Multi-unmanned ship preset time cooperative formation control method and system and medium

Abstract

This invention belongs to the field of unmanned surface navigation technology, and particularly relates to a method, system, and medium for pre-defined time-based cooperative formation control of multiple unmanned surface vessels (USVs) with error constraints. The method includes: first, establishing kinematic and dynamic models of the USVs; then, combining virtual structure and leader-follower methods to establish a virtual leader-follower formation control framework, and designing a pre-defined time-based disturbance observer to observe disturbances; finally, designing a pre-defined time function and a pre-defined performance inequality to design a pre-defined time-based formation control protocol. The controller designed in this invention enables USVs to perform formation tasks within a preset time. Furthermore, the pre-defined time-based disturbance observer observes and compensates for external disturbances, exhibiting strong robustness and anti-interference capabilities. Compared to existing finite-time formation controllers, the controller of this invention does not exhibit chattering and its convergence performance is independent of the initial state; compared to fixed-time formation controllers, the system convergence time can be manually set, improving formation control efficiency.

Description

Technical Field

[0001] This invention belongs to the field of unmanned surface navigation technology, and particularly relates to a method for pre-set time collaborative formation control of multiple unmanned surface vessels with error constraints. Background Technology

[0002] In recent years, with the rapid development of unmanned surface vessel (USV) technology, maritime missions have become increasingly complex. USV collaborative formations, with their advantages of flexible deployment, rapid mission response, high reliability, and good fault tolerance, have attracted the attention of maritime departments and researchers worldwide. Compared to traditional single USV systems, multi-USV formations offer significant improvements in reliability, mission complexity and diversity, functional scalability, and mission success rate, making them an important direction for future USV technology development. Traditional USV formation control technologies either only consider the asymptotic stability of the system or the stability performance of the formation system within a limited or fixed timeframe, failing to achieve system stability within a pre-set timeframe. This obviously increases the difficulty of actual mission execution and reduces the efficiency and control accuracy of USV formation missions. Furthermore, some complex maritime missions, such as anti-submarine warfare, mine countermeasures, and maritime military reconnaissance, place even higher demands on the control accuracy and convergence speed of USV collaborative formations. Furthermore, system settling time and convergence error are two crucial performance indicators for formation control systems. A shorter settling time indicates a faster control system response, while a smaller convergence error signifies higher convergence accuracy. However, existing surface unmanned surface vessel (USV) formation cooperative control technologies mostly focus on formation stability, rarely considering system convergence time and accuracy. As maritime missions become increasingly complex and the demands on vehicles rise, the convergence time and convergence error of USV formations are receiving increasing attention. Therefore, achieving stable distributed cooperative formation control of USVs within a preset timeframe is a challenging and worthy area of ​​research.

[0003] For example, patent application number CN202111050090.1 invented an adaptive backstepping sliding mode multi-unmanned surface vessel (USV) formation control method based on sampling communication, but it can only guarantee the asymptotic stability of the system and cannot achieve convergence of the USV formation within a finite time. Patent application number CN202110144673.4 invented a multi-USV formation control method based on fixed-time terminal sliding mode. Although this method can enable the system to converge within a fixed time, the upper bound of its maximum convergence time depends on the system itself and related control parameters, and the convergence time cannot be set manually.

[0004] Based on the above analysis, the problems and defects of the existing technology are as follows: most of the existing surface unmanned surface vessel formation cooperative control technologies only focus on the formation stability problem, and rarely consider the system convergence time and convergence accuracy, as well as whether the system convergence time can be set manually. Summary of the Invention

[0005] To address the problems existing in the prior art, this invention provides a multi-unmanned surface vessel (USV) pre-set time cooperative formation control method with error constraints.

[0006] This invention is implemented as follows: a multi-unmanned surface vessel (USV) pre-set time cooperative formation control method with error constraints, comprising:

[0007] S1: Establish kinematic and dynamic models of unmanned surface vessels;

[0008] S2: Combine the virtual structure method and the leader-follower method to establish a virtual leader-follower formation control framework;

[0009] S3: Design a preset time disturbance observer to observe disturbances;

[0010] S4: Design a preset time function and a preset performance inequality, and design a preset time formation control protocol.

[0011] Furthermore, S1 specifically includes:

[0012] The motion and dynamics model of the i-th unmanned surface vessel can be represented as follows:

[0013]

[0014] Where, η i =[x i ,y i ,ψ i ] T ∈R m Let v represent the pose vector of the unmanned surface vessel in the inertial coordinate system. i =[u i ,v i ,r i ] T Represents the velocity vector of the unmanned surface vessel in the attached coordinate system; Coriolis matrix C(v i ), hydrodynamic damping matrix D(v i ), and the inertia matrix M i The following is an expression:

[0015]

[0016]

[0017]

[0018] Coordinate system transformation matrix R i (ψ i This can be represented as:

[0019]

[0020] F(τ i ) is the saturation function of the control input of the i-th unmanned surface vessel, where τ i =[τ iu ,τ iv ,τ ir ] T ,F(τ i )=τ i, max tanh(τ i / τ i,max ), τ i,max It is the saturation threshold. d i This represents the external ocean interference experienced by the i-th unmanned surface vessel.

[0021] Furthermore, S2 specifically includes:

[0022] Virtual followers are set up to follow the leader. Real followers only need to reach the virtual follower's position and maintain their position to achieve formation control. The formation configuration of the virtual follower and the navigator is determined by vectors. The determination, of which: lateral distance Longitudinal distance In the inertial coordinate system, the virtual follower and the navigator have the following pose relationship:

[0023]

[0024] The above equation can be written in the following compact vector form.

[0025] η v =η l +R(ψ l )L;

[0026] Where, L=[d x ,d y ,0],η l =[x l ,y l ,ψ l ] T Represents the leader's pose vector; η v =[x v ,y v ,ψ v ] TThis represents the pose vector of the virtual follower. The virtual follower replaces the real navigator as a reference for the follower. When the follower reaches the position of the virtual navigator, it means that the formation is in the desired motion state. At this time, the follower and the navigator maintain a predetermined distance and angle, which means that formation control is achieved.

[0027] Furthermore, S3 specifically includes:

[0028] In order to observe and compensate for external disturbances within a predetermined time, a preset time disturbance observer is designed:

[0029]

[0030] Where K0 and C0∈R 3×3 It is a positive definite matrix. This represents the estimate of the disturbance, with an estimation error of . C0 satisfies

[0031] in T > 0 is a positive design parameter, ξ ∈ R 3 These are auxiliary state variables of the perturbation observer, updated by the following adaptive law:

[0032]

[0033] Where δ is a design parameter and satisfies

[0034] Furthermore, S4 specifically includes:

[0035] Design a predefined time-based formation controller based on an observer and preset performance control, and define the desired trajectory η. vi =[x vi ,y vi ,ψ vi ] T The tracking error is further defined as e 1i =x i -x vi e 2i =y i -y vi e 3i =ψ i -ψ vi The present invention aims to develop an effective control scheme that limits transient tracking error within a pre-set boundary.

[0036] -e ji,l <e ji <e ji,u j = 1, 2, 3; i = 1, ..., n;

[0037] Among them, eji,l and e ji,u Let represent the lower and upper limits of the tracking error, respectively. The following error transformation is then introduced:

[0038]

[0039] Differentiating the above equation, we get:

[0040]

[0041]

[0042]

[0043] The above expression can be written in compact vector form:

[0044]

[0045] Consider Lyapunov functions Differentiation yields:

[0046]

[0047] Assuming v is a virtual control signal, the following virtual control law is selected:

[0048]

[0049] Furthermore, S4 also includes:

[0050] Define the speed tracking error vector z2 = v - α and set the virtual control law α i Substituting, we get:

[0051]

[0052] To achieve predefined time tracking, the dynamic control law is designed as follows:

[0053]

[0054] in,

[0055] Another objective of this invention is to provide an error-constrained multi-unmanned surface vessel (USV) pre-time cooperative formation control system that applies the aforementioned error-constrained multi-USV pre-time cooperative formation control method. The error-constrained multi-USV pre-time cooperative formation control system includes:

[0056] The model building module is used to build kinematic and dynamic models of unmanned surface vessels.

[0057] The framework building module is used to combine the virtual structure method and the leader-follower method to build a virtual leader-follower formation control framework;

[0058] The disturbance observation module is used to design a disturbance observer that observes disturbances at a preset time.

[0059] The formation control module is used to design preset time functions and preset performance inequalities, and to design preset time formation control protocols.

[0060] Another object of the present invention is to provide a computer device, the computer device including a memory and a processor, the memory storing a computer program, and when the computer program is executed by the processor, causing the processor to perform the steps of the multi-unmanned surface vessel pre-time cooperative formation control with error constraints.

[0061] Another object of the present invention is to provide a computer-readable storage medium storing a computer program, which, when executed by a processor, causes the processor to perform the steps of the multi-unmanned surface vessel pre-time cooperative formation control method with error constraints.

[0062] Another objective of this invention is to provide an information data processing terminal for implementing the aforementioned multi-unmanned surface vessel pre-set time collaborative formation control system with error constraints.

[0063] Based on the above technical solutions and the technical problems solved, the advantages and positive effects of the technical solution to be protected by this invention are as follows:

[0064] Firstly, addressing the problem of poor control performance of multi-unmanned surface vessel (USV) formations under external disturbances in existing technologies, this invention proposes a preset-time disturbance observer. This observer can quickly observe and compensate for disturbances within a specified time, exhibiting strong robustness and anti-interference capabilities. For example... Figures 9-10 As shown, the observer's observation error converges to zero within a specified time, indicating that the designed disturbance observer can accurately observe disturbances within the specified time. Furthermore, to achieve satisfactory formation error constraints, a preset performance function is proposed. Combined with error transformation, this function can strictly limit the convergence time and convergence range, improving the transient performance of formation error. Figure 3 and Figure 4 The figures show the trajectory tracking errors of the two following unmanned surface vessels (USVs). As can be seen from the figures, the transient error values ​​in the initial stage are contained within the preset performance envelope, ensuring the transient performance of the system. Finally, by combining backstepping control technology, a kinematic and dynamic controller is designed to achieve formation control of multiple USVs with preset time and performance. Figure 7 and Figure 8 These represent the control input curves for the two following unmanned surface vessels.

[0065] Secondly, compared to the asymptotically stable traditional backstepping sliding mode formation control method, this invention ensures that transient and steady-state errors are within a preset range and maintains high control accuracy. Furthermore, this invention can achieve formation control of multiple unmanned surface vessels within a specified time, and the system convergence time can be user-defined. Additionally, while existing finite-time formation controllers can achieve convergence within a finite time, their convergence performance depends on the initial state of the system and is prone to chattering; moreover, the convergence time cannot be user-defined. In contrast, the controller of this invention does not exhibit chattering, and its convergence performance is independent of the initial state. Existing fixed-time formation controllers can also achieve convergence within a fixed time, but the convergence time depends on the system itself and related control parameters and cannot be set by the user. Compared to fixed-time formation controllers, the controller designed in this invention allows for manual setting of the system convergence time, significantly improving formation control efficiency.

[0066] Third, this invention proposes a multi-unmanned surface vessel (USV) formation control with error constraints and a preset time. By introducing preset performance equations and error transformation functions, the steady-state and transient responses of the system in the initial stage are kept within a preset envelope range, satisfying the user-defined transient and steady-state performance. Furthermore, a preset time disturbance observer is designed to accurately observe and compensate for external disturbances within a preset time, giving the system strong anti-interference capabilities. Finally, a preset time function is introduced, and kinematic and dynamic controllers are designed to ensure system convergence within the preset time, demonstrating broad application prospects in the field of multi-USV formation control.

[0067] Fourth, the significant technological advancements brought about by each claim:

[0068] 1. Claim 1: Describes a method for pre-set time cooperative formation control of multiple unmanned surface vessels with error constraints.

[0069] Technological advancements: Precise formation control of multiple unmanned surface vessels (USVs) has been achieved, enabling them to operate collaboratively within a predetermined timeframe, significantly improving the efficiency and accuracy of USV formation operations.

[0070] 2. Claim 2: It further refines the establishment of the motion and dynamics model of the unmanned surface vessel.

[0071] Technological advancements have provided a detailed and accurate dynamic model for unmanned surface vessels (USVs), enabling control strategies to be more precisely matched to the actual physical environment, thereby improving the operational stability and response speed of USVs.

[0072] 3. Claim 3: Describes the modeling of the relationship between virtual followers and leaders.

[0073] Technological advancements: The design of virtual followers simplifies the complexity of formation control by allowing real unmanned surface vessels to simply reach the virtual follower's position, while also increasing the flexibility of the formation.

[0074] 4. Claim 4: Describes the design of a preset time perturbation observer.

[0075] Technological advancements: The introduction of a preset time disturbance observer allows external disturbances to be observed and compensated for within a predetermined timeframe, thereby ensuring more stable and accurate formation operations of unmanned surface vessels.

[0076] 5. Claim 5: Describes a predefined time-grouping controller design based on an observer and preset performance control.

[0077] Technological advancements: A novel formation control strategy is provided, which enables faster and more accurate formation control through predefined time constraints, and also allows the formation to adjust and respond more quickly in the face of emergencies.

[0078] 6. Claim 6: Further refines the predefined time-based formation control strategy.

[0079] Technological advancements: By introducing a speed tracking error vector and a dynamic control law, higher tracking accuracy is provided for unmanned surface vessel (USV) formations, ensuring that USVs can execute given commands quickly and accurately.

[0080] Overall, these claims provide a comprehensive and efficient solution for unmanned surface vessel (USV) swarm control, enabling USV swarms to complete tasks more stably, accurately, and efficiently in complex aquatic environments. Attached Figure Description

[0081] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the embodiments of the present invention will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0082] Figure 1 This is a flowchart of a multi-unmanned surface vessel (USV) pre-set time cooperative formation control method with error constraints provided in an embodiment of the present invention.

[0083] Figure 2 This is a multi-unmanned surface vessel (USV) formation tracking and control trajectory diagram provided in an embodiment of the present invention;

[0084] Figure 3 This is a trajectory tracking error diagram of the unmanned surface vessel 1 provided in an embodiment of the present invention;

[0085] Figure 4This is a trajectory tracking error diagram of the unmanned surface vessel 2 provided in an embodiment of the present invention;

[0086] Figure 5 This is a speed tracking error diagram of the unmanned surface vessel 1 provided in an embodiment of the present invention;

[0087] Figure 6 This is a speed tracking error diagram of the unmanned surface vessel 2 provided in an embodiment of the present invention;

[0088] Figure 7 This is a control input diagram for following the unmanned surface vessel 1 provided in an embodiment of the present invention;

[0089] Figure 8 This is the control input diagram for the following unmanned surface vessel 2 provided in an embodiment of the present invention;

[0090] Figure 9 This is a disturbance observation error diagram of the following unmanned surface vessel 1 provided in an embodiment of the present invention;

[0091] Figure 10 This is a disturbance observation error diagram of the following unmanned surface vessel 2 provided in an embodiment of the present invention. Detailed Implementation

[0092] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0093] To address the problems existing in the prior art, the present invention provides a multi-unmanned surface vessel pre-set time cooperative formation control method with error constraints. The present invention will be described in detail below with reference to the accompanying drawings.

[0094] like Figure 1 As shown, the multi-unmanned surface vessel (USV) pre-set time cooperative formation control method with error constraints provided in this embodiment of the invention includes:

[0095] S1: Establish kinematic and dynamic models of unmanned surface vessels;

[0096] S2: Combine the virtual structure method and the leader-follower method to establish a virtual leader-follower formation control framework;

[0097] S3: Design a preset time disturbance observer to observe disturbances;

[0098] S4: Design a preset time function and a preset performance inequality, and design a preset time grouping control protocol.

[0099] The pre-set time distributed cooperative formation control method for unmanned surface vessels provided in this invention, in conjunction with specific implementation, includes the following steps:

[0100] 1. Establish kinematic and dynamic models of unmanned surface vessels;

[0101] The motion and dynamics model of the i-th unmanned surface vessel can be represented as follows:

[0102]

[0103] Where, η i =[x i ,y i ,ψ i ] T ∈R m Let v represent the pose vector of the unmanned surface vessel in the inertial coordinate system. i =[u i ,v i ,r i ] T Represents the velocity vector of the unmanned surface vessel in the attached coordinate system; Coriolis matrix C(v i ), hydrodynamic damping matrix D(v i ), and the inertia matrix M i The following is an expression:

[0104]

[0105]

[0106]

[0107] Coordinate system transformation matrix R i (ψ i This can be represented as: F(τ i ) is the saturation function of the control input of the i-th unmanned surface vessel, where τ i =[τ iu ,τ iv ,τ ir ] T ,F(τ i )=τ i,max tanh(τ i / τ i,max ), τ i,max It is the saturation threshold.

[0108] 2. Combining the virtual structure method and the leader-follower algorithm, a virtual leader-follower method is proposed. Specifically, virtual followers follow the leader, and real followers only need to reach the virtual follower's position and maintain following the leader to achieve formation control. The formation configuration of the virtual followers and the leader is determined by vectors. The determination, of which: lateral distance Longitudinal distance In the inertial coordinate system, the virtual follower and the navigator have the following pose relationship:

[0109]

[0110] Equation (2) can be written in the following compact vector form.

[0111] η v =η l +R(ψ l L(3)

[0112] in, η l =[x l ,y l ,ψ l ] T Represents the leader's pose vector; η v =[x v ,y v ,ψ v ] T This represents the pose vector of the virtual follower. The virtual follower replaces the real navigator as a reference for the follower. When the follower reaches the position of the virtual navigator, it means that the formation is in the desired motion state. At this time, the follower and the navigator maintain a predetermined distance and angle, which means that formation control is achieved.

[0113] Assumption 1: The external environmental disturbances experienced by the unmanned surface vessel are bounded and change slowly.

[0114] Assumption 2: Δτ is bounded and satisfies It is a known constant.

[0115] 3. To observe and compensate for external disturbances within a predetermined time, a preset time disturbance observer is designed:

[0116]

[0117] Where K0 and C0∈R 3×3 It is a positive definite matrix. This represents the estimate of the disturbance, with an estimation error of . C0 satisfies

[0118] in T > 0 is a positive design parameter.

[0119] ξ∈R 3 These are auxiliary state variables of the perturbation observer, updated by the following adaptive law:

[0120]

[0121] Where δ is a design parameter and satisfies

[0122] Theorem 1: Under Assumption 1, based on the proposed predefined time perturbation observer (3)-(4), by selecting appropriate control parameters, the perturbation estimation error will converge to a custom compact set within a predefined time T.

[0123] prove:

[0124] Differentiating equation (5) yields:

[0125]

[0126] Substituting equation (4) into equation (5), we get:

[0127]

[0128] Taking into account the estimation error, the above formula can be expressed as:

[0129]

[0130] Consider the following Lyapunov function:

[0131]

[0132] Differentiating the above equation, we get

[0133]

[0134] Where, μ0=min{2λ min (K0-I)},μ1=min{2λ min (C0)}, Note that C0 should be selected appropriately to satisfy the requirements. Therefore, equation (9) can be further written as

[0135] Next, when t∈[0,T), calculate The derivative can be obtained as follows:

[0136]

[0137] Furthermore, we can obtain:

[0138]

[0139] Solving the above inequality yields:

[0140]

[0141] Multiplying both sides of the above inequality by ζ, we get:

[0142]

[0143] According to the properties of ζ, when lim t→T ζ = 0 and lim ζ→0 If ζlnζ=0, V(t) will converge to a compact set in t∈[0,T).

[0144] When t∈[T,∞), we have:

[0145]

[0146] By solving the above inequality, we can obtain:

[0147]

[0148] By appropriately selecting the control parameter K0, it can be ensured that At this point, equation (15) can be restated as follows:

[0149]

[0150] Clearly, based on the above analysis, Theorem 1 is proved.

[0151] 4. Design of a predefined time-based array controller based on observers:

[0152] Design a predefined time-based formation controller based on an observer and preset performance control, and define the desired trajectory η. vi =[x vi ,y vi ,ψ vi ] T The tracking error is further defined as e 1i =x i -x vi e 2i =y i -y vi e 3i =ψ i -ψ vi The present invention aims to develop an effective control scheme that limits transient tracking error within a pre-set boundary.

[0153] -e ji,l <e ji <e ji,u ,j=1,2,3;i=1,…,n(17)

[0154] Among them, e ji,l and e ji,u Let represent the lower and upper limits of the tracking error, respectively. The following error transformation is then introduced:

[0155]

[0156] Differentiating formula (18) yields:

[0157]

[0158] Equation (19) can be written in compact vector form:

[0159] Consider Lyapunov functions Differentiation yields:

[0160]

[0161] Assuming v is a virtual control signal, the following virtual control law is selected:

[0162]

[0163] Define the speed tracking error vector z2 = v - α and set the virtual control law α i Substituting into equation (21), we get:

[0164]

[0165] To achieve predefined time tracking, the dynamic control law is designed as follows:

[0166]

[0167] in,

[0168] Theorem 2: Considering a dynamic system (1), and combining a disturbance observer (3)-(4), a virtual velocity control law (22), and a preset time control law (24), under the condition that assumptions 1-3 hold, by selecting appropriate parameters, the closed-loop system can stabilize within a preset time. Furthermore, the trajectory error is limited within the pre-set constraints, thus ensuring the transient and steady-state performance of the system.

[0169] Proof: The proof of Theorem 2 can be divided into two steps:

[0170] 1. When ||θ||≥σ

[0171] Consider the following Lyapunov function:

[0172]

[0173] Differentiating equation (26) yields:

[0174]

[0175] Combining equations (1) and (25), we can obtain:

[0176]

[0177]

[0178] Combining Young's inequality and substituting equations (9), (23), (27), and (28) into equation (27), we can obtain:

[0179]

[0180] in, 2. When ||θ|| < σ

[0181] At this point, equation (29) can be rewritten as

[0182]

[0183] Combining Young's inequality and substituting equations (9), (23), and (32) into equation (27), we can obtain...

[0184]

[0185] Where γ is a positive constant;

[0186] By choosing appropriate parameters, Theorem 2 is proved.

[0187] An application embodiment of the present invention provides a computer device, which includes a memory and a processor. The memory stores a computer program. When the computer program is executed by the processor, the processor performs the steps of a multi-unmanned surface vessel pre-time cooperative formation control method with error constraints.

[0188] An application embodiment of the present invention provides a computer-readable storage medium storing a computer program, which, when executed by a processor, causes the processor to perform the steps of a multi-unmanned surface vessel pre-time cooperative formation control method with error constraints.

[0189] An application embodiment of the present invention provides an information data processing terminal, which is used to implement a multi-unmanned surface vessel pre-set time collaborative formation control system with error constraints.

[0190] To verify the effectiveness of the method of the present invention, simulation experiments were conducted, as follows:

[0191] The effectiveness of the designed preset time formation control strategy was verified by simulation experiments using the classic Cybership II model. The parameter settings in the formation system are as follows: the desired trajectory, the initial position and velocity of the lead UAV and the follower UAV are shown in Table 1; the relevant parameter values ​​are shown in Table 2.

[0192] Table 1 Initial Values

[0193]

[0194]

[0195] Table 2 shows the parameter values.

[0196]

[0197] The disturbances are as follows:

[0198] τ d1 =[2cos(0.1t)+1.5sin(0.2t),sin(0.1t)+2cos(0.2t),2csin(0.2t)+1.5sin(0.1t)] T ;

[0199] τ d2 =[1.5sin(0.2t)+sin(0.1t),2cos(0.3t)+sin(0.2t),1.5sin(0.2t)+cos(0.1t)] T ;

[0200] like Figure 2-10 The simulation results show that the three unmanned surface vessels (USVs) can form a formation and maintain the desired formation within a preset time. Clearly, the proposed control scheme guarantees that the USV formation is completed within the preset time, and the system convergence time is independent of the initial state.

[0201] The following are two specific embodiments based on the provided technical solution:

[0202] Example 1: Adaptive Control of Unmanned Surface Vessels Based on Dynamic Parameter Tuning

[0203] 1. Selection of unmanned surface vessel model: Select a common unmanned surface vessel as the experimental object, such as a catamaran, because it has good stability and maneuverability.

[0204] 2. Establish kinematic and dynamic models: Based on the provided technical solution, establish the corresponding kinematic and dynamic models for the catamaran.

[0205] 3. Adaptive Control Strategy: Design an adaptive controller that can adjust the control strategy of the unmanned surface vessel based on real-time data of the Coriolis matrix, hydrodynamic damping matrix, and inertial matrix.

[0206] 4. Testing and Verification: Experimental tests were conducted under different water flow and wind conditions to verify the performance of the unmanned surface vessel under the adaptive control strategy.

[0207] Example 2: Collaborative Operation of Multiple Unmanned Surface Vessels

[0208] 1. Unmanned Surface Vessel (USV) platoon selection: Three USVs of the same model were selected for a collaborative operation experiment.

[0209] 2. Establish motion and dynamics models for each unmanned surface vessel: Establish kinematic and dynamic models for each unmanned surface vessel separately.

[0210] 3. Cooperative Control Strategy Design: Design a central control strategy that collects real-time data from each unmanned surface vessel (USV) and sends control commands to ensure they move according to a predetermined formation. Simultaneously, utilize a coordinate transformation matrix to ensure that each USV can correctly recognize and respond to the commands of the central control strategy.

[0211] 4. Virtual Environment Simulation: Test strategies for collaborative operation of multiple unmanned surface vessels in a computer simulation environment, simulating different external conditions such as wind and water flow.

[0212] 5. Real-world water testing: Conduct experiments under real-world water conditions to verify the practicality and efficiency of the multi-unmanned surface vessel (USV) collaborative operation strategy.

[0213] Both of these embodiments are based on the original technical solution, and are developed from the perspectives of single-boat adaptive control and multi-boat cooperative operation, respectively.

[0214] It should be noted that embodiments of the present invention can be implemented in hardware, software, or a combination of both. The hardware portion can be implemented using dedicated logic; the software portion can be stored in memory and executed by a suitable instruction execution system, such as a microprocessor or dedicated-design hardware. Those skilled in the art will understand that the above-described devices and methods can be implemented using computer-executable instructions and / or included in processor control code, for example, such code provided on a carrier medium such as a disk, CD, or DVD-ROM, a programmable memory such as read-only memory (firmware), or a data carrier such as an optical or electronic signal carrier. The devices and modules of the present invention can be implemented by hardware circuitry such as very large-scale integrated circuits or gate arrays, semiconductors such as logic chips, transistors, or programmable hardware devices such as field-programmable gate arrays, programmable logic devices, etc., or by software executed by various types of processors, or by a combination of the above-described hardware circuitry and software, such as firmware.

[0215] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any modifications, equivalent substitutions, and improvements made by those skilled in the art within the scope of the technology disclosed in the present invention, and within the spirit and principles of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. A method for multi-unmanned surface vehicle (USV) preset time cooperative formation control with error constraint, characterized in that, A virtual leader-follower formation control framework is created by combining the virtual structure method and the leader-follower method, and a preset time disturbance observer is designed to observe external disturbances. This method uses a preset time function and performance inequality to design a preset time formation control protocol to ensure that the transient tracking error can be effectively limited within the preset boundary within a predetermined time, and to achieve formation control under the condition of external disturbances. include: S1: Establish kinematic and dynamic models of unmanned surface vessels; S2: Combine the virtual structure method and the leader-follower method to establish a virtual leader-follower formation control framework; S3: Design a preset time disturbance observer to observe disturbances; S4: Design a preset time function and a preset performance inequality, and design a preset time-based formation control protocol; S4 specifically includes: Design a predefined time-based formation controller based on an observer and preset performance control, and define the desired trajectory. Tracking error is further defined as , , The transient tracking error is limited to a pre-set boundary. ； where and representing lower and upper limits of the tracking error, introduce the following error transformation: ； Differentiating the above equation, we get: ； The above expression can be written in compact vector form: ； Consider the Lyapunov function Taking the derivative gives ； Assumption For the virtual control signal, select the following virtual control law: ； S4 also includes: Define the speed tracking error vector And virtual control rate Substituting, we get: ； To achieve predefined time tracking, the dynamic control law is designed as follows: ； in, .

2. The multi-unmanned surface vessel (USV) pre-set time cooperative formation control method with error constraints as described in claim 1, characterized in that, S1 specifically includes: No. The motion and dynamics model of an unmanned surface vessel can be represented as follows: ； in, This represents the pose vector of the unmanned surface vessel in the inertial coordinate system. Represents the velocity vector of the unmanned surface vessel in the appendage coordinate system; Coriolis matrix Hydrodynamic damping matrix and inertia matrix The following is an expression: ； ； ； Coordinate system transformation matrix It can be represented as: ； It is the first The saturation function of the control input of an unmanned surface vessel, where , , It is the saturation threshold.

3. The multi-unmanned surface vessel (USV) pre-set time cooperative formation control method with error constraints as described in claim 1, characterized in that, S2 specifically includes: Virtual followers are set up to follow the leader. Real followers only need to reach the virtual follower's position and maintain their position to achieve formation control. The formation configuration of the virtual follower and the navigator is determined by vectors. The determination, of which: lateral distance Longitudinal distance In the inertial coordinate system, the virtual follower and the navigator have the following pose relationship: ； The above equation can be written in the following compact vector form. ； in, , Represents the leader's pose vector; This represents the pose vector of the virtual follower. The virtual follower replaces the real navigator as a reference for the follower. When the follower reaches the position of the virtual navigator, it means that the formation is in the desired motion state. At this time, the follower and the navigator maintain a predetermined distance and angle, thus realizing formation control.

4. The multi-unmanned surface vehicle pre-set time cooperative formation control method with error constraint of claim 1, wherein, S3 specifically includes: In order to observe and compensate for external disturbances within a predetermined time, a preset time disturbance observer is designed: ； in, and It is a positive definite matrix. This represents the estimate of the disturbance, with an estimation error of . , satisfy , ; wherein is a positive design parameter, is an auxiliary state variable of the disturbance observer, updated by the following adaptive law: ； wherein is a design parameter and satisfies .

5. A multi-unmanned surface vehicle pre-set time cooperative formation control system with error constraint applying the multi-unmanned surface vehicle pre-set time cooperative formation control method with error constraint according to any one of claims 1-4, characterized in that, The multi-unmanned surface vessel (USV) pre-set time collaborative formation control system with error constraints includes: The model building module is used to build kinematic and dynamic models of unmanned surface vessels. The framework building module is used to combine the virtual structure method and the leader-follower method to build a virtual leader-follower formation control framework; The disturbance observation module is used to design a disturbance observer that observes disturbances at a preset time. The formation control module is used to design preset time functions and preset performance inequalities, and to design preset time formation control protocols.

6. A computer-readable storage medium storing a computer program, wherein when executed by a processor, the computer program causes the processor to perform the steps of the multi-unmanned surface vessel pre-time cooperative formation control method with error constraints as described in any one of claims 1 to 4.

7. An information data processing terminal, wherein the information data processing terminal is used to implement the multi-unmanned surface vessel pre-set time collaborative formation control system with error constraints as described in claim 5.

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