A Dynamic Event-Triggered Trajectory Tracking Control Method and System for Underactuated Unmanned Surface Vehicles

Abstract

The present invention proposes a dynamic event-triggered trajectory tracking control method and system for an underactuated unmanned surface vehicle, belonging to the technical field of trajectory tracking. By acquiring the motion data of the underactuated unmanned surface vehicle, a kinematic model and a dynamic model of the underactuated unmanned surface vehicle are constructed. And an event-triggered state extended observer is established based on the kinematic model and the dynamic model. The event-triggered state extended observer is used to observe the error trajectory of the underactuated unmanned surface vehicle under event-triggered conditions. A dynamic event-triggered controller of the system is established, a virtual control function is designed based on the error trajectory, and the virtual control function is solved by using the adaptive law of uncertainty to obtain the optimal longitudinal thrust and steering moment. The dynamic event-triggered controller controls the tracking motion of the underactuated unmanned surface vehicle by outputting the optimal longitudinal thrust and steering moment. The present invention can achieve stable tracking control of the underactuated unmanned surface vehicle while ensuring a reduction in the number of actuator operations.

Description

Technical Field

[0001] The present invention belongs to the technical field of trajectory tracking, and in particular relates to a dynamic event-triggered trajectory tracking control method and system for an underactuated unmanned surface vehicle (USV). Background Art

[0002] The statements in this section merely provide background technical information related to the present invention and do not necessarily constitute prior art.

[0003] In recent years, with the acceleration of the development of the marine industry towards the deep sea and the open sea, underactuated USVs have attracted great interest in the control science community due to their simple control structure and low manufacturing cost. In terms of applications, underactuated USVs have been used in various scenarios, such as seabed resource exploitation, bathymetric survey, marine search and rescue, ocean investigation, sampling, and patrol.

[0004] However, there are still some technical problems in the existing trajectory tracking control methods for underactuated USVs, such as:

[0005] (1) Due to the complexity of the marine environment and the existence of unmodeled dynamics in the mathematical model of the USV, it will lead to a decline in the maneuverability of the USV and even cause system instability. In practical applications, the complexity of the marine environment and the strong coupling and modeling uncertainty existing in the mathematical model of the underactuated USV will lead to a decline in the control performance of the underactuated USV and even cause system performance instability.

[0006] (2) For the existing trajectory tracking control methods of underactuated USVs, real-time transmission of command signals from the controller to the actuator may lead to unnecessary communication burdens and excessive wear of the actuator.

[0007] In view of these challenges, it is crucial to conduct further research on underactuated USVs and promote their integration into ocean engineering. Summary of the Invention

[0008] To overcome the deficiencies of the above-mentioned prior art, the present invention provides a dynamic event-triggered trajectory tracking control method and system for an underactuated USV, which can achieve stable tracking control of the underactuated USV on the basis of ensuring a reduction in the number of actuator operations.

[0009] To achieve the above object, one or more embodiments of the present invention provide the following technical solutions:

[0010] The first aspect of the present invention provides a dynamic event-triggered trajectory tracking control method for an underactuated USV.

[0011] A dynamic event-triggered trajectory tracking control method for an underactuated USV includes:

[0012] Obtain the motion data of the underactuated unmanned surface vehicle (USV), and construct the kinematic model and dynamic model of the underactuated USV;

[0013] Based on the kinematic model and dynamic model of the underactuated USV, establish an event-triggered state extended observer;

[0014] Given the desired heading and define the tracking error, and use the event-triggered state extended observer to observe the error trajectory of the underactuated USV under event-triggered conditions;

[0015] Establish a dynamic event-triggered controller for the system, design a virtual control function based on the error trajectory, solve the virtual control function using the adaptive law of uncertainty, obtain the optimal longitudinal thrust and steering torque, and the dynamic event-triggered controller controls the tracking motion of the underactuated USV by outputting the optimal longitudinal thrust and steering torque.

[0016] Furthermore, when establishing the event-triggered state extended observer, the composite disturbance vector is time-varying and unknown.

[0017] Furthermore, use the earth-fixed coordinate system and body-fixed coordinate system to describe the kinematic model of the underactuated USV.

[0018] Furthermore, the error factors considered in the tracking error include: the longitudinal position error, lateral position error, and heading angle error of the underactuated USV.

[0019] Furthermore, when solving the virtual control function using the adaptive law of uncertainty, introduce a dynamic event-triggered mechanism so that the dynamic event-triggered control law is updated only at the trigger moment.

[0020] Furthermore, use Lyapunov theory to verify whether the tracking error converges within a small neighborhood of the origin.

[0021] Furthermore, the uncertainties corresponding to the adaptive rate include unmodeled dynamic uncertainties and external environmental disturbance uncertainties.

[0022] The second aspect of the present invention provides a dynamic event-triggered trajectory tracking control system for an underactuated USV.

[0023] A dynamic event-triggered trajectory tracking control system for an underactuated USV, comprising:

[0024] A model construction module, configured to: obtain the motion data of the underactuated USV, and construct the kinematic model and dynamic model of the underactuated USV;

[0025] An observer construction module, configured to: based on the kinematic model and dynamic model of the underactuated USV, establish an event-triggered state extended observer;

[0026] An error trajectory calculation module, configured to: given a desired course and define a tracking error, and utilize an event-triggered state extended observer to observe the error trajectory of an underactuated unmanned surface vehicle under event-triggered conditions;

[0027] A tracking control module, configured to: establish a dynamic event-triggered controller for the system, solve for a virtual control function using an adaptive law for uncertainty, obtain optimal longitudinal thrust and steering torque, and the dynamic event-triggered controller controls the tracking motion of the underactuated unmanned surface vehicle by outputting the optimal longitudinal thrust and steering torque.

[0028] A third aspect of the present invention provides a computer-readable storage medium, on which a program is stored, and when the program is executed by a processor, the steps in a method for dynamic event-triggered trajectory tracking control of an underactuated unmanned surface vehicle as described in the first aspect of the present invention are implemented.

[0029] A fourth aspect of the present invention provides an electronic device, including a memory, a processor, and a program stored on the memory and executable on the processor, and when the processor executes the program, the steps in a method for dynamic event-triggered trajectory tracking control of an underactuated unmanned surface vehicle as described in the first aspect of the present invention are implemented.

[0030] The above one or more technical solutions have the following beneficial effects:

[0031] (1) The present invention establishes an event-triggered state extended observer based on the kinematic model and dynamic model of an underactuated unmanned surface vehicle, and utilizes the event-triggered state extended observer to observe the error trajectory of the underactuated unmanned surface vehicle under event-triggered conditions; subsequently, a virtual control function is designed based on the error trajectory, and the virtual control function is solved using an adaptive law for uncertainty to obtain optimal longitudinal thrust and steering torque. The present invention comprehensively considers various uncertainty factors that an underactuated unmanned surface vehicle may encounter during actual tracking control, such as model error uncertainty and uncertainty of unknown forces formed in the marine environment. Therefore, the present invention can effectively improve the stability of the system and achieve stable tracking control of the underactuated unmanned surface vehicle.

[0032] (2) The present invention solves for the virtual control function using an adaptive law for uncertainty and introduces a dynamic event-triggered mechanism, such that the dynamic event-triggered control law is updated only at the trigger moment. Therefore, the present invention can effectively reduce the communication frequency between the controller and the actuator, thereby preventing unnecessary communication burdens and excessive wear of the actuator caused by the controller transmitting command signals to the actuator in real time.

[0033] Advantages of additional aspects of the present invention will be partially given in the following description, partially become apparent from the following description, or be understood through the practice of the present invention. Description of the Drawings

[0034] The accompanying drawings forming a part of this invention are used to provide a further understanding of the invention. The schematic embodiments and descriptions thereof of the invention are used to explain the invention and do not unduly limit the invention.

[0035] Figure 1 It is a flowchart of a dynamic event-triggered trajectory tracking control method for an underactuated unmanned surface vehicle in the first embodiment of the present invention.

[0036] Figure 2 It is a schematic diagram of the trajectory tracking of an underactuated unmanned surface vehicle in the first embodiment of the present invention. Detailed implementation manners

[0037] It should be noted that the following detailed descriptions are all exemplary and are intended to provide further explanations of the present invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by those of ordinary skill in the technical field to which the present invention belongs.

[0038] It should be noted that the terms used herein are only for describing specific implementation manners and are not intended to limit the exemplary implementation manners according to the present invention.

[0039] Without conflict, the embodiments in the present invention and the features in the embodiments can be combined with each other.

[0040] Embodiment 1

[0041] This embodiment discloses a dynamic event-triggered trajectory tracking control method for an underactuated unmanned surface vehicle.

[0042] As Figure 1 shown, a dynamic event-triggered trajectory tracking control method for an underactuated unmanned surface vehicle includes:

[0043] Step S1: Obtain the motion data of the underactuated unmanned surface vehicle, and construct the kinematic model and dynamic model of the underactuated unmanned surface vehicle;

[0044] Step S2: Based on the kinematic model and dynamic model of the underactuated unmanned surface vehicle, establish an event-triggered state extended observer;

[0045] Step S3: Given the desired heading and define the tracking error, and use the event-triggered state extended observer to observe the error trajectory of the underactuated unmanned surface vehicle under the event-triggered condition;

[0046] Step S4: Establish a dynamic event-triggered controller for the system, design a virtual control function based on the error trajectory, solve the virtual control function using the adaptive law of uncertainty, obtain the optimal longitudinal thrust and steering torque, and the dynamic event-triggered controller controls the tracking motion of the underactuated unmanned surface vehicle by outputting the optimal longitudinal thrust and steering torque.

[0047] Based on the above method, the present invention can achieve stable tracking control of an underactuated unmanned surface vehicle while ensuring a reduction in the number of actuator operations. To facilitate the understanding of the technical solution of the present invention, the specific implementation manners of the above steps of the present invention are further explained and described as follows:

[0048] Step S1: Obtain the motion data of the underactuated unmanned surface vehicle, and construct a kinematic model and a dynamic model of the underactuated unmanned surface vehicle.

[0049] The mathematical modeling of the underactuated unmanned surface vehicle is crucial for analyzing its motion dynamics. In recent research, the Fossen model has been widely used for the trajectory tracking control of the underactuated unmanned surface vehicle. In the Fossen model, the longitudinal thrust and turning moment of the underactuated unmanned surface vehicle (USV) are used as control outputs to regulate the motion of the underactuated unmanned surface vehicle. On this basis, the kinematic and dynamic models of the USV are mathematically expressed as follows:

[0050] ;

[0051] Where, represents the propulsion, lateral displacement, and yaw angle of the ship in the inertial coordinate system; As η the derivative of, it represents the velocity vector of the underactuated unmanned surface vehicle in the body coordinate system. represents the velocity vector of the ship in the body-fixed coordinate system; is the forward velocity of the ship in the appended body coordinate system, is the transverse drift velocity in the appended body coordinate system, is the yaw angular velocity in the appended body coordinate system. represents the transformation matrix between the inertial coordinate system and the body-fixed coordinate system, satisfying . represents the inertia matrix of the ship, represents the Coriolis and centripetal matrix; represents the damping matrix. is the control force and moment vector of the underactuated ship; where, and represent the longitudinal thrust and turning moment respectively. For the underactuated ship, there is no lateral thruster, so represents the unknown external time-varying disturbance in the body-fixed coordinate system. , , and The expressions of are as follows:

[0052] ;

[0053] Where, represents the mass coefficient when the underactuated unmanned surface vehicle (USV) surges in the hull coordinate system, and ; represents the mass coefficient when the underactuated USV sways in the hull coordinate system, and ; represents the mass coefficient of the yaw angular acceleration of the underactuated USV in the hull coordinate system, and ; represents the longitudinal linear damping coefficient due to the longitudinal acceleration, and ; represents the lateral linear damping coefficient due to the lateral velocity of the ship, and ; represents the yaw linear damping coefficient due to the angular velocity, and . represents the mass of the underactuated ship, represents the moment of inertia of the ship, represents the hydrodynamic derivative.

[0054] Furthermore, in this embodiment, the geodetic coordinate system and the body-fixed coordinate system are used to describe the kinematic model of the underactuated USV. Specifically, the kinematic models in the two coordinate systems are as follows:

[0055] ;

[0056] , and are defined in the coordinate system. Among them, and respectively represent the lateral position and longitudinal position of the USV in the geodetic coordinate system; As the x derivative, it represents the forward speed of the USV in the geodetic coordinate system; As the y derivative, it represents the sway speed of the USV in the geodetic coordinate system. represents the yaw angle, As the derivative, it represents the yaw speed of the USV in the geodetic coordinate system. , , respectively represent the surge speed, sway speed and yaw speed in the coordinate system.

[0057] The dynamic models in the two coordinate systems are as follows:

[0058] ;

[0059] Among them, , and respectively represent the modeling uncertainties existing in the surge, sway, and yaw direction accelerations of the system; , and respectively represent the unknown external forces acting on the system in the surge, sway, and yaw direction accelerations.

[0060] Step S2: Based on the kinematic model and dynamic model of the underactuated unmanned surface vehicle, establish an event-triggered state extended observer.

[0061] During the navigation of the underactuated unmanned surface vehicle, it is difficult to directly measure its velocity vector, and the velocity vector can be obtained through an extended observer. Usually, the data exchange of the underactuated unmanned surface vehicle is carried out through a wireless communication network, which involves connecting system components through a communication link, such as a sensor, controller, filter, and actuator network. The controller is located on a remote mother ship or a land base; the most important thing is to reduce the computational cost and save communication resources to achieve sufficient control.

[0062] Therefore, under the assumption that the state of the system is unknown, the following event-triggered state observer is adopted in this embodiment for observation:

[0063] ;

[0064] Let , . Among them, represents the rotation matrix, represents the derivative of the rotation matrix; represents the surge, sway, and yaw direction accelerations. Therefore, the dynamic model of the underactuated unmanned surface vehicle (USV) can be expressed as:

[0065] ;

[0066] Among them, represents the lumped uncertainty, including unmodeled dynamics and external disturbances. Specifically, the external disturbance is the uncertainty of the unknown force that may be generated in the marine environment; therefore, the present invention can effectively improve the stability of the system and achieve stable tracking control of the underactuated unmanned surface vehicle. The composite disturbance vector is time-varying and unknown, and its Euclidean norm is bounded by a constant, that is, ; among them, is a constant. In addition, the lumped uncertainty satisfies ; among them, is an unknown bounded constant.

[0067] Furthermore, the event-triggered observer is designed as follows:

[0068] ;

[0069] Wherein, , and are the estimated values of , and , respectively. The parameter is a high-gain parameter to be determined. The function ( ) is defined as follows:

[0070] .

[0071] Only by ensuring that the matrix is a Hurwitz constant can the convergence of ETESO be guaranteed; the matrix is expressed as:

[0072] ;

[0073] Meanwhile, is defined as:

[0074] ;

[0075] Wherein, represents a piecewise function. Furthermore, let represent the measured output position of the ship and is defined as: .

[0076] The event-triggering condition is given by the following formula: . Wherein, is a positive constant to be determined, and is the Lipschitz constant of . represents the sampling error, and , . Wherein, represents the triggering instant, represents the event-triggering condition, and in this embodiment, the sum of the errors is used as the event-triggering condition.

[0077] Step S3: Given the desired course and define the tracking error, and use the event-triggered state extended observer to observe the error trajectory of the underactuated unmanned surface vehicle under the event-triggering condition.

[0078] For the given sliding reference trajectory , the following tracking error is defined:

[0079] ;

[0080] Among them, represents the position of the USV in the geodetic coordinate system, represents the heading angle of the ship. The terms , and represent the longitudinal position error, the lateral position error, and the heading angle error, respectively. In addition, ; among them, and represent the vertical and horizontal position errors, respectively. These errors correspond to the horizontal and vertical coordinates of the reference trajectory. The following equation describes the desired heading:

[0081] ;

[0082] where, represents the desired heading trajectory; and represent the lateral velocity and the longitudinal velocity of the target trajectory in the geodetic coordinate system, respectively.

[0083] As Figure 2 shown, the coordinate system represents the inertial reference frame. Among them, the point is the initial position, axis points due north, while axis points due west; the point is defined as the midpoint between the bow and the stern of the USV. The vector points along the midline of the USV towards the bow, while the vector points along the port side direction of the USV; the line segment AB represents the reference trajectory.

[0084] Step S4: Establish the dynamic event-triggered controller of the system, design the virtual control function based on the error trajectory, solve the virtual control function using the adaptive law of uncertainty, obtain the optimal longitudinal thrust and steering moment, and the dynamic event-triggered controller controls the tracking motion of the underactuated unmanned surface vehicle by outputting the optimal longitudinal thrust and steering moment.

[0085] Step S4-1: According to the relationship shown in Figure 2 , the variables , and can be expressed by the following formula:

[0086] ;

[0087] where, is an intermediate variable used to characterize the variable and The variation of; for the variable and Taking the time derivative, the following equation can be derived:

[0088] ;

[0089] where represents the lateral acceleration of the target trajectory, represents the heading angle error, represents the variation law of the heading angle error, represents the variation law of the desired heading angle.

[0090] Step S4-2, Design the virtual control functions and as follows:

[0091] ;

[0092] where , , , , and are design parameters. It should be noted that when , becomes undefined. Therefore, in practical engineering, the first assumption is that the condition holds, and this assumption is guaranteed through the following equation transformation, that is:

[0093] ;

[0094] Step S4-3, To prevent dimensional explosion, introduce a first-order filter, that is:

[0095] ;

[0096] where represents the estimated value of the output of the first-order filter for the input, represents the estimated value of the derivative of the input by the first-order filter; represents the time constant; α represents the input of the first-order filter, represents the initial estimated value of the output of the first-order filter for the input, represents the initial value of the input of the first-order filter.

[0097] ;

[0098] where represents the virtual controller function filtered by the first-order filter , Denotes the virtual controller function filtered by a first-order filter , Denotes the actual u And the one filtered by a first-order filter The error between them, Denotes the actual r And the one filtered by a first-order filter The error between them.

[0099] Introduce the INTSM surface for longitudinal error and yaw rate error, that is:

[0100] ;

[0101] Given , And As design constants, continue to differentiate To obtain:

[0102] ;

[0103] Advance the motion control law And the yaw motion control law Can be designed as:

[0104] ;

[0105] Among them, , And Respectively represent the estimates of ETESO for u , v And r ; Represents the parameter The adaptation rate of.

[0106] ;

[0107] Among them, , , , Are all positive constants; And Respectively represent the estimates of And The corresponding adaptation laws are given in the equation, that is:

[0108] ;

[0109] Therefore, the adaptation law for the model uncertainty of the underactuated unmanned surface vehicle (USV) is defined as follows:

[0110] ;

[0111] Step S4-4: Introduce a dynamic event-triggered control scheme. Specifically, first define the dynamic event-triggered control law as . Obviously, is only updated at the trigger moment ; where . On this basis, define the measurement error z ( t ) as:

[0112] ;

[0113] Furthermore, the dynamic event-triggered mechanism is designed as follows:

[0114] ;

[0115] where is an internal dynamic variable that satisfies the following conditions, i.e.:

[0116] ;

[0117] Obviously, the inequality always holds. Now it will be proved that indeed holds. Specifically, according to 's definition, it can be obtained that for all . Therefore, for all , can be further deduced as . Then, through the comparison lemma, it can be obtained that for all , .

[0118] Step S4-4: Use Lyapunov theory to verify whether the tracking error converges within a small neighborhood of the origin. The Lyapunov function is expressed as follows:

[0119] ;

[0120] Based on the Lyapunov function, it can be proved that the states of the system are all uniformly ultimately bounded. Since proving the consistency and boundedness of the system states based on the Lyapunov function is not the main technical point of the present invention, it will not be elaborated here too much.

[0121] Furthermore, the USV model parameters used in the specific implementation process of this embodiment are shown in Table 1:

[0122] Table 1 USV model parameters

[0123]

[0124] Table 2 Parameters in the control scheme

[0125]

[0126] As can be seen from Table 1, the internal disturbances and external disturbances of the system are respectively , , , .

[0127] Meanwhile, the predetermined trajectory of the USV set in the specific implementation process of this embodiment, that is, the time-varying trajectory is .

[0128] Based on the USV model parameters in Table 1 and the above-given time-varying trajectory, this embodiment simulates the trajectory tracking problem of an underactuated unmanned surface vehicle (USV) under dynamic uncertainties and unknown environmental disturbances. In the control design, the ETESO measurement system measures the speed and can accurately estimate the unmeasurable speed and convergent disturbances. To improve the robustness of the control system, a multi-layer perceptron (MLP) neural network is used to approximate and compensate for the model uncertainties. In addition, based on the backstepping method, the INTSM method is combined with the DETM. This scheme not only inherits the advantages of traditional sliding mode control and neural network control, but also further reduces the occupation of communication resources by introducing a dynamic event-triggering mechanism. In addition, the stability of the closed-loop control system is strictly guaranteed by using the Lyapunov theory, and it has been proved that the tracking error converges to a small neighborhood of the origin.

[0129] It can be seen that the present invention simultaneously takes into account the problems of complex external environments, unknown dynamic parameters, unnecessary communication burdens of actuators, and excessive wear of actuators, and can achieve stable tracking control of an underactuated unmanned surface vehicle while ensuring a reduction in the number of actuator operations.

[0130] Embodiment 2

[0131] This embodiment discloses an underactuated unmanned surface vehicle dynamic event-triggering trajectory tracking control system.

[0132] An underactuated unmanned surface vehicle dynamic event-triggering trajectory tracking control system includes:

[0133] A model construction module configured to: obtain the motion data of the underactuated unmanned surface vehicle and construct the kinematic model and dynamic model of the underactuated unmanned surface vehicle;

[0134] An observer construction module configured to: establish an event-triggering state extended observer based on the kinematic model and dynamic model of the underactuated unmanned surface vehicle;

[0135] An error trajectory calculation module, configured to: given a desired heading and define a tracking error, and utilize an event-triggered state extended observer to observe the error trajectory of an underactuated unmanned surface vehicle under event-triggered conditions;

[0136] A tracking control module, configured to: establish a dynamic event-triggered controller for the system, solve a virtual control function by using an adaptive law for uncertainty, obtain optimal longitudinal thrust and steering torque, and the dynamic event-triggered controller controls the tracking motion of the underactuated unmanned surface vehicle by outputting the optimal longitudinal thrust and steering torque.

[0137] Embodiment III

[0138] The purpose of this embodiment is to provide a computer-readable storage medium.

[0139] A computer-readable storage medium, on which a computer program is stored, and when the program is executed by a processor, it implements the steps in a method for dynamic event-triggered trajectory tracking control of an underactuated unmanned surface vehicle as described in Embodiment I of the present disclosure.

[0140] Embodiment IV

[0141] The purpose of this embodiment is to provide an electronic device.

[0142] An electronic device, including a memory, a processor, and a program stored on the memory and executable on the processor. When the processor executes the program, it implements the steps in a method for dynamic event-triggered trajectory tracking control of an underactuated unmanned surface vehicle as described in Embodiment I of the present disclosure.

[0143] The steps involved in the devices in the above Embodiments II, III, and IV correspond to those in Method Embodiment I. For specific implementation manners, reference may be made to the relevant description part of Embodiment I. The term "computer-readable storage medium" should be understood to include a single medium or multiple media including one or more instruction sets; it should also be understood to include any medium that can store, encode, or carry an instruction set for execution by a processor and enable the processor to execute any method in the present invention.

[0144] Those skilled in the art should understand that the above-mentioned modules or steps of the present invention can be implemented by a general-purpose computer device. Optionally, they can be implemented by program codes executable by a computing device, so that they can be stored in a storage device and executed by the computing device, or they can be separately fabricated into individual integrated circuit modules, or multiple modules or steps among them can be fabricated into a single integrated circuit module for implementation. The present invention is not limited to any specific combination of hardware and software.

[0145] Although the specific implementation manners of the present invention have been described above in conjunction with the accompanying drawings, it is not a limitation on the protection scope of the present invention. Those skilled in the art should understand that various modifications or deformations that can be made without creative efforts on the basis of the technical solution of the present invention are still within the protection scope of the present invention.

Claims

1. A dynamic event-triggered trajectory tracking control method for an underactuated unmanned boat, characterized in that: include: Obtain the motion data of the underactuated unmanned boat and build the kinematic model and dynamic model of the underactuated unmanned boat; An event-triggered state extended observer is established based on the kinematic model and dynamic model of the underactuated unmanned vehicle; the event triggering condition of the event-triggered state extended observer is: ,in, is a positive constant to be determined, yes The Lipschitz constant, parameter is a high gain parameter that needs to be determined. represents the sampling error, and , ,in, Indicates the trigger instant; Indicates the conditions for event triggering; Given the desired heading and defining the tracking error, the event-triggered state extended observer is used to observe the error trajectory of the underactuated unmanned vehicle under event-triggered conditions. The dynamic event-triggered controller of the system is established, and the virtual control function is designed based on the error trajectory. The virtual control function is solved using the adaptive law of uncertainty to obtain the optimal longitudinal thrust and steering torque. The longitudinal thrust and steering torque are expressed as and Indicates; where longitudinal thrust Specifically: in, represents the mass coefficient of the underactuated unmanned vehicle under the hull coordinate system during the longitudinal acceleration; Representation parameters Adaptation rate; INTSM surface representing longitudinal error; represents the mass coefficient of the underactuated unmanned vehicle under the sway acceleration in the hull coordinate system; , and Respectively represent ETESO u , v and r An estimated value of Steering torque Specifically: in, The mass coefficient representing the bow angular acceleration of the underactuated unmanned vehicle in the hull coordinate system; INTSM surface representing yaw rate error; represents the linear damping coefficient of the bow due to the angular velocity; , , , All are normal numbers; and Respectively express and estimates; and They represent the modeling uncertainty of the acceleration of the system in the surge and yaw directions respectively; The dynamic event triggered controller controls the tracking motion of the underactuated unmanned vehicle by outputting the optimal longitudinal thrust and steering torque. When solving the virtual control function using the adaptive law of uncertainty, a dynamic event trigger mechanism is introduced so that the dynamic event triggered control law is updated only at the triggering moment. The uncertainty corresponding to the adaptive rate includes the unmodeled dynamic uncertainty and the external environmental interference uncertainty. A multilayer perceptron neural network is used to approximate and compensate for the uncertainty of the model.

2. The method for controlling the trajectory tracking of an underactuated unmanned vehicle triggered by a dynamic event according to claim 1, characterized in that: When establishing the event-triggered state extended observer, the composite disturbance vector is time-varying and unknown.

3. The method for controlling a dynamic event-triggered trajectory tracking of an underactuated unmanned vehicle according to claim 1, characterized in that: The geodetic coordinate system and body-attached coordinate system are used to describe the kinematic model of the underactuated unmanned vehicle.

4. The method for controlling a dynamic event-triggered trajectory tracking of an underactuated unmanned vehicle according to claim 1, characterized in that: The error factors considered in the tracking error include: longitudinal position error, lateral position error and heading angle error of the underactuated unmanned vehicle.

5. The method for controlling the trajectory tracking of an underactuated unmanned vehicle triggered by a dynamic event according to claim 1, characterized in that: Lyapunov theory is used to verify whether the tracking error converges to a small neighborhood of the origin.

6. A dynamic event-triggered trajectory tracking control system for an underactuated unmanned boat, characterized in that: include: The model building module is configured to: obtain motion data of the underactuated unmanned boat, and build a kinematic model and a dynamic model of the underactuated unmanned boat; The observer construction module is configured to: establish an event-triggered state extension observer based on the kinematic model and dynamic model of the underactuated unmanned boat; the event triggering condition of the event-triggered state extension observer is: ,in, is a positive constant to be determined, yes The Lipschitz constant, parameter is a high gain parameter that needs to be determined. represents the sampling error, and , ,in, Indicates the trigger instant; Indicates the conditions for event triggering; The error trajectory calculation module is configured to: given a desired heading and defining a tracking error, use an event-triggered state extended observer to observe the error trajectory of the underactuated unmanned vehicle under event-triggered conditions; The tracking control module is configured to: establish a dynamic event trigger controller for the system, use the adaptive law of uncertainty to solve the virtual control function, and obtain the optimal longitudinal thrust and steering torque. The longitudinal thrust and steering torque are respectively and Indicates; where longitudinal thrust Specifically: in, represents the mass coefficient of the underactuated unmanned vehicle under the hull coordinate system during the longitudinal acceleration; Representation parameters Adaptation rate; INTSM surface representing longitudinal error; represents the mass coefficient of the underactuated unmanned vehicle under the sway acceleration in the hull coordinate system; , and Respectively represent ETESO u , v and r An estimated value of Steering torque Specifically: in, The mass coefficient representing the bow angular acceleration of the underactuated unmanned vehicle in the hull coordinate system; INTSM surface representing yaw rate error; represents the linear damping coefficient of the bow due to the angular velocity; , , , All are normal numbers; and Respectively express and estimates; and They represent the modeling uncertainty of the acceleration of the system in the surge and yaw directions respectively; The dynamic event triggered controller controls the tracking motion of the underactuated unmanned vehicle by outputting the optimal longitudinal thrust and steering torque. When solving the virtual control function using the adaptive law of uncertainty, a dynamic event trigger mechanism is introduced so that the dynamic event triggered control law is updated only at the triggering moment. The uncertainty corresponding to the adaptive rate includes the unmodeled dynamic uncertainty and the external environmental interference uncertainty. A multilayer perceptron neural network is used to approximate and compensate for the uncertainty of the model.

7. A computer-readable storage medium having a program stored thereon, characterized in that: When the program is executed by a processor, the steps of the dynamic event triggered trajectory tracking control method for an under-actuated unmanned boat as described in any one of claims 1 to 5 are implemented.

8. An electronic device comprising a memory, a processor, and a program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the steps in the dynamic event triggered trajectory tracking control method for an under-actuated unmanned boat as described in any one of claims 1-5 are implemented.

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