterogeneous multi-unmanned vessel systems, according to an exemplary embodiment.

[0029] Figure 2 This is a schematic diagram of the communication topology of heterogeneous multi-unmanned vessel according to an embodiment of the present invention.

[0030] Figure 3 This is a trajectory change diagram of the leader and four heterogeneous unmanned vessels under distributed adaptive fault-tolerant control, an embodiment of the present invention.

[0031] Figure 4This is a schematic diagram illustrating the changes in the horizontal coordinates of the leader and four heterogeneous unmanned vessels under distributed adaptive fault-tolerant control, as well as the horizontal coordinate tracking errors of each unmanned vessel and the leader, according to an embodiment of the present invention.

[0032] Figure 5 This is a schematic diagram showing the changes in the longitudinal coordinates of the leader and four heterogeneous unmanned vessels under distributed adaptive fault-tolerant control, as well as the longitudinal coordinate tracking errors of each unmanned vessel and the leader, according to an embodiment of the present invention.

[0033] Figure 6 This is a schematic diagram illustrating the yaw angle changes of the leader and four heterogeneous unmanned vessels under distributed adaptive fault-tolerant control, as well as the yaw angle tracking errors of each unmanned vessel and the leader, according to an embodiment of the present invention.

[0034] Figure 7 This is a block diagram of a safe and consistent tracking control device under distributed adaptive fault-tolerant control for heterogeneous multi-unmanned vessel, according to an exemplary embodiment. Detailed Implementation

[0035] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. In the following description relating to the drawings, unless otherwise indicated, the same numerals in different drawings denote the same or similar elements.

[0036] The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0037] The terminology used in this application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. The singular forms “a,” “the,” and “the” used in this application and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used herein refers to and includes any or all possible combinations of one or more of the associated listed items.

[0038] It should be understood that although the terms first, second, third, etc., may be used in this application to describe various information, such information should not be limited to these terms. These terms are only used to distinguish information of the same type from one another. For example, without departing from the scope of this application, first information may also be referred to as second information, and similarly, second information may also be referred to as first information. Depending on the context, the word "if" as used herein may be interpreted as "when," "when," or "in response to determination."

[0039] Figure 1This is a flowchart illustrating a safe and consistent tracking method under distributed adaptive fault-tolerant control for heterogeneous multi-unmanned surface vessels, according to an exemplary embodiment. Figure 1 As shown, the method may include the following steps:

[0040] S1: Construct an uncertain nonlinear system model of heterogeneous multi-unmanned ships, including a dynamic model and a kinematic model of heterogeneous multi-unmanned ships;

[0041] The kinematic model of heterogeneous unmanned surface vessels is represented as follows:

[0042]

[0043] η i =[x i ,y i ,ψ i ] T

[0044]

[0045] The heterogeneous multi-unmanned vessel dynamics model is expressed as follows:

[0046]

[0047] Where i represents the i-th unmanned vessel, i∈{1,2,...,N}, and the system has a total of N unmanned vessels, η i =[x i ,y i ,ψ i ] T Let x represent the position vector of the unmanned vessel in the Earth's fixed inertial frame. i ,y i ,ψ i These represent the x-axis, y-axis, and yaw angle, respectively. Represents the position vector η i The derivative with respect to time, υ i =[u i ,v i ,r i ] T Let u represent the velocity vector of the unmanned vessel in the Earth's fixed inertial frame. i ,v i ,r i J represents the longitudinal velocity, lateral drift velocity, and bow roll rate, respectively. i (η i ) represents the rotation matrix. Represents the velocity vector υ i The derivative with respect to time, M i ∈R 3×3 C i (υi )∈R 3×3 D i (υ i )∈R 3×3 Let represent the inertia matrix, Coriolis centripetal force matrix, and fluid damping matrix of the unmanned vessel, respectively. τ represents the actual driving force experienced by the unmanned vessel. Ei τ represents the vector of environmental disturbances caused by wind, waves, and ocean currents. Ei The upper bound exists but is unknown. The heterogeneous multi-unmanned vessel kinematic model is not affected by actuator failures and attacks.

[0048] S2: Construct a heterogeneous multi-unmanned vessel dynamics model under actuator failure and attack based on an uncertain nonlinear system model;

[0049] In the specific implementation of S2: a heterogeneous multi-unmanned vessel dynamics model under actuator failure and attack is constructed based on an uncertain nonlinear system model;

[0050] Consider modeling actuator faults as a linear model, which often occurs when there is wear or failure in the actuator's transmission system:

[0051]

[0052] Where ρ = 1, 2, 3 correspond to the driving forces in the three dimensions of longitudinal velocity, lateral drift velocity, and yaw rate, respectively. τ represents the driving force experienced by the unmanned surface vessel when an actuator fails. i =[τ 1,i ,τ 2,i ,τ 3,i ] T h represents the driving force experienced by the unmanned surface vessel under normal conditions and under attack. ρ,i This represents the actuator failure coefficient, which has unknown upper and lower bounds that satisfy... The fault deviation is time-varying, and it is bounded but unknown.

[0053] Meanwhile, since multiple unmanned surface vessel (USV) systems need to communicate with each other to exchange information, the possibility of external attacks on the USVs is considered. The attack signal is modeled as f. i =n i υ i n i υ is an unknown constant. i Let n be the velocity vector. i v i This constitutes the attack force. Considering the simultaneous occurrence of actuator malfunction and attack, the actual driving force experienced by the unmanned surface vessel is re-expressed as:

[0054]

[0055] Among them, H i =diag{h 1,i ,h 2,i ,h 3,i}, Δτ i =[Δτ 1,i ,Δτ 2,i ,Δτ 3,i ] T ;

[0056] Therefore, the dynamic model under actuator failure and attack can be expressed as:

[0057]

[0058] S3: Based on the communication topology of heterogeneous multi-unmanned vessels, a distributed tracking estimator is designed, which is used to generate the expected trajectory of each unmanned vessel.

[0059] In the specific implementation of S3: a distributed tracking estimator is designed based on the communication topology of heterogeneous multi-unmanned vessels;

[0060] Design a virtual leader to generate a reference tracking trajectory. The virtual leader's position vector is η0 = [x0, y0, ψ0]. T Where x0, y0, and ψ0 represent the horizontal coordinate, vertical coordinate, and yaw angle of the virtual leader, respectively. Let η0 be the derivative of the virtual leader's position vector with respect to time, which satisfies:

[0061]

[0062] Where A∈R 3×3 It is a known constant matrix.

[0063] Considering that not all unmanned surface vessels (USVs) can directly obtain the leader's information, an assumption needs to be made about the communication topology to ensure that each USV can obtain the leader's information. This communication topology can be represented by a graph, where node 0 represents the virtual leader, nodes 1 through N represent USVs, and edges represent communication connections between USVs. ij This is used to represent the weight of the edge from node i to node j. If there is a communication connection between the two unmanned vessels, then a ij >0, otherwise 0. Assume the communication topology can be divided into a directed spanning tree rooted at the leader, meaning each unmanned vessel can obtain the leader's information from the root node through a directed path.

[0064] The distributed tracking estimator is designed as follows:

[0065]

[0066] Where c is the given coupling gain, Let represent the expected position vector of the i-th unmanned vessel. Represents the desired position vector The derivative with respect to time.

[0067] The distributed tracking estimator is designed so that each unmanned vessel can estimate the information of the leader and generate a desired trajectory for consistent tracking, thus obtaining a reference trajectory for the tracking controller.

[0068] S4: Based on the heterogeneous multi-unmanned vessel dynamics model and distributed tracking estimator under actuator failure and attack, a distributed tracking controller is designed. The distributed tracking controller is used to control each unmanned vessel and make the unmanned vessel track the corresponding desired trajectory.

[0069] In the specific implementation of S4: Based on the heterogeneous multi-unmanned vessel dynamics model and distributed tracking estimator under actuator failure and attack, a distributed tracking controller is designed;

[0070] Define tracking error z 1,i The expression is:

[0071]

[0072] Tracking error z 1,i The expression for the derivative with respect to time is:

[0073]

[0074] Among them, υ i It is a velocity vector, which can be regarded as a virtual control input.

[0075] Define tracking error z 2,i The expression is:

[0076]

[0077] in, K 1,i It is a positive definite diagonal matrix.

[0078] Because J i (η i )J i T (η i ) = I, we can get:

[0079]

[0080] Taking the derivative with respect to time, we get:

[0081]

[0082] The distributed tracking controller is designed as follows:

[0083]

[0084] Where, γ i For variables whose initial values ​​are known, satisfying m i Given a positive constant, ||z 2,i ||2 represents z 2,i 2-norm, K 2,i Given a positive definite diagonal matrix, Indicates that for n i The estimator satisfies d i Given a positive constant, Controller output τ i This is equivalent to the original output, which will change under faults and attacks. The changed output is the actual driving force.

[0085] The distributed tracking controller design enables each unmanned surface vessel (USV) to track a reference trajectory. Because the reference trajectory is consistently tracked, each USV also achieves consistent tracking control.

[0086] S5: The distributed tracking estimator and distributed tracking controller are used to perform safe and consistent tracking of the heterogeneous multi-unmanned vessel under adaptive fault-tolerant control.

[0087] In the specific implementation of S5: the distributed tracking estimator and the distributed tracking controller are used to perform safe and consistent tracking of the heterogeneous multi-unmanned vessel under adaptive fault-tolerant control.

[0088] The effectiveness of the proposed method was verified through simulation.

[0089] Figure 2 The diagram shows the heterogeneous multi-unmanned vessel communication topology used in the simulation. Node 0 represents the virtual leader, nodes 1 to 4 represent unmanned vessels, and edges represent the communication connections between unmanned vessels.

[0090] Set the navigator's trajectory as follows:

[0091]

[0092] Four heterogeneous unmanned surface vessels were selected, i∈{1,2,3,4}, and their model parameters are as follows:

[0093]

[0094]

[0095]

[0096]

[0097]

[0098]

[0099] τ Ei =[sin(x i ),cos(y i )sin(ψ i ),e -t sin(ψ i )] T ;

[0100]

[0101] where, d 11,1 =0.7225+1.3274|u1|+5.8664u1 2 , d 22,1 =0.8612+36.2823|v1|+8.05|r1|, d 23,1 =-0.1079+0.845|v1|+3.45|r1|, d 32,1 =-0.1052-5.0437|v1|-0.13|r1|, d 33,i =1.9-0.08|v1|+0.75|r1|; d 11,2 =0305+0.5576|u2|+5.8664u2 2 , d 22,2 =0.3617+36.2823|v2|+8.05|r2|, d 23,2 =-0.1079+0.845|v2|+3.45|r2|, d 32,2 =-0.0442-5.0437|v2|-0.13|r2|, d 33,2 =1.9-0.08|v2|+0.75|r2|; d 11,3 =1+2|u3|+5.8664u3 2 , d 22,3 =1.3214+36.2823|v3|+8.05|r3|, d 23,3 =-0.1079+0.845|v3|+3.45|r3|, d 32,3 =-0.1578-5.0437|v3|-0.13|r3|, d 33,3 =1.9-0.08|v3|+0.75|r3|; d 11,4=1.5211+2.7875|u4|+5.8664u4 2 d 32,4 =-0.2209-5.0437|v4|-0.13|r4|,d 33,4 =1.9 - 0.08|v4| + 0.75|r4|;

[0102] The initial value is set to: η0(0)=[0.1,1,0.1] T η1(0)=[-0.6,1.2,0.1] T η2(0)=[-0.2,0.9,0] T η3(0)=[-0.5,1.3,0.15] T η4(0)=[-0.4,0.8,0.1] T ,υ i =[1,1,1] T ;

[0103] The attack modeling parameter is n i =1; Actuator fault modeling parameters are Δτ i =[0.1sin(t),0.2cos(t),0.3e -t ] T ;

[0104] c = 2, m i =50,d i =1.

[0105] Figure 3 The diagram shows the coordinate changes of the leader and the heterogeneous unmanned vessels. The leader moves along a circular trajectory, and unmanned vessels 1 to 4 complete consistent tracking of the leader from different starting points. Figure 4 The diagram shows the horizontal coordinates and tracking errors of the leader and heterogeneous unmanned surface vessels. The upper part describes the changes in the horizontal coordinates of the unmanned surface vessels, and the lower part shows the tracking error of the horizontal coordinates. As time goes by, the tracking error quickly converges to near zero. Figure 5 The diagram shows the longitudinal coordinates and tracking errors of the leader and the heterogeneous multi-unmanned surface vessels. The upper part describes the changes in the longitudinal coordinates of the unmanned surface vessels, and the lower part shows the tracking error of the longitudinal coordinates. As time goes by, the tracking error quickly converges to near zero. Figure 6The diagram illustrates the heading angle and tracking error of the leader and heterogeneous multi-unmanned surface vessels (USVs). The upper part depicts the heading angle changes of the USVs, while the lower part shows the tracking error. Over time, the tracking error quickly converges to near zero. These results demonstrate that in heterogeneous multi-USV systems, the safe and consistent tracking method under distributed adaptive fault-tolerant control proposed in this invention can overcome the adverse effects of actuator failures and attacks, ensuring the safe and stable operation of the system. Therefore, the distributed adaptive fault-tolerant control method proposed in this invention has significant practical application value in heterogeneous multi-USV consistent tracking systems.

[0106] Corresponding to the aforementioned embodiment of the safe consistent tracking method under distributed adaptive fault-tolerant control for heterogeneous multi-unmanned surface vessels, this application also provides a block diagram of a safe consistent tracking control device under distributed adaptive fault-tolerant control for heterogeneous multi-unmanned surface vessels. (Refer to...) Figure 7 The device includes:

[0107] The first building module is used to construct an uncertain and nonlinear system model of heterogeneous multi-unmanned vessels;

[0108] The second building module is used to build a heterogeneous multi-unmanned vessel dynamics model under actuator failure and attack conditions;

[0109] The third building block is used to build a distributed tracking estimator;

[0110] The fourth building block is used to build a distributed tracking controller;

[0111] The control module is used to perform safe and consistent tracking control of the heterogeneous multi-unmanned vessel under adaptive fault-tolerant control using the distributed tracking estimator and the decentralized tracking controller.

[0112] Accordingly, this application also provides an electronic device, including: one or more processors; a memory 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 implement the safety control method of the above-described safe consistent tracking method under the distributed adaptive fault-tolerant control of heterogeneous multi-unmanned vessel.

[0113] Accordingly, this application also provides a computer-readable storage medium storing computer instructions that, when executed by a processor, implement the security control method described above for a safe and consistent tracking method under distributed adaptive fault-tolerant control of heterogeneous multi-unmanned vessels.

[0114] Regarding the apparatus in the above embodiments, the specific manner in which each module performs its operation has been described in detail in the embodiments related to the method, and will not be elaborated upon here.

[0115] For the apparatus embodiments, since they basically correspond to the method embodiments, the relevant parts can be referred to in the description of the method embodiments. The apparatus embodiments described above are merely illustrative, and the units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units. Some or all of the modules can be selected to achieve the purpose of this application according to actual needs. Those skilled in the art can understand and implement this without creative effort.

[0116] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the disclosure herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein. The specification and embodiments are to be considered exemplary only, and the true scope and spirit of this application are indicated by the claims.

[0117] This invention is not limited to the above embodiments. Based on the technical solutions disclosed herein, those skilled in the art can make some substitutions and modifications to some of the technical features without creative effort, and all such substitutions and modifications are within the protection scope of this invention.

Claims

1. A safe and consistent tracking method under distributed adaptive fault-tolerant control of a heterogeneous multi-unmanned ship, characterized in that, include: Step 1: Construct an uncertain nonlinear system model of heterogeneous multi-unmanned vessels; The system model includes a heterogeneous multi-unmanned vessel dynamics model and a heterogeneous multi-unmanned vessel kinematics model; Step 2: Construct a heterogeneous multi-unmanned vessel dynamics model under actuator failure and attack conditions based on the uncertain nonlinear system model; The kinematic model of heterogeneous multi-unmanned vessels is not affected by actuator failures and attacks; Step 3: Based on the communication topology of heterogeneous multi-unmanned vessel, construct a distributed tracking estimator, which is used to generate the expected trajectory of each unmanned vessel; Specifically, a virtual leader is additionally set up in the communication topology. This virtual leader is used to generate a reference tracking trajectory. The unmanned surface vessel (USV) obtains information about the virtual leader through the communication topology. Based on the heterogeneous multi-USV communication topology, a distributed tracking estimator is constructed. ； in, Representing the An unmanned boat, The system has a total of N unmanned boats; Given a constant matrix, For a given coupling gain, Let represent the expected position vector of the i-th unmanned vessel. Represents the desired position vector The derivative with respect to time, Let be the weight of the edge from the i-th unmanned surface vessel (USV) node to the j-th USV node in the communication topology. Let be the weight of the edge from the i-th unmanned boat node to the virtual leader in the communication topology. Represents the position vector of the virtual leader; Step 4: Based on the heterogeneous multi-unmanned surface vessel (USV) kinematic model, the heterogeneous multi-USV dynamics model under actuator failure and attack, and the distributed tracking estimator, a distributed tracking controller is constructed. This distributed tracking controller controls each USV and enables it to track the corresponding desired trajectory. The distributed tracking controller is represented as follows: ； ； ； ； ； in, , , Let represent the inertia matrix, Coriolis centripetal force matrix, and fluid damping matrix of the unmanned vessel, respectively. This represents the position vector of the unmanned vessel in the Earth's fixed inertial frame. This represents the velocity vector of the unmanned vessel in the Earth's fixed inertial frame. These represent longitudinal velocity, lateral drift velocity, and bow roll rate, respectively. and For tracking error; Represents the rotation matrix. express The derivative with respect to time; For variables whose initial values ​​are known, satisfying , Given a positive constant, express 2-norm; For unknown constants, Indicates to The estimator satisfies , Given a positive constant; Given a positive definite diagonal matrix; Step 5: Use the distributed tracking estimator and distributed tracking controller to perform safe and consistent tracking of the heterogeneous multi-unmanned vessel under adaptive fault-tolerant control.

2. The secure consistency tracking method according to claim 1, characterized in that, In step 1, an uncertain nonlinear system model of heterogeneous multi-unmanned vessels is constructed. The dynamic model of the heterogeneous multi-unmanned vessels is as follows: ； The kinematic model of heterogeneous unmanned surface vessels is as follows: ； ； ； in, Representing the An unmanned boat, There are a total of N unmanned boats. This represents the position vector of the unmanned vessel in the Earth's fixed inertial frame. These represent the x-axis, y-axis, and yaw angle, respectively. Represents position vector The derivative with respect to time, This represents the velocity vector of the unmanned vessel in the Earth's fixed inertial frame. These represent longitudinal velocity, lateral drift velocity, and bow roll rate, respectively. Represents the rotation matrix. Represents the velocity vector The derivative with respect to time, , , Let represent the inertia matrix, Coriolis centripetal force matrix, and fluid damping matrix of the unmanned vessel, respectively. This indicates the actual driving force experienced by the unmanned surface vessel. This represents the vector of environmental disturbances caused by wind, waves, and ocean currents. The upper bound exists, but the upper bound is unknown.

3. The secure consistency tracking method according to claim 2, characterized in that, The heterogeneous multi-unmanned vessel dynamics model under actuator failure and attack in step S2 is expressed as follows: ； in, The actuator failure coefficient matrix, The driving force experienced by the unmanned vessel under fault-free and attack-free conditions. It is an unknown constant.

4. The secure consistency tracking method according to claim 3, characterized in that, In the heterogeneous multi-unmanned vessel dynamics model described in step 2, the driving force affected by actuator failure is expressed as: ； in Representing the An unmanned boat, The system has a total of N unmanned boats. These correspond to the driving forces in the three dimensions of longitudinal velocity, lateral drift velocity, and yaw rate, respectively. This indicates the driving force experienced by the unmanned surface vessel when an actuator fails. This indicates the driving force experienced by the unmanned surface vessel under normal conditions and under attack. This represents the actuator failure coefficient, which has unknown upper and lower bounds that satisfy... , This is the lower bound of the actuator failure coefficient. This is the upper bound of the actuator failure coefficient; The fault deviation is time-varying, and it is bounded but unknown.

5. The secure consistency tracking method according to claim 4, characterized in that, In the heterogeneous multi-unmanned vessel dynamics model described in step 2, the driving force under the condition of simultaneous actuator failure and attack is expressed as: ； ； in, This is an attack signal. For unknown constants, It is the velocity vector; ; .

6. A control device based on the secure consistency tracking method of claim 1, characterized in that, include: The first building module is used to construct an uncertain and nonlinear system model of heterogeneous multi-unmanned vessels; The second building module is used to construct a heterogeneous multi-unmanned vessel dynamics model under actuator failure and attack based on an uncertain nonlinear system model. The third building module is used to build a distributed tracking estimator based on the communication topology of heterogeneous multi-unmanned vessels; The fourth building block is used to construct a distributed tracking controller based on the heterogeneous multi-unmanned vessel dynamics model and distributed tracking estimator under actuator failure and attack conditions; The control module is used to perform safe and consistent tracking control of the heterogeneous multi-unmanned vessel under adaptive fault-tolerant control using the distributed tracking estimator and the decentralized tracking controller.

7. An electronic device, characterized in that, include: Memory, used to store programs; A processor is used to execute programs stored in memory; When the program is executed by the processor, it implements the method described in any one of claims 1-5.

8. A computer-readable storage medium storing computer instructions thereon, characterized in that, When the computer instructions are executed by the processor, they implement the steps of the method according to any one of claims 1-5.

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