An unmanned ship parallel preset performance track tracking control method for high-precision operation

Abstract

This invention discloses a parallel preset performance trajectory tracking control method for unmanned surface vessels (USVs) oriented towards high-precision operations. This method establishes a real USV system model considering environmental interference, then combines a fuzzy logic system, filters, data stacks, and an extended state observer to construct an artificial USV system model, achieving dynamic interaction between the virtual and real spaces. Subsequently, a preset performance function is designed and an error transformation function is constructed to solve the initial value constraint problem of the preset performance control. Finally, a kinematic guidance law and a parallel preset performance trajectory tracking controller are designed to generate control signals and achieve parallel control of the real and artificial USVs. This invention reduces the cost and risk of real-vehicle testing, improves control efficiency, optimizes the transient and steady-state performance of system trajectory tracking, and broadens the engineering application scope of preset performance control.

Description

Technical Field

[0001] This invention relates to the field of unmanned surface vessel (USV) trajectory tracking and control technology, and more particularly to a parallel preset performance trajectory tracking and control method for USVs for high-precision operations. Background Technology

[0002] Unmanned surface vessels (USVs), as intelligent surface navigation systems, play a significant role in many fields such as marine resource exploration, maritime transportation, and national defense, and have therefore attracted much attention. Trajectory tracking, a key technology in USV control, directly affects the realization of high-precision tasks such as marine surveillance and collaborative operations. Its control accuracy is a core indicator for measuring the maneuverability, environmental adaptability, and automation level of USVs. Therefore, deepening research on this technology has significant strategic value for enhancing marine industry capabilities.

[0003] However, as operational tasks become increasingly complex and sophisticated, the performance requirements for trajectory tracking in both transient and steady-state conditions are constantly rising. Therefore, pre-defined performance control methods have become a research hotspot. This method mainly includes two steps: first, designing a suitable performance function to improve the dynamic performance of tracking errors; second, transforming the error constraint problem into a bounded control problem of the transformed system through error transformation. Currently, related research focuses on improving and optimizing the performance function, and has made positive theoretical progress, further promoting the realization of high-precision trajectory tracking for unmanned surface vessels.

[0004] However, existing trajectory tracking and control methods for unmanned surface vessels have the following shortcomings:

[0005] First, traditional ship trajectory tracking and control methods are mostly designed directly based on the physical state of the ship in the real ocean environment. However, the real ocean environment itself is an open and highly uncertain complex system. At the same time, because these methods fail to achieve dynamic interaction between virtual and real space, they often lead to problems such as low efficiency, high cost, and high risk in actual ship testing and verification.

[0006] Second, existing parallel trajectory tracking control methods for unmanned surface vessels (USVs) often focus on synchronizing the state of the human and the actual system, failing to impose higher requirements on the trajectory tracking accuracy of USVs, and failing to constrain indicators such as the convergence speed of tracking errors. This results in the tracking accuracy failing to meet the actual needs of high-precision tasks such as marine resource exploration and maritime collaborative operations, which to some extent limits the application of parallel control technology for USVs. Summary of the Invention

[0007] To address the aforementioned problems, the technical solution adopted by this invention is: a parallel preset performance trajectory tracking and control method for unmanned surface vessels (USVs) oriented towards high-precision operations, comprising the following steps: S1: Construct a practical unmanned surface vessel system that takes into account environmental interference; S2: Use a fuzzy logic system to model the unknown dynamics of the actual unmanned surface vessel (USV) system, and complete the equivalent model of the dynamics of the actual USV. Then design filters to filter the basis functions of the fuzzy logic system and the equivalent computable quantities of the unknown dynamics of the actual USV, and store the filtered data in the data stack. Combine the extended state observer with the equivalent dynamics model of the actual USV to construct the artificial unmanned surface vessel system model. S3: Based on the constructed artificial unmanned surface vessel (USV) system model, define the trajectory tracking error between the USV system model and the reference trajectory of the actual USV; select a preset performance function to construct a corresponding preset performance boundary for the trajectory tracking error; design an error transformation function according to the preset performance function to transform the constrained trajectory tracking error into an unconstrained error transformation variable, thus solving the initial value constraint problem of preset performance control. S4: Based on the variables after error transformation, combined with the position, bow angle, and velocity information of the actual unmanned surface vessel system in the Earth coordinate system considering environmental interference, as well as the estimated position, bow angle, and velocity values ​​of the actual unmanned surface vessel output by the extended state observer, and simultaneously integrating the dynamic characteristics of the reference trajectory signal and the preset performance function, the kinematic guidance law of the artificial unmanned surface vessel system is designed. S5: Based on the kinematic guidance law of the artificial unmanned surface vessel system, the estimated value of the unknown dynamics of the actual unmanned surface vessel system, and the estimated value of the modeling approximation estimation error obtained by combining the extended state observer, a parallel preset performance trajectory tracking controller for the artificial unmanned surface vessel system is designed to generate a control signal; then the control signal is synchronously applied to the actual unmanned surface vessel system and the artificial unmanned surface vessel system to achieve dynamic synchronization of their states, and finally complete the parallel trajectory tracking control of the actual unmanned surface vessel system and the artificial unmanned surface vessel system.

[0008] Furthermore, the actual unmanned surface vessel system model considering environmental interference is as follows:

[0009] in, , This indicates the actual location information of the unmanned surface vessel. This indicates the actual bow roll angle of the unmanned surface vessel; This indicates the actual speed information of the unmanned surface vessel. These represent the longitudinal velocity, lateral velocity, and bow roll rate of the actual unmanned surface vessel, respectively. This represents the actual control input of the unmanned surface vessel; = Represents the inertial mass matrix; Represents the centripetal force and Coriolis coefficient matrix; Represents the nonlinear damping matrix; Indicates unknown hydrodynamic damping; This indicates an unknown external disturbance caused by wind, waves, and currents; This represents the rotation matrix.

[0010] Furthermore, the construction steps of the artificial unmanned surface vessel system model are as follows: The actual unmanned surface vessel system model is rewritten as follows:

[0011] in, , This indicates the actual location information of the unmanned surface vessel. This indicates the actual bow roll angle of the unmanned surface vessel; Represents the rotation matrix; This indicates the actual speed information of the unmanned surface vessel. These represent the longitudinal velocity, lateral velocity, and bow roll rate of the actual unmanned surface vessel, respectively. Represents the inertial mass matrix The nominal value; This represents the actual control input of the unmanned surface vessel; Indicates the unknown dynamics of the actual unmanned surface vessel. The equivalent computable quantity, These represent the unknown dynamic components of the actual unmanned surface vessel (USV) in the longitudinal, lateral, and bow-roll dimensions, respectively. The definition is as follows:

[0012] The unknown dynamics of a real unmanned surface vessel (USV) are modeled using a fuzzy logic system. The equivalent mathematical model of the dynamics of the real USV is shown below:

[0013] in, Represents the nominal value of the inertial mass matrix; This represents the matrix inverse operation; This represents the actual control input of the unmanned surface vessel; , Both represent the basis functions of the fuzzy logic system; Indicates modeling bias; By fuzzy weights composition, These represent the fuzzy weight vectors corresponding to the longitudinal, lateral, and pitch directions, respectively. It is expressed as follows:

[0014] The filter is defined as follows:

[0015] and in, It is the filter output; These are the filter parameters; Both represent the basis functions of the fuzzy logic system; This represents the equivalent computable quantity of unknown dynamics of an actual unmanned surface vessel. The amount; Represented by the natural logarithm Exponentiation to base 1; Indicates time; They represent The initial value; express The derivative; similarly, They represent The initial value; Based on the filter, the artificial unmanned surface vessel system is constructed as follows, combined with the extended state observer:

[0016]

[0017] in, express The estimated value; Represents the rotation matrix; Indicates the actual speed information of the unmanned surface vessel. The estimated value; Indicates the estimation error; express The derivative; Represents the nominal value of the inertial mass matrix; This represents the matrix inverse operation; This represents the actual control input of the unmanned surface vessel; Indicating modeling bias The estimated value; , Both represent the basis functions of the fuzzy logic system; express The estimated value; All are design parameters; They represent The estimated value; Indicates the length of the data stack; Indicates adaptive gain; Indicates projection operation; These represent the data stack after filtering. Stored in exist The value at any given moment.

[0018] Furthermore: Based on the constructed unmanned surface vessel (USV) system model, the trajectory tracking error between the USV system model and the reference trajectory is defined; a preset performance function is selected and designed to construct a corresponding preset performance boundary for the trajectory tracking error; an error transformation function is designed according to the preset performance function to transform the constrained trajectory tracking error into an unconstrained error transformation variable. The process of solving the initial value constraint problem of the preset performance control is as follows: The trajectory tracking error of an unmanned surface vessel (USV) system is defined as follows:

[0019] in, Indicates the reference trajectory; This indicates the actual location and bow angle information of the unmanned surface vessel. The estimated value; Define preset performance boundaries to constrain trajectory tracking errors as follows:

[0020] in, Indicates the preset performance function Indicates and The relevant global Lipschitz continuity function, and They represent Initial and final values, The amount; Construct the error transformation function and obtain the variable after error transformation. As shown below:

[0021] in, The amount; Indicates the preset performance function; Represents the tangent function. .

[0022] Furthermore: The process of designing the kinematic guidance law of the artificial unmanned surface vessel system based on the error-transformed variables, combined with the position, bow angle, and velocity information of the actual unmanned surface vessel system in the Earth coordinate system considering environmental interference, as well as the estimated position, bow angle, and velocity values ​​of the actual unmanned surface vessel output by the extended state observer, and simultaneously integrating the dynamic characteristics of the reference trajectory signal and the preset performance function, is as follows: Define auxiliary positive definite matrices respectively and diagonal matrix As shown below:

[0023] and

[0024] in, The variable represents the result of the error transformation; Indicates the preset performance function; ; Represents the cosine function; Design the kinematic guidance law for an unmanned surface vessel system. as follows:

[0025] in, Represents the rotation matrix; ; This represents the matrix inverse operation; ; Represents a diagonal matrix; Represents the control parameter matrix; ; For design parameters; Indicates the estimation error; Indicates the reference trajectory; ; express The derivative; .

[0026] Furthermore, the process of the parallel preset performance trajectory tracking controller of the artificial unmanned surface vessel system is as follows:

[0027] in, Represents the nominal value of the inertial mass matrix; This represents the control parameter matrix of the parallel preset performance trajectory tracking controller; Indicates the dynamic velocity tracking error. Indicates the actual speed information of the unmanned surface vessel. The estimated value, This describes the kinematic guidance law of the designed unmanned surface vessel system; ; ; Represents the rotation matrix; Represents the variable after error transformation ; , Both represent the basis functions of the fuzzy logic system. Represents a column vector composed of the basis functions of a fuzzy logic system; express The derivative; express The estimated value; Indicating modeling bias The estimated value.

[0028] A parallel preset performance trajectory tracking and control device for unmanned surface vessels (USVs) designed for high-precision operations includes: Practical Unmanned Surface Vessel System Construction Module: Used to construct practical unmanned surface vessel systems that take environmental interference into account; Artificial Unmanned Surface Vessel (USV) System Construction Module: This module is used to model the unknown dynamics of the actual USV system using a fuzzy logic system, thus completing the equivalent model of the actual USV dynamics. Then, filters are designed to filter the basis functions of the fuzzy logic system and the equivalent computable quantities of the unknown dynamics of the actual USV, and the filtered data is stored in a data stack. Finally, the extended state observer and the equivalent dynamics model of the actual USV are combined to construct the artificial USV system model. Preset performance control module: Based on the constructed artificial unmanned surface vessel system model, the trajectory tracking error between the model and the reference trajectory of the actual unmanned surface vessel is defined; a preset performance function is selected and designed to construct a corresponding preset performance boundary for the trajectory tracking error; an error transformation function is designed according to the preset performance function to transform the constrained trajectory tracking error into an unconstrained error transformation variable, thus solving the initial value constraint problem of preset performance control; Kinematic guidance law module: Based on the variables after error transformation, combined with the position, bow angle, and velocity information of the actual unmanned surface vessel system in the Earth coordinate system considering environmental interference, as well as the estimated position, bow angle, and velocity values ​​of the actual unmanned surface vessel output by the extended state observer, and simultaneously integrating the dynamic characteristics of the reference trajectory signal and the preset performance function, the kinematic guidance law of the artificial unmanned surface vessel system is designed. Parallel trajectory tracking controller module: Based on the kinematic guidance law of the artificial unmanned surface vessel (USV) system, the estimated value of the unknown dynamics of the actual USV system, and the estimated value of the modeling approximation estimation error obtained by combining the extended state observer, a parallel preset performance trajectory tracking controller for the USV system is designed to generate a control signal; then, the control signal is synchronously applied to the actual USV system and the artificial USV system to achieve dynamic synchronization of their states, and finally complete the parallel trajectory tracking control of the actual USV system and the artificial USV system.

[0029] The present invention provides a parallel preset performance trajectory tracking and control method and system for unmanned surface vessels (USVs) oriented towards high-precision operations. Compared with the prior art, the present invention has the following advantages: First, compared with existing traditional trajectory tracking control strategies, this invention utilizes fuzzy logic systems and extended state observers to model the actual unmanned surface vessel system model as an artificial unmanned surface vessel system model, reducing the cost and risk of actual ship testing and verification, and improving efficiency.

[0030] Secondly, compared with the existing parallel trajectory tracking control strategy of unmanned surface vessels, the present invention introduces a preset performance control method into the control strategy, which can effectively improve the transient and steady-state performance of the system and meet the accuracy requirements of unmanned surface vessel trajectory tracking in engineering.

[0031] Third, compared with existing preset performance control methods, constructing a suitable error transformation function can solve the problem of initial value constraints, thus broadening the application scope of preset performance control in engineering. Attached Figure Description

[0032] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0033] Figure 1 This is a flowchart of a parallel preset performance trajectory tracking and control method for unmanned surface vessels for high-precision operations according to the present invention; Figure 2 This is a schematic diagram of the unmanned surface vessel parallel preset performance trajectory tracking control system in an embodiment of the present invention; Figure 3 This is a schematic diagram illustrating the trajectory tracking and control performance of the unmanned surface vessel in an embodiment of the present invention; Figure 4 This is a schematic diagram illustrating the tracking error and preset performance constraints in an embodiment of the present invention; wherein (a) Directional trajectory tracking error versus preset performance boundary curve, (b) Direction trajectory tracking error versus preset performance boundary curve, (c) bow roll angle Direction trajectory tracking error versus preset performance constraint curve; Figure 5 This is a schematic diagram illustrating the position and heading estimation performance of the unmanned surface vessel in an embodiment of the present invention, wherein (a) (b) Comparison curve of estimated position of actual unmanned surface vessel in direction, actual position and expected position. (c) Comparison curve of estimated position, actual position and expected position of unmanned surface vessel (USV), and actual bow roll angle of USV. A curve comparing the estimated value, the actual value, and the expected value. Detailed Implementation

[0034] It should be noted that, unless otherwise specified, the embodiments and features in the embodiments of the present invention can be combined with each other. The present invention will be described in detail below with reference to the accompanying drawings and embodiments.

[0035] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The following description of at least one exemplary embodiment is merely illustrative and is in no way intended to limit the present invention or its application or use. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0036] Figure 1 This is a flowchart of a parallel preset performance trajectory tracking and control method for unmanned surface vessels for high-precision operations according to the present invention; A method for parallel preset performance trajectory tracking and control of unmanned surface vessels (USVs) for high-precision operations includes the following steps: S1: Establish a practical unmanned surface vessel system model that takes into account environmental interference; S2: Use a fuzzy logic system to model the unknown dynamics of the actual unmanned surface vessel (USV) system, and complete the equivalent model of the dynamics of the actual USV. Then design filters to filter the basis functions of the fuzzy logic system and the equivalent computable quantities of the unknown dynamics of the actual USV, and store the filtered data in the data stack. Combine the extended state observer with the equivalent dynamics model of the actual USV to construct the artificial unmanned surface vessel system model. S3: Based on the constructed artificial unmanned surface vessel (USV) system model, define the trajectory tracking error between the USV system model and the reference trajectory of the actual USV; select a preset performance function to construct a corresponding preset performance boundary for the trajectory tracking error; design an error transformation function according to the preset performance function to transform the constrained trajectory tracking error into an unconstrained error transformation variable, thus solving the initial value constraint problem of preset performance control. S4: Based on the variables after error transformation, combined with the position, bow angle, and velocity information of the actual unmanned surface vessel system in the Earth coordinate system considering environmental interference, as well as the estimated position, bow angle, and velocity values ​​of the actual unmanned surface vessel output by the extended state observer, and simultaneously integrating the dynamic characteristics of the reference trajectory signal and the preset performance function, the kinematic guidance law of the artificial unmanned surface vessel system is designed. S5: Based on the kinematic guidance law of the artificial unmanned surface vessel system, the estimated value of the unknown dynamics of the actual unmanned surface vessel system, and the estimated value of the modeling approximation estimation error obtained by combining the extended state observer, a parallel preset performance trajectory tracking controller for the artificial unmanned surface vessel system is designed to generate a control signal; then the control signal is synchronously applied to the actual unmanned surface vessel system and the artificial unmanned surface vessel system to achieve dynamic synchronization of their states, and finally complete the parallel trajectory tracking control of the actual unmanned surface vessel system and the artificial unmanned surface vessel system.

[0037] Steps S1 / S2 / S3 / S4 / S5 are executed sequentially; The "high-precision operation" mentioned in this application refers to the strict control of position error to ensure the quality and safety of the operation when unmanned surface vessels perform some maritime operations that have strict requirements for trajectory tracking accuracy. The technical solution of this application is not only for high-precision operations, but also compatible with multiple scenarios through configurable preset performance boundaries. It can set strict constraints to achieve accurate tracking, or relax the constraints to obtain more stable control. Its core advantage is that it can meet the stringent requirements of high-precision operations and has good versatility. This application achieves high-precision tracking under constraints by introducing a preset performance function to impose transient and steady-state constraints on the tracking error and designing an error transformation and trajectory tracking controller.

[0038] The actual unmanned surface vessel system model considering environmental interference is as follows:

[0039] in, , This indicates the actual location information of the unmanned surface vessel. This indicates the actual bow roll angle of the unmanned surface vessel; This indicates the actual speed information of the unmanned surface vessel. These represent the longitudinal velocity, lateral velocity, and bow roll rate of the actual unmanned surface vessel, respectively. This represents the actual control input of the unmanned surface vessel; = Represents the inertial mass matrix; Represents the centripetal force and Coriolis coefficient matrix; Represents the nonlinear damping matrix; Indicates unknown hydrodynamic damping; This indicates an unknown external disturbance caused by wind, waves, and currents; This represents the rotation matrix.

[0040] Furthermore, the construction steps of the artificial unmanned surface vessel system model are as follows: The actual unmanned surface vessel system model is rewritten as follows:

[0041] in, This indicates the actual location and bow roll angle of the unmanned surface vessel. Represents the rotation matrix; This indicates the actual speed information of the unmanned surface vessel; Represents the inertial mass matrix The nominal value; This represents the actual control input of the unmanned surface vessel; Indicates the unknown dynamics of the actual unmanned surface vessel. The equivalent computable quantity, These represent the unknown dynamic components of the actual unmanned surface vessel (USV) in the longitudinal, lateral, and bow-roll dimensions, respectively. The definition is as follows:

[0042] The unknown dynamics of a real unmanned surface vessel (USV) are modeled using a fuzzy logic system. The equivalent mathematical model of the dynamics of the real USV is shown below:

[0043] in, Represents the nominal value of the inertial mass matrix; This represents the matrix inverse operation; This represents the actual control input of the unmanned surface vessel; , Both represent the basis functions of the fuzzy logic system; Indicates modeling bias; By fuzzy weights composition, These represent the fuzzy weight vectors corresponding to the longitudinal, lateral, and pitch directions, respectively. It is expressed as follows:

[0044] The filter is defined as follows:

[0045] and in, It is the filter output; These are the filter parameters; Both represent the basis functions of the fuzzy logic system; This represents the equivalent computable quantity of unknown dynamics of an actual unmanned surface vessel. The amount; Represented by the natural logarithm Exponentiation to base 1; Indicates time; They represent The initial value; express The derivative; similarly, They represent The initial value; Based on the filter, the artificial unmanned surface vessel system is constructed as follows, combined with the extended state observer:

[0046]

[0047] in, express The estimated value; Represents the rotation matrix; Indicates the actual speed information of the unmanned surface vessel. The estimated value; Indicates the estimation error; express The derivative; Represents the nominal value of the inertial mass matrix; This represents the matrix inverse operation; This represents the actual control input of the unmanned surface vessel; Indicating modeling bias The estimated value; , Both represent the basis functions of the fuzzy logic system; express The estimated value; All are design parameters; They represent The estimated value; Indicates the length of the data stack; Indicates adaptive gain; Indicates projection operation; These represent the data stack after filtering. Stored in exist The value at any given moment.

[0048] Furthermore: Regarding the trajectory tracking error of the constructed unmanned surface vessel system model, the process of selecting a suitable preset performance function to construct a preset performance boundary, and designing an error transformation function based on the preset performance function to obtain the variable after error transformation is as follows: The trajectory tracking error of an unmanned surface vessel (USV) system is defined as follows:

[0049] in, Indicates the reference trajectory; This indicates the actual location and bow angle information of the unmanned surface vessel. The estimated value; Define preset performance boundaries to constrain trajectory tracking errors as follows:

[0050] in, Indicates the preset performance function Indicates and The relevant global Lipschitz continuity function, and They represent Initial and final values, The components; the preset performance boundary refers to the upper and lower bounds of the inequality signs on both sides of the tracking error, i.e., the components in the embodiment. Figure 4 The upper and lower black dashed lines in the middle; Preferably, to solve the initial value constraint problem in the preset performance control, an error transformation and the resulting variable after the error transformation are constructed. As shown below:

[0051] in, The amount; Indicates the preset performance function; Represents the tangent function. .

[0052] Furthermore, the design steps for the kinematic guidance law of the aforementioned unmanned surface vessel system are as follows: Define auxiliary positive definite matrices respectively and diagonal matrix As shown below:

[0053] and

[0054] in, The variable represents the result of the error transformation; Indicates the preset performance function; ; Represents the cosine function; The kinematic guidance law for the artificial unmanned surface vessel system is designed as follows:

[0055] in, Represents the rotation matrix; ; This represents the matrix inverse operation; ; Represents a diagonal matrix; Represents the control parameter matrix; ; For design parameters; Indicates the estimation error; Indicates the reference trajectory; ; express The derivative; .

[0056] Furthermore, the parallel preset performance trajectory tracking controller of the artificial unmanned surface vessel system is designed as follows:

[0057] in, Represents the nominal value of the inertial mass matrix; This represents the control parameter matrix of the parallel preset performance trajectory tracking controller; Indicates the dynamic velocity tracking error. Indicates the actual speed information of the unmanned surface vessel. The estimated value, This describes the kinematic guidance law of the designed unmanned surface vessel system; ; ; Represents the rotation matrix; Represents the variable after error transformation ; , Both represent the basis functions of the fuzzy logic system. Represents a column vector composed of the basis functions of a fuzzy logic system; express The derivative; express The estimated value; Indicating modeling bias The estimated value.

[0058] Figure 2 This is a schematic diagram of the unmanned surface vessel parallel preset performance trajectory tracking control system in an embodiment of the present invention; A parallel preset performance trajectory tracking control system for unmanned surface vessels (USVs) designed for high-precision operations includes: Practical Unmanned Surface Vessel System Construction Module: Used to construct practical unmanned surface vessel systems that take environmental interference into account; Artificial Unmanned Surface Vessel (USV) System Construction Module: This module utilizes a fuzzy logic system to model the unknown dynamics of the actual USV system, completing the equivalent model of the actual USV's dynamics. Then, filters are designed to process the basis functions of the fuzzy logic system and the equivalent computable quantities of the unknown dynamics of the actual USV, storing the filtered data in a data stack. Finally, an artificial unmanned surface vessel (USV) system model is constructed by combining an extended state observer with the equivalent dynamics model of the actual USV. Preset performance control module: Based on the constructed artificial unmanned surface vessel system model, the trajectory tracking error between the artificial unmanned surface vessel system model and the reference trajectory of the actual unmanned surface vessel is defined; a preset performance function is selected and designed to construct a corresponding preset performance boundary for the trajectory tracking error; an error transformation function is designed according to the preset performance function to transform the constrained trajectory tracking error into an unconstrained error transformation variable, thus solving the initial value constraint problem of preset performance control; Kinematic guidance law module: Based on the variables after error transformation, combined with the position, bow angle, and velocity information of the actual unmanned surface vessel system in the Earth coordinate system considering environmental interference, as well as the estimated position, bow angle, and velocity values ​​of the actual unmanned surface vessel output by the extended state observer, and simultaneously integrating the dynamic characteristics of the reference trajectory signal and the preset performance function, the kinematic guidance law of the artificial unmanned surface vessel system is designed. Parallel trajectory tracking controller module: Based on the kinematic guidance law of the artificial unmanned surface vessel (USV) system, the estimated value of the unknown dynamics of the actual USV system, and the estimated value of the modeling approximation estimation error obtained by combining the extended state observer, a parallel preset performance trajectory tracking controller for the USV system is designed to generate a control signal; then, the control signal is synchronously applied to the actual USV system and the artificial USV system to achieve dynamic synchronization of their states, and finally complete the parallel trajectory tracking control of the actual USV system and the artificial USV system.

[0059] This invention provides a parallel preset performance trajectory tracking controller for unmanned surface vessels (USVs) for high-precision operations. It includes an actual USV system, an artificial USV system construction module including a filter, a data stack, a fuzzy logic system, and an extended state observer, and a preset performance control module including performance constraints, error transformation, kinematic guidance law, and a parallel preset performance trajectory tracking controller. The input end of the actual unmanned surface vessel system construction module is connected to the trajectory tracking controller module, and the output end of the actual unmanned surface vessel system construction module is connected to the artificial unmanned surface vessel system construction module. The input end of the artificial unmanned surface vessel system construction module is connected to the output end of the actual unmanned surface vessel system, and the output end of the artificial unmanned surface vessel system construction module is connected to the input end of the preset performance control module after calculation with the reference trajectory. The input end of the preset performance control module is connected to the output end of the artificial unmanned surface vessel system construction module, and the output end of the preset performance control module is connected to the input end of the kinematic guidance law. The input of the kinematic guidance law is connected to the output of the preset performance control module, and the output of the kinematic guidance law module is connected to the input of the trajectory tracking controller.

[0060] Example 1 in At any time, the actual position and bow angle information of the unmanned surface vessel system will be recorded. Speed ​​information and control input The data is transmitted to the unmanned surface vessel (USV) system, which then calculates an estimate of its position and bow angle for the next moment. Compare the estimated value with the reference trajectory The comparison results in an error that is then transformed using a preset performance control method and fed into the trajectory tracking controller. The trajectory tracking controller generates the control input for the next moment and simultaneously sends it to both the actual unmanned surface vessel (USV) system and the artificial USV system. The actual USV system updates its state based on this input and synchronizes its state with the artificial USV system, ultimately achieving closed-loop control.

[0061] A specific embodiment of the present invention is as follows: wherein the parameters are selected as follows: Design parameters: ; Filter parameters Adaptive gain ; Control parameter matrix ; Preset performance function satisfies

[0062] The actual initial position and bow angle of the unmanned surface vessel

[0063] Initial position and bow angle of the unmanned surface vessel

[0064] Preset performance function initial value ; Furthermore, the simulation results of this embodiment are as follows: Figures 3 to 5 As shown: Figure 3 The motion trajectory of the actual unmanned surface vessel (USV) system is displayed. It can be seen that the proposed method can achieve control of the actual USV system through physical information interaction using a model of the artificial USV system, thereby completing the task of tracking parallel preset performance trajectories.

[0065] Figure 4 This is a schematic diagram illustrating the tracking error and preset performance constraints in an embodiment of the present invention; wherein (a) Directional trajectory tracking error versus preset performance boundary curve, (b) Direction trajectory tracking error versus preset performance boundary curve, (c) bow roll angle Direction trajectory tracking error versus preset performance constraint curve; Figure 4 The trajectory tracking errors of the artificial unmanned surface vessel (USV) system and the actual USV system are given. It can be seen that the tracking error can approach zero at a relatively fast speed, showing good tracking performance.

[0066] Figure 5 This is a schematic diagram illustrating the position and heading estimation performance of the unmanned surface vessel in an embodiment of the present invention, wherein (a) (b) Comparison curve of estimated position of actual unmanned surface vessel in direction, actual position and expected position. (c) Comparison curve of estimated position, actual position and expected position of unmanned surface vessel (USV), and actual bow roll angle of USV. A curve comparing estimated, actual, and expected values; Figure 5 The results demonstrate the effectiveness of the extended state observer in estimating the position, heading, velocity, and modeling bias of an actual unmanned surface vessel (USV). The results show that the extended state observer, as an artificial unmanned surface vessel system, can accurately characterize the vessel's motion state in the information space, ensuring that the USV's output trajectory remains synchronized in both physical and information spaces.

[0067] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A parallel preset performance trajectory tracking control method for high-precision operation-oriented unmanned surface vehicle, characterized in that: Includes the following steps: S1: Construct a practical unmanned surface vessel system that takes into account environmental interference; S2: Use a fuzzy logic system to model the unknown dynamics of the actual unmanned surface vessel (USV) system, and complete the equivalent model of the dynamics of the actual USV. Then design filters to filter the basis functions of the fuzzy logic system and the equivalent computable quantities of the unknown dynamics of the actual USV, and store the filtered data in the data stack. Combine the extended state observer with the equivalent dynamics model of the actual USV to construct the artificial unmanned surface vessel system model. S3: Based on the constructed artificial unmanned surface vessel (USV) system model, define the trajectory tracking error between the USV system model and the reference trajectory of the actual USV. A preset performance function is selected to construct a corresponding preset performance boundary for the trajectory tracking error. An error transformation function is designed based on the preset performance function to transform the constrained trajectory tracking error into an unconstrained error transformation variable, thus solving the initial value constraint problem of preset performance control. S4: Based on the variables after error transformation, combined with the position, bow angle, and velocity information of the actual unmanned surface vessel system in the Earth coordinate system considering environmental interference, as well as the estimated position, bow angle, and velocity values ​​of the actual unmanned surface vessel output by the extended state observer, and simultaneously integrating the dynamic characteristics of the reference trajectory signal and the preset performance function, the kinematic guidance law of the artificial unmanned surface vessel system is designed. S5: Based on the kinematic guidance law of the artificial unmanned surface vessel system, the estimated value of the unknown dynamics of the actual unmanned surface vessel system, and the estimated value of the modeling approximation estimation error obtained by combining the extended state observer, design a parallel preset performance trajectory tracking controller for the artificial unmanned surface vessel system and generate control signals. Then, the control signal is applied synchronously to the actual unmanned surface vessel system and the artificial unmanned surface vessel system to achieve dynamic synchronization of their states, and finally complete the parallel control of trajectory tracking between the actual unmanned surface vessel system and the artificial unmanned surface vessel system.

2. The parallel preset performance trajectory tracking control method for unmanned surface vessels (USVs) for high-precision operations according to claim 1, wherein the actual USV system model considering environmental interference is as follows: in, , This indicates the actual location information of the unmanned surface vessel. This indicates the actual bow roll angle of the unmanned surface vessel; This indicates the actual speed information of the unmanned surface vessel. These represent the longitudinal velocity, lateral velocity, and bow roll rate of the actual unmanned surface vessel, respectively. This represents the actual control input of the unmanned surface vessel; = Represents the inertial mass matrix; Represents the centripetal force and Coriolis coefficient matrix; Represents the nonlinear damping matrix; Indicates unknown hydrodynamic damping; This indicates an unknown external disturbance caused by wind, waves, and currents; This represents the rotation matrix.

3. The parallel preset performance trajectory tracking and control method for unmanned surface vessels (USVs) for high-precision operations according to claim 1, characterized in that: The construction steps of the artificial unmanned surface vessel system model are as follows: The actual unmanned surface vessel system model is rewritten as follows: in, , This indicates the actual location information of the unmanned surface vessel. This indicates the actual bow roll angle of the unmanned surface vessel; Represents the rotation matrix; This indicates the actual speed information of the unmanned surface vessel. These represent the longitudinal velocity, lateral velocity, and bow roll rate of the actual unmanned surface vessel, respectively. Represents the inertial mass matrix The nominal value; This represents the actual control input of the unmanned surface vessel; Indicates the unknown dynamics of the actual unmanned surface vessel. The equivalent computable quantity, These represent the unknown dynamic components of the actual unmanned surface vessel (USV) in the longitudinal, lateral, and bow-roll dimensions, respectively. The definition is as follows: The unknown dynamics of a real unmanned surface vessel (USV) are modeled using a fuzzy logic system. The equivalent mathematical model of the dynamics of the real USV is shown below: in, Represents the nominal value of the inertial mass matrix; This represents the matrix inverse operation; This represents the actual control input of the unmanned surface vessel; , Both represent the basis functions of the fuzzy logic system; Indicates modeling bias; By fuzzy weights composition, These represent the fuzzy weight vectors corresponding to the longitudinal, lateral, and pitch directions, respectively. It is expressed as follows: The filter is defined as follows: and in, It is the filter output; These are the filter parameters; Both represent the basis functions of the fuzzy logic system; This represents the equivalent computable quantity of unknown dynamics of an actual unmanned surface vessel. The amount; Represented by the natural logarithm Exponentiation to base 1; Indicates time; They represent The initial value; express The derivative; similarly, They represent The initial value; Based on the filter, the artificial unmanned surface vessel system is constructed as follows, combined with the extended state observer: in, express The estimated value; Represents the rotation matrix; Indicates the actual speed information of the unmanned surface vessel. The estimated value; Indicates the estimation error; express The derivative; Represents the nominal value of the inertial mass matrix; This represents the matrix inverse operation; This represents the actual control input of the unmanned surface vessel; Indicating modeling bias The estimated value; , Both represent the basis functions of the fuzzy logic system; express The estimated value; All are design parameters; They represent The estimated value; Indicates the length of the data stack; Indicates adaptive gain; Indicates projection operation; These represent the data stack after filtering. Stored in exist The value at any given moment.

4. The parallel preset performance trajectory tracking and control method for unmanned surface vessels (USVs) for high-precision operations according to claim 1, characterized in that: The constructed unmanned surface vessel system model defines the trajectory tracking error between the unmanned surface vessel system model and the reference trajectory. The process of selecting a preset performance function, constructing a corresponding preset performance boundary for the trajectory tracking error, and designing an error transformation function based on the preset performance function to transform the constrained trajectory tracking error into an unconstrained error transformation variable, thus solving the initial value constraint problem of preset performance control, is as follows: The trajectory tracking error of an unmanned surface vessel (USV) system is defined as follows: in, Indicates the reference trajectory; This indicates the actual location and bow angle information of the unmanned surface vessel. The estimated value; Define preset performance boundaries to constrain trajectory tracking errors as follows: in, Indicates the preset performance function Indicates and The relevant global Lipschitz continuity function, and They represent Initial and final values, The amount; Construct the error transformation function and obtain the variable after error transformation. As shown below: in, The amount; Indicates the preset performance function; Represents the tangent function. .

5. The parallel preset performance trajectory tracking and control method for unmanned surface vessels (USVs) for high-precision operations according to claim 1, characterized in that: The process of designing the kinematic guidance law for the artificial unmanned surface vessel (USV) system, based on the error-transformed variables, combined with the actual position, bow angle, and velocity information of the USV system in the Earth coordinate system considering environmental interference, as well as the estimated position, bow angle, and velocity values ​​of the USV output by the extended state observer, and simultaneously integrating the dynamic characteristics of the reference trajectory signal and the preset performance function, is as follows: Define auxiliary positive definite matrices respectively and diagonal matrix As shown below: and in, The variable represents the result of the error transformation; Indicates the preset performance function; ; Represents the cosine function; Design the kinematic guidance law for an unmanned surface vessel system. as follows: in, Represents the rotation matrix; ; This represents the matrix inverse operation; ; Represents a diagonal matrix; Represents the control parameter matrix; ; For design parameters; Indicates the estimation error; Indicates the reference trajectory; ; express The derivative; .

6. The parallel preset performance trajectory tracking and control method for unmanned surface vessels (USVs) for high-precision operations according to claim 1, characterized in that: The process of the parallel preset performance trajectory tracking controller of the artificial unmanned surface vessel system is as follows: in, Represents the nominal value of the inertial mass matrix; This represents the control parameter matrix of the parallel preset performance trajectory tracking controller; Indicates the dynamic velocity tracking error. Indicates the actual speed information of the unmanned surface vessel. The estimated value, This describes the kinematic guidance law of the designed unmanned surface vessel system; ; ; Represents the rotation matrix; Represents the variable after error transformation ; , Both represent the basis functions of the fuzzy logic system. Represents a column vector composed of the basis functions of a fuzzy logic system; express The derivative; express The estimated value; Indicating modeling bias The estimated value.

7. A parallel preset performance trajectory tracking and control device for unmanned surface vessels (USVs) designed for high-precision operations, characterized in that: include: Practical Unmanned Surface Vessel System Construction Module: Used to construct practical unmanned surface vessel systems that take environmental interference into account; Artificial Unmanned Surface Vessel (USV) System Construction Module: This module is used to model the unknown dynamics of the actual USV system using a fuzzy logic system, thus completing the equivalent model of the actual USV dynamics. Then, filters are designed to filter the basis functions of the fuzzy logic system and the equivalent computable quantities of the unknown dynamics of the actual USV, and the filtered data is stored in a data stack. Finally, the extended state observer and the equivalent dynamics model of the actual USV are combined to construct the artificial USV system model. Preset performance control module: Based on the constructed artificial unmanned surface vessel system model, it defines the trajectory tracking error between the model and the reference trajectory of the actual unmanned surface vessel; A preset performance function is selected to construct a corresponding preset performance boundary for the trajectory tracking error. An error transformation function is designed based on the preset performance function to transform the constrained trajectory tracking error into an unconstrained error transformation variable, thus solving the initial value constraint problem of preset performance control. Kinematic guidance law module: Based on the variables after error transformation, combined with the position, bow angle, and velocity information of the actual unmanned surface vessel system in the Earth coordinate system considering environmental interference, as well as the estimated position, bow angle, and velocity values ​​of the actual unmanned surface vessel output by the extended state observer, and simultaneously integrating the dynamic characteristics of the reference trajectory signal and the preset performance function, the kinematic guidance law of the artificial unmanned surface vessel system is designed. Parallel trajectory tracking controller module: Based on the kinematic guidance law of the artificial unmanned surface vessel system, the estimated value of the unknown dynamics of the actual unmanned surface vessel system, and the estimated value of the modeling approximation estimation error obtained by combining the extended state observer, a parallel preset performance trajectory tracking controller for the artificial unmanned surface vessel system is designed to generate control signals; Then, the control signal is applied synchronously to the actual unmanned surface vessel system and the artificial unmanned surface vessel system to achieve dynamic synchronization of their states, and finally complete the parallel control of trajectory tracking between the actual unmanned surface vessel system and the artificial unmanned surface vessel system.

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