Finite-time adaptive adjustment of multiple unmanned boat formation consistent control method and system

Abstract

The present invention relates to the technical field of unmanned watercraft formation consistency control, and in particular to a method and system for consistent control of a multi-unmanned watercraft formation with finite-time adaptive regulation. The method comprises: defining auxiliary variables based on the dynamic equations, nonlinear dynamic characteristics, and external disturbances of each unmanned watercraft; constructing a finite-time consistency control law and an adaptive law based on the auxiliary variables and the conditions for achieving bounded consistency of the multi-unmanned watercraft system; determining a closed-loop error controller based on position error, velocity error, the finite-time consistency control law, and the adaptive law; constructing a Lyapunov function based on the auxiliary variables and the closed-loop error controller; verifying the error stability of the position and velocity of each unmanned watercraft using the Lyapunov function; and achieving consistent control of the multi-unmanned watercraft formation based on the finite-time consistency control law. The method solves the problems of disturbance compensation and finite-time formation consistency control with more general state-dependent disturbances.

Description

Technical Field

[0001] The present invention relates to the technical field of unmanned boat formation consistent control, and in particular to a method and system for consistent control of multiple unmanned boat formations with finite time adaptive adjustment. Background Art

[0002] In recent years, the formation consistency problem in multiple unmanned aerial vehicle systems has been a hot topic of research, attracting considerable attention due to its broad application prospects in various nonlinear dynamic systems. In complex operating environments, these nonlinear dynamic systems are often subject to nonideal factors such as strong uncertainty, external disturbances, and nonlinear coupling, making achieving formation consistency control in multiple unmanned aerial vehicle systems challenging.

[0003] It is well known that finite-time control is one of the most effective control methods for achieving high-precision tracking, fast convergence, and resilience to unpredictable variables in dynamic systems. In order to cope with the impact of these non-ideal factors on consistency problems, many scholars have developed a variety of effective methods. These methods include neural network-based control strategies, observer-based control strategies, and sliding mode control strategies. However, these traditional advanced control algorithms require constraints on the differentiability of disturbances and nonlinearities, and require the adjustment of a large number of parameters, which undoubtedly increases computing resources. Research has found that in order to ensure finite-time consistency while reducing constraints and computational burden, it is necessary to further develop more effective nonlinear and disturbance compensation control methods. Summary of the Invention

[0004] In order to address the shortcomings of the existing technology, the present invention provides a multi-unmanned boat formation consistency control method and system with finite-time adaptive adjustment; the present invention develops a new adaptive distributed consistency control scheme for a multi-unmanned boat system, which solves the disturbance compensation with more general state-related disturbances and finite-time formation consistency control problems.

[0005] On the one hand, a consistent control method for a multi-UAV formation with finite-time adaptive adjustment is provided, including:

[0006] According to the dynamic characteristics of the multi-UAV system, the dynamic equation of each UAV is established, and the boundaries of each UAV are defined by assuming the nonlinear dynamic characteristics and external disturbances of each UAV.

[0007] Define the position error and velocity error of each UAV, and define the conditions for achieving bounded consistency of the multi-UAV system;

[0008] Auxiliary variables are defined based on the dynamic equations, nonlinear dynamic characteristics, and external disturbances of each unmanned vehicle. Finite-time consistency control laws and adaptive laws are constructed based on the auxiliary variables and the conditions for achieving bounded consistency of the multi-unmanned vehicle system.

[0009] Determine the closed-loop error controller based on position error, velocity error, finite-time consistency control law and adaptive law;

[0010] Based on the auxiliary variables and the closed-loop error controller, a Lyapunov function is constructed. The error stability of the position and speed of each unmanned boat is verified by the Lyapunov function.

[0011] Based on the finite-time consistency control law, consistency control of multiple unmanned boat formations is achieved.

[0012] On the other hand, a multi-unmanned boat formation consistent control system with finite time adaptive adjustment is provided, including:

[0013] An establishment module is configured to: establish a dynamic equation for each unmanned vehicle according to the dynamic characteristics of the multi-unmanned vehicle system, and define boundaries for the nonlinear dynamic characteristics and external disturbances of each unmanned vehicle by assuming;

[0014] A definition module is configured to: define a position error and a velocity error of each unmanned vehicle, and define a condition for achieving bounded consistency of the multi-unmanned vehicle system;

[0015] A construction module is configured to: define auxiliary variables according to the dynamic equations, nonlinear dynamic characteristics and external disturbances of each unmanned vehicle; construct a finite-time consistency control law and an adaptive law according to the auxiliary variables and the conditions for achieving bounded consistency of the multi-unmanned vehicle system;

[0016] A determination module is configured to: determine a closed-loop error controller according to a position error, a velocity error, a finite-time consistency control law, and an adaptive law;

[0017] A verification module is configured to: construct a Lyapunov function based on the auxiliary variables and the closed-loop error controller; and verify the error stability of the position and velocity of each unmanned boat through the Lyapunov function;

[0018] The control module is configured to achieve consistency control of multiple unmanned boat formations based on a finite-time consistency control law.

[0019] The above technical solution has the following advantages or beneficial effects:

[0020] (1) Compared with traditional methods, the present invention significantly reduces the consumption of computing resources and improves real-time control performance by introducing a finite-time adaptive compensation mechanism;

[0021] (2) The present invention only needs to assume that the disturbance satisfies partial boundedness. Compared with the traditional finite-time control method, the present invention does not require high-order differentiability or strict norm boundedness conditions, which expands the application scope of the method.

[0022] (3) The finite-time consistency control scheme designed in the present invention can effectively achieve the finite-time consistency of the multi-UAV system under nonlinear dynamics and external interference, and enable the multi-UAV system to reach a consistent state within a predetermined time, thereby improving the control efficiency and response speed.

[0023] (4) Through the designed finite-time control function, the multi-UAV system can achieve rapid convergence of the consistency error within a predetermined time. Through the adaptive compensation term and parameter update law, the system can online estimate and offset unknown nonlinear dynamics and external disturbances when the disturbance is state-dependent and without the need for pre-knowledge of the boundaries. Compared with existing neural network methods, the control law structure of the present invention is simple and significantly reduces the computational burden. In addition, the present invention only needs to meet some bounded conditions and can be extended to various second-order multi-agent systems. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] The accompanying drawings, which constitute a part of the present invention, are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute improper limitations on the present invention.

[0025] Figure 1 Flow chart of the method of the present invention.

[0026] Figure 2 Represents the motion plan of the unmanned boat.

[0027] Figure 3 Represents the motion topology of the unmanned boat; where Figure 3 The numbers 1, 2, 3, 4, and 5 represent the numbers of the five unmanned boats respectively.

[0028] Figure 4 Schematic diagram showing the lateral position trajectory of each unmanned boat and the reference lateral position trajectory.

[0029] Figure 5 Schematic diagram showing the longitudinal position trajectory of each unmanned boat and the reference longitudinal position trajectory.

[0030] Figure 6 Schematic diagram showing the heading angle trajectory of each unmanned boat and the reference heading angle trajectory.

[0031] Figure 7 Schematic diagram showing the lateral velocity trajectory of each unmanned boat and the reference lateral velocity trajectory.

[0032] Figure 8 Schematic diagram showing the longitudinal velocity trajectory of each unmanned boat and the reference longitudinal velocity trajectory.

[0033] Figure 9 Schematic diagram showing the yaw angular velocity trajectory of each unmanned boat and the reference yaw angular velocity trajectory.

[0034] Figure 10 The figure shows the trajectory tracking error of the first unmanned boat.

[0035] Figure 11 Figure 2 shows the trajectory tracking error of the second unmanned boat.

[0036] Figure 12 The figure shows the trajectory tracking error of the third unmanned boat.

[0037] Figure 13 Figure 2 shows the trajectory tracking error of the fourth unmanned boat.

[0038] Figure 14 Figure 2 shows the trajectory tracking error of the fifth unmanned boat.

[0039] Figure 15 Figure 2 shows the speed tracking error of the first unmanned boat.

[0040] Figure 16 Figure 2 shows the speed tracking error of the second unmanned boat.

[0041] Figure 17 Figure 2 shows the speed tracking error of the third unmanned boat.

[0042] Figure 18 Figure 2 shows the speed tracking error of the fourth unmanned boat.

[0043] Figure 19 Figure 2 shows the speed tracking error of the fifth unmanned boat.

[0044] Figure 20 Figure 4 shows the control input response diagram of the first unmanned boat.

[0045] Figure 21 Figure 4 shows the control input response diagram of the second unmanned boat.

[0046] Figure 22 The control input response diagram of the third unmanned boat is shown.

[0047] Figure 23 The control input response diagram of the fourth unmanned boat is shown.

[0048] Figure 24 Figure 4 shows the control input response diagram of the fifth unmanned boat.

[0049] Figure 25 Represents the adaptive adjustment diagram of the disturbance estimation parameters of the first unmanned boat.

[0050] Figure 26 Figure 4 shows the adaptive adjustment diagram of the disturbance estimation parameters of the second unmanned boat.

[0051] Figure 27Figure 2 shows the adaptive adjustment diagram of the disturbance estimation parameters of the third unmanned boat.

[0052] Figure 28 Figure 4 shows the adaptive adjustment diagram of the disturbance estimation parameters of the fourth unmanned boat.

[0053] Figure 29 Figure 5. The adaptive adjustment diagram of disturbance estimation parameters for the fifth unmanned boat. DETAILED DESCRIPTION

[0054] It should be noted that the following detailed descriptions are exemplary and intended to provide further explanation of the present invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which the present invention belongs.

[0055] Explanation of terms:

[0056] 1. An unmanned surface vessel system (UAV) is an unmanned surface vessel system typically composed of a platform system, payload system, communications system, navigation system, and control system. It can complete various designated missions through autonomous navigation or remote control. A multi-UAV system, on the other hand, consists of multiple UAVs operating in coordination using specific technologies and methods to achieve mission objectives.

[0057] 2. Finite-time control refers to designing a control law so that the system state converges to the desired state or meets the specified control objective within a finite time. It has the advantages of fast convergence speed and strong interference rejection, and is often used in control scenarios with strict response time requirements.

[0058] 3. Formation consensus control refers to the process of making all the UAVs’ state variables (such as position, speed, etc.) consistent through local information interaction and control strategies in a multi-UAV system. It is a key method to achieve collaborative control.

[0059] 4. Adaptive control refers to the process of online estimation and adjustment of system control parameters so that the control system can adapt to changes in the system's internal dynamics or external disturbances.

[0060] 5. Anti-interference control is a control strategy that designs a control strategy to compensate for unknown nonlinear dynamics, including external disturbances and internal uncertainties of the system, so that the control system can maintain good performance and stability in the presence of external disturbances.

[0061] To address the shortcomings of the existing technology, the present invention develops a new adaptive finite-time formation consistency control scheme for a multi-UAV system. First, a finite-time control function is used to ensure that the system state error converges within a finite time. Then, an adaptive law is used to dynamically compensate for system disturbances, reducing the requirements for a priori assumptions on the disturbance model. Finally, the adaptive compensation term and the control function are combined to obtain the control input, ensuring that the system reaches consistency within a finite time with low computational complexity and strong robustness. This scheme achieves fast and high-precision consistency of the multi-UAV system under more general disturbance assumptions, overcoming the strong constraints of existing methods on nonlinear terms and disturbances.

[0062] Example 1

[0063] This embodiment provides a method for consistent control of a multi-unmanned boat formation with finite time adaptive adjustment;

[0064] like Figure 1 As shown in FIG, a finite-time adaptively regulated multi-UAV formation consensus control method includes:

[0065] S100: Based on the dynamic characteristics of the multi-UAV system, establish the dynamic equations of each UAV, and define the boundaries of the nonlinear dynamic characteristics and external disturbances of each UAV by assuming;

[0066] S200: Define the position error and velocity error of each UAV and define the conditions for achieving bounded consistency of the multi-UAV system;

[0067] S300: Define auxiliary variables based on the dynamic equations, nonlinear dynamic characteristics, and external disturbances of each unmanned vehicle. Construct finite-time consistency control laws and adaptive laws based on the auxiliary variables and the conditions for achieving bounded consistency of the multi-unmanned vehicle system.

[0068] S400: determining a closed-loop error controller according to the position error, the speed error, the finite-time consistency control law, and the adaptive law;

[0069] S500: Construct a Lyapunov function based on the auxiliary variables and the closed-loop error controller; verify the error stability of the position and speed of each unmanned boat through the Lyapunov function;

[0070] S600: Based on the finite-time consistency control law, it realizes the consistency control of multiple unmanned boat formations.

[0071] Among them, the multi-unmanned boat system includes: multiple unmanned boats, each of which is controlled by a console.

[0072] The beneficial effects of the above technical solution are: in order to achieve finite-time formation consistency control of a multi-unmanned boat system under nonlinear dynamics and external interference conditions, an adaptive disturbance estimation and safety controller is established through the design of system errors and auxiliary variables, so that the unmanned boats can navigate and track the preset target trajectory and maintain formation consistency.

[0073] Furthermore, the S100: establishing a dynamic equation for each unmanned boat according to the dynamic characteristics of the multi-unmanned boat system, including:

[0074] S101: Unmanned boat structure and formation topology diagram Figure 2 and Figure 3 As shown. Set the ground coordinate system ,definition and Unmanned Boat axis, Axis position status, is the yaw angle of the unmanned boat. Accordingly, define Unmanned boat axis, The velocity state in the axis direction and the yaw angular velocity. According to the dynamic principle of the multi-unmanned boat system, The dynamic equation of an unmanned boat can be expressed as:

[0075] ;

[0076] in, represents the control input of each unmanned boat, represents the nonlinear dynamics of each unmanned boat, , represents the unknown external disturbance of each unmanned boat. Obviously, and Respectively represent The position and velocity vector of each unmanned boat; represents the inertia matrix of the unmanned boat; and denote the Coriolis and centrifugal matrices and the hydrodynamic damping parameter matrix, respectively; represents the unknown external disturbance, where represents the disturbance of the unmanned boat in the longitudinal direction, Indicates the disturbance suffered by the unmanned boat in the lateral direction, Indicates the disturbance suffered by the unmanned boat in the yaw direction, middle 、 、 They are the surge, sway and pitch forces provided by the actuators; represents the rotation matrix used to transform variables between the Earth-fixed inertial coordinate system and the body-fixed coordinate system, and is defined as follows:

[0077] .

[0078] The beneficial effect of the above technical solution is that each unmanned boat is modeled as an Euler-Langerange type second-order nonlinear dynamic model containing an inertia matrix, Coriolis and centrifugal matrices, a hydrodynamic damping parameter matrix, and an external disturbance term. Compared with the traditional first-order integrator modeling, this model can more accurately characterize the dynamic response characteristics of the surface unmanned boat under complex sea conditions. The control system constructed based on this model can more effectively introduce a disturbance compensation mechanism and an adaptive estimation structure, further realizing the system's stable and consistent control goals within a limited time, with stronger control accuracy, response speed, and robustness. At the same time, this modeling method has good versatility and engineering deployment value, and can be widely adapted to multiple types of unmanned boat platforms.

[0079] Furthermore, the step S100 of defining the boundaries of each unmanned vehicle by assuming the nonlinear dynamic characteristics and external disturbances specifically includes:

[0080] S102: Nonlinear dynamic characteristics of an unmanned vehicle and disturbances The following conditions should be met:

[0081] ;

[0082] as well as

[0083] ;

[0084] in, is a positive but unknown constant.

[0085] The beneficial effect of this technical solution is that by making bounded assumptions about the nonlinear dynamic characteristics of each unmanned vehicle and the external disturbance term, they are uniformly represented as a weighted combination of state-dependent terms and constant terms, and three unknown boundary parameters are introduced. This approach simplifies disturbance modeling, facilitates controller design and stability analysis. Combined with an adaptive estimation mechanism, it enables online identification of the upper bound of the disturbance without requiring prior knowledge, enhancing the robustness and practicality of the system and providing theoretical support for finite-time consistency control.

[0086] Furthermore, the step S200 of defining the position error and speed error of each unmanned boat specifically includes:

[0087] S201: Definition The position and velocity errors of the unmanned boat 、 ,in and Respectively The reference position and velocity signals expected by an unmanned boat satisfy:

[0088] ;

[0089] in, is the reference input.

[0090] Furthermore, the S200: defining the conditions for achieving bounded consistency of the multi-unmanned vehicle system specifically includes:

[0091] S202: Define the conditions for achieving bounded consistency of the multi-UAV system. For any initial value and , if the error satisfies:

[0092] ;

[0093] in, 、 , Defined as:

[0094] ;

[0095] and is a positive constant, the multi-unmanned boat system is said to have achieved bounded consistency.

[0096] The beneficial effects of the above technical solution are: S200 defines the error variables and reference signal models of each unmanned boat according to the dynamic characteristics of the multi-unmanned boat system, introduces the concept of bounded consistency, and ensures that the error signal is limited to a small range when time approaches a certain limit after appropriate linear transformation.

[0097] Furthermore, the S300: defines auxiliary variables according to the dynamic equations, nonlinear dynamic characteristics and external disturbances of each unmanned boat, specifically including:

[0098] S301: Define auxiliary variables

[0099] ;

[0100] in, , , is the number of unmanned boats in the formation, is the topological factor, indicating that the unmanned boat and The connection status between Indicates connection, Indicates disconnection.

[0101] Furthermore, the S300: constructing a finite-time consistency control law and an adaptive law based on the auxiliary variables and the conditions for achieving bounded consistency of the multi-unmanned vehicle system, specifically includes:

[0102] S302: Design a finite-time consistency control law based on the auxiliary variables as follows:

[0103] ;

[0104] in, ;

[0105] is a finite-time control function:

[0106] ;

[0107] in, ,

[0108] ; is a matrix The maximum eigenvalue of , , is a constant, and its adaptive law satisfies the following formula:

[0109] ;

[0110] as well as:

[0111] ;

[0112] as well as:

[0113] ;

[0114] in, is a positive constant.

[0115] The beneficial effects of the above technical solution are as follows: auxiliary variables are defined based on the nonlinear dynamics and external disturbance characteristics of multiple unmanned vehicles to enhance system consistency; finite-time control functions are designed based on the auxiliary variables and control objectives to ensure that the system achieves consistency within a finite time. Based on the auxiliary variables and finite-time control functions, a distributed finite-time consistency control law is constructed to achieve rapid state tracking of the unmanned vehicles.

[0116] Furthermore, the step S400 of determining a closed-loop error controller according to the position error, the speed error, the finite-time consistency control law, and the adaptive law includes:

[0117] S401: Substitute the finite-time consistency control law into the state equation of each unmanned boat to obtain:

[0118] ;

[0119] Then, the reference position and velocity signals expected by the UAV are combined with the state equation of each UAV to further obtain the error system equation:

[0120] ;

[0121] in: , , , , ,in, .

[0122] S402: According to the auxiliary variables, we can obtain:

[0123] ;

[0124] S403: Combining the error system equation and the time derivative of the auxiliary variable, the following closed-loop error system is obtained:

[0125] ;

[0126] in, , , .

[0127] The beneficial effect of this technical solution is that it constructs a closed-loop error system based on position and velocity errors, and combines a finite-time consistency control law with an adaptive disturbance estimation mechanism to achieve rapid consistency tracking control under unknown disturbance conditions. This system features a closed structure, fast response, and strong robustness, making it suitable for engineering applications in multi-unmanned vehicle formation missions.

[0128] Furthermore, the step S500: constructing a Lyapunov function based on the auxiliary variables and the closed-loop error controller; and verifying the error stability of the position and speed of each unmanned boat through the Lyapunov function, including:

[0129] S501: Based on the auxiliary variables and error signals of the multi-unmanned vehicle system, a Lyapunov function is constructed as follows:

[0130] ;

[0131] in, , , ;

[0132] S502: When When , the time derivative of the Lyapunov function is obtained:

[0133] ;

[0134] in,

[0135] ,

[0136] Indicated by Define the matrix elements.

[0137] S503: Based on the assumptions and nonlinear dynamic characteristics of each unmanned boat and external disturbances get:

[0138]

[0139]

[0140]

[0141]

[0142]

[0143]

[0144] ;

[0145] S504: According to , and combined with the adaptive law:

[0146] ;

[0147] S505: According to the finite time stability theorem, the error state 、 and In a limited time The inner region converges to the area near zero, and because of the auxiliary variable satisfy ,in .

[0148] In addition, from the definition of auxiliary variables, we can know that auxiliary variables Expressed as:

[0149] ;

[0150] From the above we can get:

[0151] ;

[0152] S506: Order

[0153] ;

[0154] because is a bounded signal, so there is a parameter Make . So we get the following relationship:

[0155] ;

[0156] ;

[0157] Then, we further get:

[0158] ;

[0159] This proves that the position and speed errors of each unmanned boat in the multi-unmanned boat system will be ,and within the range of .

[0160] The beneficial effect of this technical solution is that, based on the auxiliary variables and the closed-loop error system, a unified Lyapunov function is constructed to analyze the dynamic behavior of the system's position and velocity errors under external disturbances and model uncertainty. This function rigorously proves that the system error converges within a finite time, ensuring the stability and convergence speed of the control system in complex environments.

[0161] Furthermore, S600: the finite-time consistency control law is used as a finite-time consistency controller, and based on the finite-time consistency controller, consistency control of multiple unmanned boat formations is achieved.

[0162] Furthermore, the method further comprises: performing actual operation through computer simulation software MATLAB to verify the effectiveness of the method and system of the present invention.

[0163] This example uses the computer software MATLAB to select five unmanned boats to verify the invented control method. The parameters related to each step in the simulation are selected as follows:

[0164] In S100, the inertial matrix, Coriolis matrix and centrifugal matrix parameters of the unmanned boat are selected as:

[0165] ,

[0166] .

[0167] in:

[0168] ,

[0169] ,

[0170] The hydrodynamic damping parameter matrix is ​​selected as:

[0171] .

[0172] in:

[0173] ,

[0174] ,

[0175] .

[0176] The multi-UAV system in the simulation consists of five UAVs, and its topology is described by the following Laplace matrix:

[0177] .

[0178] In S200, the reference input signal Select as:

[0179] .

[0180] The external disturbance is selected as:

[0181] .

[0182] in, .

[0183] In S300, the finite time consistency controller parameters are selected as:

[0184] , , , ,

[0185] , , ,

[0186] in, .

[0187] The adaptive scheme parameters are selected as follows:

[0188] ,

[0189] in, , .

[0190] The initial value of the adaptive law is selected as:

[0191] ,

[0192] in, , .

[0193] Result description:

[0194] Figure 4 Schematic diagram showing the lateral position trajectory of each unmanned boat and the reference lateral position trajectory. Figure 5 Schematic diagram showing the longitudinal position trajectory of each unmanned boat and the reference longitudinal position trajectory. Figure 6 Schematic diagram showing the heading angle trajectory of each unmanned boat and the reference heading angle trajectory.

[0195] Figure 7 Schematic diagram showing the lateral velocity trajectory of each unmanned boat and the reference lateral velocity trajectory. Figure 8 Schematic diagram showing the longitudinal velocity trajectory of each unmanned boat and the reference longitudinal velocity trajectory. Figure 9 Schematic diagram showing the yaw angular velocity trajectory of each unmanned boat and the reference yaw angular velocity trajectory.

[0196] Figure 10 The figure shows the trajectory tracking error of the first unmanned boat. Figure 11 Figure 2 shows the trajectory tracking error of the second unmanned boat. Figure 12 The figure shows the trajectory tracking error of the third unmanned boat. Figure 13 Figure 2 shows the trajectory tracking error of the fourth unmanned boat. Figure 14 Figure 2 shows the trajectory tracking error of the fifth unmanned boat.

[0197] Figure 15 Figure 2 shows the speed tracking error of the first unmanned boat. Figure 16 Figure 2 shows the speed tracking error of the second unmanned boat. Figure 17 Figure 2 shows the speed tracking error of the third unmanned boat. Figure 18 Figure 2 shows the speed tracking error of the fourth unmanned boat. Figure 19 Figure 2 shows the speed tracking error of the fifth unmanned boat.

[0198] Figure 20 Figure 4 shows the control input response diagram of the first unmanned boat. Figure 21 Figure 4 shows the control input response diagram of the second unmanned boat. Figure 22 The control input response diagram of the third unmanned boat is shown. Figure 23 The control input response diagram of the fourth unmanned boat is shown. Figure 24 Figure 4 shows the control input response diagram of the fifth unmanned boat.

[0199] Figure 25 Represents the adaptive adjustment diagram of the disturbance estimation parameters of the first unmanned boat. Figure 26Figure 4 shows the adaptive adjustment diagram of the disturbance estimation parameters of the second unmanned boat. Figure 27 Figure 2 shows the adaptive adjustment diagram of the disturbance estimation parameters of the third unmanned boat. Figure 28 Figure 4 shows the adaptive adjustment diagram of the disturbance estimation parameters of the fourth unmanned boat. Figure 29 Figure 5. The adaptive adjustment diagram of disturbance estimation parameters for the fifth unmanned boat.

[0200] Example 2

[0201] This embodiment provides a finite time adaptive adjustment multi-unmanned boat formation consistent control system;

[0202] The multi-unmanned boat formation consensus control system with finite time adaptive adjustment includes:

[0203] An establishment module is configured to: establish a dynamic equation for each unmanned vehicle according to the dynamic characteristics of the multi-unmanned vehicle system, and define boundaries for the nonlinear dynamic characteristics and external disturbances of each unmanned vehicle by assuming;

[0204] A definition module is configured to: define a position error and a velocity error of each unmanned vehicle, and define a condition for achieving bounded consistency of the multi-unmanned vehicle system;

[0205] A construction module is configured to: define auxiliary variables according to the dynamic equations, nonlinear dynamic characteristics and external disturbances of each unmanned vehicle; construct a finite-time consistency control law and an adaptive law according to the auxiliary variables and the conditions for achieving bounded consistency of the multi-unmanned vehicle system;

[0206] A determination module is configured to: determine a closed-loop error controller according to a position error, a velocity error, a finite-time consistency control law, and an adaptive law;

[0207] A verification module is configured to: construct a Lyapunov function based on the auxiliary variables and the closed-loop error controller; and verify the error stability of the position and velocity of each unmanned boat through the Lyapunov function;

[0208] The control module is configured to achieve consistency control of multiple unmanned boat formations based on a finite-time consistency control law.

[0209] The foregoing description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Those skilled in the art will readily appreciate that various modifications and variations of the present invention are possible. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention are intended to be within the scope of protection of the present invention.

Claims

1. A finite-time adaptive multi-unmanned boat formation consensus control method, characterized by: include: According to the dynamic characteristics of the multi-UAV system, the dynamic equation of each UAV is established, and the boundaries of each UAV are defined by assuming the nonlinear dynamic characteristics and external disturbances of each UAV. Define the position error and velocity error of each UAV, and define the conditions for achieving bounded consistency of the multi-UAV system; Auxiliary variables are defined according to the dynamic equations, nonlinear dynamic characteristics and external disturbances of each unmanned vehicle; According to the conditions of auxiliary variables and multi-UAV system to achieve bounded consistency, the finite-time consistency control law and adaptive law are constructed. Determine the closed-loop error controller based on position error, velocity error, finite-time consistency control law and adaptive law; Based on the auxiliary variables and the closed-loop error controller, a Lyapunov function is constructed. The error stability of the position and speed of each unmanned boat is verified by the Lyapunov function. Based on the finite time consistency control law, the consistency control of multiple unmanned boat formations is realized; Among them, the conditions for achieving bounded consistency of the multi-unmanned vehicle system are defined, including: Define the conditions for achieving bounded consistency of the multi-unmanned vehicle system. For any initial value and , if the error satisfies: ； in, 、 , Defined as: ； and is a positive constant, then the multi-unmanned boat system is said to have achieved bounded consistency; Among them, auxiliary variables are defined according to the dynamic equations, nonlinear dynamic characteristics and external disturbances of each unmanned boat, including: Defining auxiliary variables ； in, , , is the number of unmanned boats in the formation, is the topological factor, indicating that the unmanned boat and The connection status between Indicates connection, Indicates disconnection; Among them, according to the conditions for achieving bounded consistency of auxiliary variables and multi-unmanned boat systems, finite-time consistency control law and adaptive law are constructed, including: The finite-time consistency control law is designed based on the auxiliary variables as follows: ； in, ; is a finite-time control function: ； in, , ; is a matrix The maximum eigenvalue of , , is a constant; Among them, according to the position error, speed error, finite time consistency control law and adaptive law, the closed-loop error controller is determined, including: Substituting the finite time consistency control law into the state equation of each unmanned boat yields: ； Then, the reference position and velocity signals expected by the UAV are combined with the state equation of each UAV to further obtain the error system equation: ； in: , , , , , ; represents the rotation matrix used to transform variables between the Earth-fixed inertial coordinate system and the body-fixed coordinate system, and is defined as follows: ; is the reference input; According to the auxiliary variables, we can get: ； Combining the error system equations and the time derivatives of the auxiliary variables, the following closed-loop error system is obtained: ； in, , , .

2. The method for consistent control of a multi-unmanned boat formation with finite time adaptive adjustment as claimed in claim 1 is characterized in that: According to the dynamic characteristics of the multi-UAV system, the dynamic equation of each UAV is established, including: Set the ground coordinate system ,definition and Unmanned Boat axis, Axis position status, is the yaw angle of the unmanned boat; accordingly, define Unmanned boat axis, The velocity state in the axis direction and the yaw angular velocity; According to the dynamic principle of the multi-unmanned boat system, the The dynamic equation of an unmanned boat can be expressed as: ； in, represents the control input of each unmanned boat, represents the nonlinear dynamics of each unmanned boat, , represents the unknown external disturbance of each unmanned boat. Obviously, and Respectively represent The position and velocity vector of each unmanned boat; represents the inertia matrix of the unmanned boat; and denote the Coriolis and centrifugal matrices and the hydrodynamic damping parameter matrix, respectively; represents the unknown external disturbance, where represents the disturbance of the unmanned boat in the longitudinal direction, Indicates the disturbance suffered by the unmanned boat in the lateral direction, Indicates the disturbance suffered by the unmanned boat in the yaw direction, middle 、 、 They are the surge, sway and pitch forces provided by the actuators respectively.

3. The method for consistent control of a multi-unmanned boat formation with finite time adaptive adjustment as claimed in claim 2, characterized in that: The nonlinear dynamic characteristics of each unmanned vehicle and the external disturbances are defined by assumptions, including: No. Nonlinear dynamic characteristics of an unmanned vehicle and disturbances The following conditions should be met: ； as well as ； in, is a positive but unknown constant.

4. The method for controlling a multi-unmanned boat formation with finite time adaptive adjustment as claimed in claim 3 is characterized in that: The position error and speed error of each unmanned boat include: Definition The position and velocity errors of the unmanned boat 、 ,in and Respectively The reference position and velocity signals expected by an unmanned boat satisfy: 。 5. The method for consistent control of a multi-unmanned watercraft formation with finite time adaptive regulation as claimed in claim 1, characterized in that: The adaptive law satisfies the following formula: ； as well as: ； as well as: ； in, is a positive constant.

6. A finite time adaptive adjustment multi-unmanned boat formation unanimous control system using the finite time adaptive adjustment multi-unmanned boat formation unanimous control method according to claim 1, characterized in that: include: An establishment module is configured to: establish a dynamic equation for each unmanned vehicle according to the dynamic characteristics of the multi-unmanned vehicle system, and define boundaries for the nonlinear dynamic characteristics and external disturbances of each unmanned vehicle by assuming; A definition module is configured to: define a position error and a velocity error of each unmanned vehicle, and define a condition for achieving bounded consistency of the multi-unmanned vehicle system; A construction module is configured to: define auxiliary variables according to the dynamic equations, nonlinear dynamic characteristics and external disturbances of each unmanned vehicle; construct a finite-time consistency control law and an adaptive law according to the auxiliary variables and the conditions for achieving bounded consistency of the multi-unmanned vehicle system; A determination module is configured to: determine a closed-loop error controller according to a position error, a velocity error, a finite-time consistency control law, and an adaptive law; A verification module is configured to: construct a Lyapunov function based on the auxiliary variables and the closed-loop error controller; and verify the error stability of the position and velocity of each unmanned boat through the Lyapunov function; The control module is configured to achieve consistency control of multiple unmanned boat formations based on a finite-time consistency control law.

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