Self-adaptive control method for unmanned ship in high-fluctuation environment

Abstract

The invention relates to the technical field of unmanned ship self-adaptive control, and discloses an unmanned ship self-adaptive control method in a high-fluctuation environment, and the method comprises the steps: obtaining the navigation state of an unmanned ship; estimating the navigation estimation position of the unmanned ship and the speed reference instruction vector of the unmanned ship by using the navigation position target estimation model; calculating an unmanned ship driving dynamic error according to the unmanned ship speed reference instruction vector; calculating and obtaining an unmanned ship navigation virtual control signal based on the unmanned ship navigation dynamic error, and performing inverse transformation on the unmanned ship navigation virtual control signal to obtain an unmanned ship navigation control instruction. According to the method, the navigation state and the navigation position of the unmanned ship at different moments are estimated by using the navigation position target estimation model, and the driving dynamic error is calculated based on the reference speeds of different positions; and generating a corresponding unmanned ship navigation virtual control signal for the position with the relatively large driving dynamic error so as to carry out unmanned ship self-adaptive control.

Description

Technical Field

[0001] The present invention relates to the technical field of unmanned ship adaptive control, and in particular to an unmanned ship adaptive control method in a high-fluctuation environment. Background Art

[0002] Unmanned ships are an important tool to ensure the safety and efficiency of offshore operations. Unmanned ships use various sensors to obtain information about the surrounding environment, and can autonomously navigate and avoid obstacles to complete specific offshore operations. Unmanned ships are widely used in various fields due to their distinctive characteristics, such as nautical charting, military defense, marine research, etc. In the process of completing various offshore operations, unmanned ships are susceptible to various unknown interferences, such as wind, waves, and currents, which makes it impossible to complete the specified tasks as planned. In response to this problem, the present invention proposes an adaptive control method for unmanned ships in a high-volatility environment to achieve robust navigation control of unmanned ships in a high-volatility environment. Summary of the invention

[0003] In view of this, the present invention provides an adaptive control method for an unmanned ship in a high-fluctuation environment, the purpose of which is to: 1) obtain the attitude information of the unmanned ship, establish the coordinate conversion relationship between the propeller coordinate system and the inertial coordinate system, convert the coordinates of the propeller blade apex to the inertial coordinate system, and realize the parameter characterization of the propeller. Since the unmanned ship is easily affected by various fluctuations during driving, which leads to the uncertainty of the attitude parameters of the unmanned ship, by establishing a loop conversion relationship between the attitude information and the attitude angular velocity, the anti-interference degree and stability of the attitude parameters are improved, and the stability of the adaptive control of the unmanned ship is enhanced; 2) using the navigation position target estimation model The model estimates the navigation status and navigation position of the unmanned ship at different times, and generates a reference speed for the estimated navigation position at any time in combination with the line of sight angle between the unmanned ship and the target area and the ship speed information. The driving dynamic error of the estimated ship speed and the estimated navigation position is calculated based on the estimated reference speed. The larger the driving dynamic error, the greater the difference between the estimated ship speed and the reference speed, and the greater the difference between the estimated navigation position and the propeller blade coordinates. Then, a virtual control signal for the navigation of the unmanned ship is generated, and the virtual control signal for the navigation of the unmanned ship is inversely transformed to obtain the navigation control instruction of the unmanned ship, so as to realize the adaptive control of the unmanned ship.

[0004] To achieve the above object, the present invention provides an adaptive control method for an unmanned ship in a high-volatility environment, comprising the following steps: S1: constructing a navigation position target estimation model and obtaining the navigation state of the unmanned ship, wherein the navigation position target estimation model takes the navigation state of the unmanned ship as input and takes the navigation estimated position as output; S2: using the navigation position target estimation model to estimate the navigation estimated position of the unmanned ship, and determining the unmanned ship speed reference command vector according to the estimated navigation estimated position; S3: Calculate the unmanned ship driving dynamic error according to the unmanned ship speed reference command vector; S4: A virtual control signal for navigation of the unmanned ship is obtained based on the dynamic error calculation of the unmanned ship, and an inverse transformation is performed on the virtual control signal for navigation of the unmanned ship to obtain a navigation control instruction for the unmanned ship.

[0005] As a further improvement method of the present invention: Optionally, constructing a navigation position target estimation model in step S1 includes: Constructing a navigation position target estimation model, the constructed navigation position target estimation model takes the navigation state of the unmanned ship as input and the navigation estimated position as output, wherein the navigation state of the unmanned ship includes the propeller blade coordinate information, attitude information, bow direction information and ship speed information of the unmanned ship, the attitude information includes the roll angle, pitch angle, yaw angle and attitude angular velocity of the unmanned ship, and the ship speed information represents the decomposition of the ship speed according to the bow direction, and the obtained horizontal ship speed and vertical ship speed compared with the inertial coordinate system, as well as the accelerations corresponding to the two directions; in the embodiment of the present invention, the horizontal direction is the preset water flow direction, and the vertical direction is the direction on the sea surface perpendicular to the water flow direction; The navigation position target estimation model estimates the navigation state of the unmanned ship according to the radius and area direction of the unmanned ship's navigation target area, obtains the navigation state of the unmanned ship at the next moment, and estimates the navigation position of the unmanned ship at the next moment based on the estimated navigation state.

[0006] Optionally, obtaining the navigation status of the unmanned ship in step S1 includes: Get the current navigation status of the unmanned ship. The process of obtaining the current navigation status of the unmanned ship is as follows: S11: Use attitude sensors to obtain the current attitude information of the unmanned ship ,in represents the rolling angle of the unmanned ship, represents the pitch angle of the unmanned ship, Indicates the yaw angle of the unmanned ship; S12: Determine the propeller coordinate system centered on the propeller of the unmanned ship according to the right-hand rule, and obtain the three-dimensional position coordinates of the propeller blade vertex in the propeller coordinate system Based on the attitude information of the unmanned ship, the following three-dimensional position coordinate transformation relationship of the propeller blade vertex in the propeller coordinate system and the inertial coordinate system is calculated: : ; Based on the three-dimensional position coordinate transformation relationship Convert the three-dimensional position coordinates in the propeller coordinate system to the inertial coordinate system: ; in: Represents the three-dimensional position coordinates in the propeller coordinate system Three-dimensional coordinate results in the inertial coordinate system; Representation based on posture information The three-dimensional position coordinate transformation relationship; S13: Calculate the attitude angular velocity of the unmanned ship based on the attitude information: ; in: Representation based on posture information The attitude angular velocity vector; S14: Obtaining bow direction information and ship speed information, wherein the bow direction information is the angle between the line of sight between the bow of the unmanned ship and the center of the target area and the horizontal direction. , the ship speed information is: ; ; in: are the speed of the unmanned ship in the horizontal and vertical directions at the current moment respectively; They are respectively the horizontal and vertical accelerations of the unmanned ship at the current moment.

[0007] Optionally, in step S2, estimating the estimated navigation position of the unmanned ship using the navigation position target estimation model includes: The estimated navigation position of the unmanned ship is estimated by using the navigation position target estimation model, where the navigation position estimation process of the unmanned ship at the next moment is: S21: Initialize and generate the speed of the unmanned ship passing The observation matrix after time t ; S22: It is estimated that the unmanned ship is passing Ship speed after time t: ; ; ; in: Indicates the estimated number of unmanned ships passing by The ship speed after time t, Indicates the ship's speed in the horizontal direction, Indicates the ship's speed in the vertical direction; S23: Construct the estimated error covariance matrix : ; ; in: represents the standard deviation of the horizontal acceleration of the unmanned ship, Represents the standard deviation of the vertical acceleration of the unmanned ship; It is estimated that the unmanned ship is passing The distance traveled after time t, Indicates the distance the unmanned ship travels in the horizontal direction. Indicates the distance the unmanned ship travels in the vertical direction; S24: It is estimated that the unmanned ship is passing Posture information after t time: ; in: Indicates that an unmanned ship is passing by Posture information after t time ; Indicates the preset Posture transformation matrix parameters after time t; S25: Estimate the speed of the unmanned ship After k Results after t time : ; in: k is a positive integer greater than 1, ; And update the parameters: ; ; ; ; in: represents the adaptive factor; b represents the forgetting factor, and b is set to 0.9; Indicates that after k The estimated error covariance matrix after time t; Indicates that after k Posture information after t time; Representation based on posture information The calculated attitude angular velocity; It is estimated that the unmanned ship is passing The distance traveled after time t; And set the two-dimensional coordinate position of the unmanned ship at the current moment to , according to the estimated travel distance of the unmanned ship at different times, the estimated navigation position of the unmanned ship at different times is obtained: ; in: Indicates that after k The estimated navigation position of the unmanned ship after time t is obtained, and the navigation status of the unmanned ship after different times is obtained according to step S1.

[0008] Optionally, determining the unmanned ship speed reference instruction vector according to the estimated navigation position in step S2 includes: The unmanned ship speed reference command vector is determined according to the estimated navigation position, where the unmanned ship navigation estimated position The corresponding unmanned ship speed reference instruction vector is : ; ; ; in: represents a symbolic function; L represents the area radius of the target navigation area of ​​the unmanned ship; represents the L1 norm; Indicates that after k The angle between the line of sight between the bow of the unmanned ship and the center of the target area and the horizontal direction after time t.

[0009] Optionally, the unmanned ship driving dynamic error is calculated according to the unmanned ship speed reference instruction vector in step S3, including: The unmanned ship's driving dynamic error is calculated based on the unmanned ship's speed reference command vector, where the unmanned ship is estimated to be in the navigation position. The dynamic error of the unmanned ship at is: ; in: Indicates that after k The two-dimensional coordinate position of the propeller blade apex in the inertial coordinate system after time t; represents an exponential function with a natural constant as base; Indicates the estimated position of the unmanned ship during navigation The dynamic error of unmanned ship driving at

[0010] Optionally, in step S4, obtaining the unmanned ship navigation virtual control signal based on the unmanned ship driving dynamic error calculation includes: Based on the calculation results of the unmanned ship's driving dynamic error, if the unmanned ship is in the estimated position If the unmanned ship driving dynamic error at k is greater than the preset error threshold, a Virtual control signal of unmanned ship navigation after time t: ; in: Represents the unmanned ship speed reference instruction vector Reference speed of the unmanned ship in the horizontal direction, Represents the unmanned ship speed reference instruction vector Reference speed of the unmanned ship in the vertical direction; m represents the mass of the unmanned ship; F represents the total power of the unmanned ship; Indicates the power value control command of the unmanned ship in the horizontal direction , Indicates the power value control command of the unmanned ship in the vertical direction ; Based on the error threshold The observation matrix To update: .

[0011] Optionally, in step S4, inverse transformation of the unmanned ship navigation virtual control signal to obtain the unmanned ship navigation control instruction includes: The speed control signal in the unmanned ship navigation virtual control signal is inversely transformed to obtain the unmanned ship navigation control instruction, wherein the unmanned ship navigation control instruction is the power value control instruction of the unmanned ship in the horizontal direction And the power value control command in the vertical direction , the unmanned ship navigation control command is used to control and adjust the horizontal power value and the vertical power value of the unmanned ship so that the power values ​​reach as well as , and after k The moment after time t is the initial moment, and the process returns to step S1 to perform the self-adaptive control of the unmanned ship.

[0012] In order to solve the above problem, the present invention provides an electronic device, the electronic device comprising: A memory storing at least one instruction; Communication interface, enabling electronic equipment to communicate; and The processor executes the instructions stored in the memory to implement the above-mentioned unmanned ship adaptive control method in a high-fluctuation environment.

[0013] In order to solve the above problems, the present invention also provides a computer-readable storage medium, in which at least one instruction is stored. The at least one instruction is executed by a processor in an electronic device to implement the above-mentioned unmanned ship adaptive control method in a high-volatility environment.

[0014] Compared with the prior art, the present invention proposes an adaptive control method for unmanned ships in a high-volatility environment, which has the following advantages: First, this scheme proposes a method for obtaining the current navigation status of an unmanned ship, wherein the process of obtaining the current navigation status of an unmanned ship is as follows: using an attitude sensor to obtain the current attitude information of the unmanned ship ,in represents the rolling angle of the unmanned ship, represents the pitch angle of the unmanned ship, Represents the yaw angle of the unmanned ship; determine the propeller coordinate system centered on the propeller of the unmanned ship according to the right-hand rule, and obtain the three-dimensional position coordinates of the propeller blade vertex in the propeller coordinate system Based on the attitude information of the unmanned ship, the following three-dimensional position coordinate transformation relationship of the propeller blade vertex in the propeller coordinate system and the inertial coordinate system is calculated: : ; Based on the three-dimensional position coordinate transformation relationship Convert the three-dimensional position coordinates in the propeller coordinate system to the inertial coordinate system:

[0015] in: Represents the three-dimensional position coordinates in the propeller coordinate system Three-dimensional coordinate results in the inertial coordinate system; Representation based on posture information The three-dimensional position coordinate transformation relationship; the attitude angular velocity of the unmanned ship is calculated based on the attitude information: ; in: Representation based on posture information The attitude angular velocity vector is obtained; the bow direction information and the ship speed information are obtained, where the bow direction information is the angle between the line of sight and the horizontal direction between the bow of the unmanned ship and the center of the target area , the ship speed information is: ; ; in: are the speed of the unmanned ship in the horizontal and vertical directions at the current moment respectively; They are the horizontal and vertical accelerations of the unmanned ship at the current moment. This scheme acquires the attitude information of the unmanned ship, establishes the coordinate conversion relationship between the propeller coordinate system and the inertial coordinate system, and converts the coordinates of the propeller blade apex to the inertial coordinate system to achieve the parameter characterization of the propeller. Since the unmanned ship is easily affected by various fluctuations during driving, which leads to the uncertainty of the attitude parameters of the unmanned ship, the loop conversion relationship between the attitude information and the attitude angular velocity is established to improve the anti-interference degree and stability of the attitude parameters, and enhance the stability of the unmanned ship's adaptive control.

[0016] At the same time, this scheme proposes an unmanned ship adaptive navigation direction and navigation speed control method, which determines the unmanned ship speed reference command vector according to the estimated navigation position, where the unmanned ship navigation estimated position The corresponding unmanned ship speed reference instruction vector is : ; ; ; in: represents the symbolic function; L represents the area radius of the target navigation area of ​​the unmanned ship; represents the L1 norm; Indicates that after k The angle between the line of sight between the bow of the unmanned ship and the center of the target area and the horizontal direction after t time. The unmanned ship's driving dynamic error is calculated based on the unmanned ship's speed reference command vector, where the unmanned ship is estimated to be in the navigation position. The dynamic error of the unmanned ship at is: ; in: Indicates that after k The two-dimensional coordinate position of the propeller blade apex in the inertial coordinate system after time t; represents an exponential function with a natural constant as base; Indicates the estimated position of the unmanned ship during navigation Based on the calculation results of the unmanned ship driving dynamic error, if the unmanned ship is at the estimated navigation position If the unmanned ship driving dynamic error at k is greater than the preset error threshold, a Virtual control signal of unmanned ship navigation after time t: ; in: Represents the unmanned ship speed reference instruction vector Reference speed of the unmanned ship in the horizontal direction, Represents the unmanned ship speed reference instruction vector The reference speed of the unmanned ship in the vertical direction; m represents the mass of the unmanned ship; F represents the total power of the unmanned ship; Indicates the power value control command of the unmanned ship in the horizontal direction , Indicates the power value control command of the unmanned ship in the vertical direction ; and based on the error threshold The observation matrix To update: The speed control signal in the unmanned ship navigation virtual control signal is inversely transformed to obtain the unmanned ship navigation control instruction, wherein the unmanned ship navigation control instruction is the power value control instruction of the unmanned ship in the horizontal direction. And the power value control command in the vertical direction , the unmanned ship navigation control command is used to control and adjust the horizontal power value and the vertical power value of the unmanned ship so that the power values ​​reach as well as , and after k The moment after t time is the initial moment, and the unmanned ship is adaptively controlled. This scheme uses the navigation position target estimation model to estimate the navigation state and navigation position of the unmanned ship at different times, and combines the line of sight angle between the unmanned ship and the target area and the ship speed information to generate a reference speed for the estimated navigation position at any time. Based on the estimated reference speed, the driving dynamic error of the estimated ship speed and the estimated navigation position is calculated. The larger the driving dynamic error, the greater the difference between the estimated ship speed and the reference speed, and the greater the difference between the estimated navigation position and the propeller blade coordinates. Then, the unmanned ship navigation virtual control signal is generated, and the unmanned ship navigation virtual control signal is inversely transformed to obtain the unmanned ship navigation control instruction, so as to realize the adaptive control of the unmanned ship. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 A schematic flow chart of an adaptive control method for an unmanned ship in a high-volatility environment provided by one embodiment of the present invention; Figure 2 A schematic diagram of the structure of an electronic device for implementing an adaptive control method for an unmanned ship in a high-volatility environment provided by an embodiment of the present invention.

[0018] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0019] It should be understood that the specific embodiments described herein are only used to explain the present invention, and are not used to limit the present invention.

[0020] The embodiment of the present application provides an unmanned ship adaptive control method in a high-volatility environment. The execution subject of the unmanned ship adaptive control method in a high-volatility environment includes but is not limited to at least one of the electronic devices such as a server and a terminal that can be configured to execute the method provided by the embodiment of the present application. In other words, the unmanned ship adaptive control method in a high-volatility environment can be executed by software or hardware installed in a terminal device or a server device, and the software can be a blockchain platform. The server is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, etc.

[0021] Embodiment 1: S1: construct a navigation position target estimation model and obtain the navigation status of the unmanned ship, wherein the navigation position target estimation model takes the navigation status of the unmanned ship as input and takes the navigation estimated position as output.

[0022] The navigation position target estimation model is constructed in the step S1, including: Constructing a navigation position target estimation model, the constructed navigation position target estimation model takes the navigation state of the unmanned ship as input and the navigation estimated position as output, wherein the navigation state of the unmanned ship includes the propeller blade coordinate information, attitude information, bow direction information and ship speed information of the unmanned ship, the attitude information includes the roll angle, pitch angle, yaw angle and attitude angular velocity of the unmanned ship, and the ship speed information represents the decomposition of the ship speed according to the bow direction, and the obtained horizontal ship speed and vertical ship speed compared with the inertial coordinate system, as well as the accelerations corresponding to the two directions; in the embodiment of the present invention, the horizontal direction is the preset water flow direction, and the vertical direction is the direction on the sea surface perpendicular to the water flow direction; The navigation position target estimation model estimates the navigation state of the unmanned ship according to the radius and area direction of the unmanned ship's navigation target area, obtains the navigation state of the unmanned ship at the next moment, and estimates the navigation position of the unmanned ship at the next moment based on the estimated navigation state.

[0023] The step S1 of obtaining the navigation status of the unmanned ship includes: Get the current navigation status of the unmanned ship. The process of obtaining the current navigation status of the unmanned ship is as follows: S11: Use attitude sensors to obtain the current attitude information of the unmanned ship ,in represents the rolling angle of the unmanned ship, represents the pitch angle of the unmanned ship, Indicates the yaw angle of the unmanned ship; S12: Determine the propeller coordinate system centered on the propeller of the unmanned ship according to the right-hand rule, and obtain the three-dimensional position coordinates of the propeller blade vertex in the propeller coordinate system Based on the attitude information of the unmanned ship, the following three-dimensional position coordinate transformation relationship of the propeller blade vertex in the propeller coordinate system and the inertial coordinate system is calculated: : ; Based on the three-dimensional position coordinate transformation relationship Convert the three-dimensional position coordinates in the propeller coordinate system to the inertial coordinate system: ; in: Represents the three-dimensional position coordinates in the propeller coordinate system Three-dimensional coordinate results in the inertial coordinate system; Representation based on posture information The three-dimensional position coordinate transformation relationship; S13: Calculate the attitude angular velocity of the unmanned ship based on the attitude information: ; in: Representation based on posture information The attitude angular velocity vector; S14: Obtaining bow direction information and ship speed information, wherein the bow direction information is the angle between the line of sight between the bow of the unmanned ship and the center of the target area and the horizontal direction. , the ship speed information is: ; ; in: are the speed of the unmanned ship in the horizontal and vertical directions at the current moment respectively; They are respectively the horizontal and vertical accelerations of the unmanned ship at the current moment.

[0024] S2: The estimated navigation position of the unmanned ship is estimated by using the navigation position target estimation model, and the speed reference instruction vector of the unmanned ship is determined according to the estimated navigation position.

[0025] In the step S2, the estimated navigation position of the unmanned ship is estimated by using the navigation position target estimation model, including: The estimated navigation position of the unmanned ship is estimated by using the navigation position target estimation model, where the navigation position estimation process of the unmanned ship at the next moment is: S21: Initialize and generate the speed of the unmanned ship passing The observation matrix after time t ; S22: It is estimated that the unmanned ship is passing Ship speed after time t: ; ; ; in: Indicates the estimated number of unmanned ships passing by The ship speed after time t, Indicates the ship's speed in the horizontal direction, Indicates the ship's speed in the vertical direction; S23: Construct the estimated error covariance matrix : ; ; in: represents the standard deviation of the horizontal acceleration of the unmanned ship, Represents the standard deviation of the vertical acceleration of the unmanned ship; It is estimated that the unmanned ship is passing The distance traveled after time t, Indicates the distance the unmanned ship travels in the horizontal direction. Indicates the distance the unmanned ship travels in the vertical direction; S24: It is estimated that the unmanned ship is passing Posture information after t time: ; in: Indicates that an unmanned ship is passing by Posture information after t time ; Indicates the preset Posture transformation matrix parameters after time t; S25: Estimate the speed of the unmanned ship After k Results after t time : ; in: k is a positive integer greater than 1, ; And update the parameters: ; ; ; ; in: represents the adaptive factor; b represents the forgetting factor, and b is set to 0.9; Indicates that after k The estimated error covariance matrix after time t; Indicates that after k Posture information after t time; Representation based on posture information The calculated attitude angular velocity; It is estimated that the unmanned ship is passing The distance traveled after time t; And set the two-dimensional coordinate position of the unmanned ship at the current moment to , according to the estimated travel distance of the unmanned ship at different times, the estimated navigation position of the unmanned ship at different times is obtained: ; in: Indicates that after k The estimated navigation position of the unmanned ship after time t is obtained, and the navigation status of the unmanned ship after different times is obtained according to step S1.

[0026] Determining the unmanned ship speed reference instruction vector according to the estimated navigation estimated position in step S2 includes: The unmanned ship speed reference command vector is determined according to the estimated navigation position, where the unmanned ship navigation estimated position The corresponding unmanned ship speed reference instruction vector is : ; ; ; in: represents a symbolic function; L represents the area radius of the target navigation area of ​​the unmanned ship; represents the L1 norm; Indicates that after k The angle between the line of sight between the bow of the unmanned ship and the center of the target area and the horizontal direction after time t.

[0027] S3: Calculate the unmanned ship driving dynamic error according to the unmanned ship speed reference command vector.

[0028] In the step S3, the unmanned ship driving dynamic error is calculated according to the unmanned ship speed reference instruction vector, including: The unmanned ship's driving dynamic error is calculated based on the unmanned ship's speed reference command vector, where the unmanned ship is estimated to be in the navigation position. The dynamic error of the unmanned ship at is: ; in: Indicates that after k The two-dimensional coordinate position of the propeller blade apex in the inertial coordinate system after time t; represents an exponential function with a natural constant as base; Indicates the estimated position of the unmanned ship during navigation The dynamic error of unmanned ship driving at

[0029] S4: A virtual control signal for navigation of the unmanned ship is obtained based on the dynamic error calculation of the unmanned ship, and an inverse transformation is performed on the virtual control signal for navigation of the unmanned ship to obtain a navigation control instruction for the unmanned ship.

[0030] The step S4 calculates the unmanned ship navigation virtual control signal based on the unmanned ship driving dynamic error, including: Based on the calculation results of the unmanned ship's driving dynamic error, if the unmanned ship is in the estimated position If the unmanned ship driving dynamic error at k is greater than the preset error threshold, a Virtual control signal of unmanned ship navigation after time t: ; in: Represents the unmanned ship speed reference instruction vector Reference speed of the unmanned ship in the horizontal direction, Represents the unmanned ship speed reference instruction vector Reference speed of the unmanned ship in the vertical direction; m represents the mass of the unmanned ship; F represents the total power of the unmanned ship; Indicates the power value control command of the unmanned ship in the horizontal direction , Indicates the power value control command of the unmanned ship in the vertical direction ; Based on the error threshold The observation matrix To update: .

[0031] In step S4, the unmanned ship navigation virtual control signal is inversely transformed to obtain the unmanned ship navigation control instruction, including: The speed control signal in the unmanned ship navigation virtual control signal is inversely transformed to obtain the unmanned ship navigation control instruction, wherein the unmanned ship navigation control instruction is the power value control instruction of the unmanned ship in the horizontal direction And the power value control command in the vertical direction , the unmanned ship navigation control command is used to control and adjust the horizontal power value and the vertical power value of the unmanned ship so that the power values ​​reach as well as , and after k The moment after time t is the initial moment, and the process returns to step S1 to perform the self-adaptive control of the unmanned ship.

[0032] Embodiment 2: like Figure 2 , which is a schematic diagram of the structure of an electronic device for implementing an adaptive control method for an unmanned ship in a high-fluctuation environment provided by an embodiment of the present invention.

[0033] The electronic device 1 may include a processor 10 , a memory 11 , a communication interface 13 and a bus, and may also include a computer program stored in the memory 11 and executable on the processor 10 , such as a program 12 .

[0034] The memory 11 includes at least one type of readable storage medium, and the readable storage medium includes a flash memory, a mobile hard disk, a multimedia card, a card-type memory (e.g., SD or DX memory, etc.), a magnetic memory, a disk, an optical disk, etc. In some embodiments, the memory 11 may be an internal storage unit of the electronic device 1, such as a mobile hard disk of the electronic device 1. In other embodiments, the memory 11 may also be an external storage device of the electronic device 1, such as a plug-in mobile hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (SecureDigital, SD) card, a flash card (Flash Card), etc. equipped on the electronic device 1. Further, the memory 11 may also include both an internal storage unit of the electronic device 1 and an external storage device. The memory 11 may not only be used to store application software and various types of data installed in the electronic device 1, such as the code of the program 12, etc., but also be used to temporarily store data that has been output or is to be output.

[0035] The processor 10 may be composed of an integrated circuit in some embodiments, for example, a single packaged integrated circuit, or a plurality of packaged integrated circuits with the same or different functions, including one or more central processing units (CPUs), microprocessors, digital processing chips, graphics processors, and combinations of various control chips, etc. The processor 10 is the control core (Control Unit) of the electronic device, and uses various interfaces and lines to connect various components of the entire electronic device, and executes or executes programs or modules stored in the memory 11 (such as the program 12 for realizing adaptive control of unmanned ships in a high-fluctuation environment), and calls data stored in the memory 11, so as to execute various functions of the electronic device 1 and process data.

[0036] The communication interface 13 may include a wired interface and / or a wireless interface (such as a WI-FI interface, a Bluetooth interface, etc.), which is generally used to establish a communication connection between the electronic device 1 and other electronic devices, and to achieve connection and communication between internal components of the electronic device.

[0037] The bus may be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, etc. The bus may be divided into an address bus, a data bus, a control bus, etc. The bus is configured to realize connection and communication between the memory 11 and at least one processor 10, etc.

[0038] Figure 2 Only an electronic device with components is shown, and those skilled in the art will understand that Figure 2 The structure shown does not constitute a limitation on the electronic device 1, and may include fewer or more components than shown in the figure, or combine certain components, or arrange the components differently.

[0039] For example, although not shown, the electronic device 1 may also include a power source (such as a battery) for supplying power to various components. Preferably, the power source may be logically connected to the at least one processor 10 through a power management device, so that the power management device can realize functions such as charging management, discharging management, and power consumption management. The power source may also include one or more DC or AC power sources, recharging devices, power failure detection circuits, power converters or inverters, power status indicators, and other arbitrary components. The electronic device 1 may also include a variety of sensors, Bluetooth modules, Wi-Fi modules, etc., which will not be repeated here.

[0040] Optionally, the electronic device 1 may further include a user interface, which may be a display, an input unit (such as a keyboard), or a standard wired interface or a wireless interface. Optionally, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, and an OLED (Organic Light-Emitting Diode) touch device. The display may also be appropriately referred to as a display screen or a display unit, which is used to display information processed in the electronic device 1 and to display a visual user interface.

[0041] It should be understood that the embodiment is for illustration only and the scope of the patent application is not limited to this structure.

[0042] The program 12 stored in the memory 11 in the electronic device 1 is a combination of multiple instructions. When running in the processor 10, it can achieve: Construct a navigation position target estimation model and obtain the navigation status of the unmanned ship; The estimated navigation position of the unmanned ship is estimated by using a navigation position target estimation model, and a speed reference instruction vector of the unmanned ship is determined according to the estimated navigation position; Calculate the unmanned ship driving dynamic error according to the unmanned ship speed reference instruction vector; The unmanned ship navigation virtual control signal is obtained based on the unmanned ship driving dynamic error calculation, and the unmanned ship navigation virtual control signal is inversely transformed to obtain the unmanned ship navigation control instruction.

[0043] Specifically, the specific implementation method of the processor 10 for the above instructions can refer to Figure 1 to Figure 2 The description of the relevant steps in the corresponding embodiments will not be repeated here.

[0044] It should be noted that the serial numbers of the above embodiments of the present invention are only for description and do not represent the advantages and disadvantages of the embodiments. And the terms "including", "comprising" or any other variants thereof in this article are intended to cover non-exclusive inclusion, so that a process, device, article or method including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, device, article or method. In the absence of further restrictions, an element defined by the sentence "including a ..." does not exclude the presence of other identical elements in the process, device, article or method including the element.

[0045] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) as described above, and includes a number of instructions for a terminal device (which can be a mobile phone, a computer, a server, or a network device, etc.) to execute the methods described in each embodiment of the present invention.

[0046] The above are only preferred embodiments of the present invention, and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. An adaptive control method for an unmanned ship in a high-volatility environment, characterized in that: The method comprises: S1: constructing a navigation position target estimation model and obtaining the navigation state of the unmanned ship, wherein the navigation position target estimation model takes the navigation state of the unmanned ship as input and takes the navigation estimated position as output; S2: using the navigation position target estimation model to estimate the navigation estimated position of the unmanned ship, and determining the unmanned ship speed reference command vector according to the estimated navigation estimated position; S3: Calculate the unmanned ship driving dynamic error according to the unmanned ship speed reference command vector; S4: A virtual control signal for navigation of the unmanned ship is obtained based on the dynamic error calculation of the unmanned ship, and an inverse transformation is performed on the virtual control signal for navigation of the unmanned ship to obtain a navigation control instruction for the unmanned ship.

2. The method for adaptively controlling an unmanned ship in a high-volatility environment as claimed in claim 1, characterized in that: The navigation position target estimation model is constructed in the step S1, including: Construct a navigation position target estimation model, which takes the navigation state of the unmanned ship as input and the navigation estimated position as output, wherein the navigation state of the unmanned ship includes the propeller blade coordinate information, attitude information, bow direction information and ship speed information of the unmanned ship, the attitude information includes the roll angle, pitch angle, yaw angle and attitude angular velocity of the unmanned ship, and the ship speed information represents the decomposition of the ship speed according to the bow direction, and the obtained horizontal ship speed and vertical ship speed compared with the inertial coordinate system, as well as the accelerations in the two directions; The navigation position target estimation model estimates the navigation state of the unmanned ship according to the radius and area direction of the unmanned ship's navigation target area, obtains the navigation state of the unmanned ship at the next moment, and estimates the navigation position of the unmanned ship at the next moment based on the estimated navigation state.

3. The method for adaptively controlling an unmanned ship in a high-volatility environment as claimed in claim 1, characterized in that: The step S1 of obtaining the navigation status of the unmanned ship includes: Get the current navigation status of the unmanned ship. The process of obtaining the current navigation status of the unmanned ship is as follows: S11: Use attitude sensors to obtain the current attitude information of the unmanned ship ,in represents the rolling angle of the unmanned ship, represents the pitch angle of the unmanned ship, Indicates the yaw angle of the unmanned ship; S12: Determine the propeller coordinate system centered on the propeller of the unmanned ship according to the right-hand rule, and obtain the three-dimensional position coordinates of the propeller blade vertex in the propeller coordinate system Based on the attitude information of the unmanned ship, the following three-dimensional position coordinate transformation relationship of the propeller blade vertex in the propeller coordinate system and the inertial coordinate system is calculated: : ； Based on the three-dimensional position coordinate transformation relationship Convert the three-dimensional position coordinates in the propeller coordinate system to the inertial coordinate system: ； in: Represents the three-dimensional position coordinates in the propeller coordinate system Three-dimensional coordinate results in the inertial coordinate system; Representation based on posture information The three-dimensional position coordinate transformation relationship; S13: Calculate the attitude angular velocity of the unmanned ship based on the attitude information: ； in: Representation based on posture information The attitude angular velocity vectors correspond to the attitude angular velocities of the roll angle, pitch angle, and yaw angle respectively; S14: Obtaining bow direction information and ship speed information, wherein the bow direction information is the angle between the line of sight between the bow of the unmanned ship and the center of the target area and the horizontal direction. , the ship speed information is: ； ； in: are the speed of the unmanned ship in the horizontal and vertical directions at the current moment respectively; They are respectively the horizontal and vertical accelerations of the unmanned ship at the current moment.

4. The method for adaptively controlling an unmanned ship in a high-volatility environment as claimed in claim 3, characterized in that: In the step S2, the estimated navigation position of the unmanned ship is estimated by using the navigation position target estimation model, including: The estimated navigation position of the unmanned ship is estimated by using the navigation position target estimation model, where the navigation position estimation process of the unmanned ship at the next moment is: S21: Initialize and generate the speed of the unmanned ship passing The observation matrix after time t ; S22: It is estimated that the unmanned ship is passing Ship speed after time t: ； ； ； in: Indicates the estimated number of unmanned ships passing by The ship speed after time t, Indicates the ship's speed in the horizontal direction, Indicates the ship's speed in the vertical direction; S23: Construct the estimated error covariance matrix : ； ； in: represents the standard deviation of the horizontal acceleration of the unmanned ship, Represents the standard deviation of the vertical acceleration of the unmanned ship; It is estimated that the unmanned ship is passing The distance traveled after time t, Indicates the distance the unmanned ship travels in the horizontal direction. Indicates the distance the unmanned ship travels in the vertical direction; S24: It is estimated that the unmanned ship is passing Posture information after t time: ； in: Indicates that an unmanned ship is passing by Posture information after t time ; Indicates the preset Parameters of the attitude transformation matrix after time t; S25: Estimate the speed of the unmanned ship After k Results after t time : ； in: k is a positive integer greater than 1, , K t represents the maximum estimated time range of the preset unmanned ship speed; And update the parameters: ； ； ； ； in: represents the identity matrix; represents the adaptive factor; b represents the forgetting factor, and b is set to 0.9; Indicates that after k The estimated error covariance matrix after time t; Indicates that after k Posture information after t time; Representation based on posture information The calculated attitude angular velocity; It is estimated that the unmanned ship is passing The distance traveled after time t; And set the two-dimensional coordinate position of the unmanned ship at the current moment to , according to the estimated travel distance of the unmanned ship at different times, the estimated navigation position of the unmanned ship at different times is obtained: ； in: Indicates that after k The estimated navigation position of the unmanned ship after time t is obtained, and the navigation status of the unmanned ship after different times is obtained according to step S1.

5. The method for adaptively controlling an unmanned ship in a high-volatility environment as claimed in claim 4, characterized in that: Determining the unmanned ship speed reference instruction vector according to the estimated navigation estimated position in step S2 includes: The unmanned ship speed reference command vector is determined according to the estimated navigation position, where the unmanned ship navigation estimated position The corresponding unmanned ship speed reference instruction vector is : ； ； ； in: represents a symbolic function; L represents the area radius of the target navigation area of ​​the unmanned ship; represents the L1 norm; Indicates that after k The angle between the line of sight between the bow of the unmanned ship and the center of the target area and the horizontal direction after time t.

6. The method for adaptively controlling an unmanned ship in a high-volatility environment as claimed in claim 5, characterized in that: In the step S3, the unmanned ship driving dynamic error is calculated according to the unmanned ship speed reference instruction vector, including: The unmanned ship's driving dynamic error is calculated based on the unmanned ship's speed reference command vector, where the unmanned ship is estimated to be in the navigation position. The dynamic error of the unmanned ship at is: ； in: Indicates that after k The two-dimensional coordinate position of the propeller blade apex in the inertial coordinate system after time t; represents an exponential function with a natural constant as base; Indicates the estimated position of the unmanned ship during navigation The dynamic error of unmanned ship driving at 7. The method for adaptively controlling an unmanned ship in a high-volatility environment as claimed in claim 6, characterized in that: The step S4 calculates the unmanned ship navigation virtual control signal based on the unmanned ship driving dynamic error, including: Based on the calculation results of the unmanned ship's driving dynamic error, if the unmanned ship is in the estimated position If the unmanned ship driving dynamic error at k is greater than the preset error threshold, a Virtual control signal of unmanned ship navigation after time t: ； in: Represents the unmanned ship speed reference instruction vector Reference speed of the unmanned ship in the horizontal direction, Represents the unmanned ship speed reference instruction vector Reference speed of the unmanned ship in the vertical direction; m represents the mass of the unmanned ship; F represents the total power of the unmanned ship; Indicates the power value control command of the unmanned ship in the horizontal direction , Indicates the power value control command of the unmanned ship in the vertical direction ; Based on the error threshold The observation matrix To update: .

8. The method for adaptively controlling an unmanned ship in a high-volatility environment as claimed in claim 7, characterized in that: In step S4, the unmanned ship navigation virtual control signal is inversely transformed to obtain the unmanned ship navigation control instruction, including: The speed control signal in the unmanned ship navigation virtual control signal is inversely transformed to obtain the unmanned ship navigation control instruction, wherein the unmanned ship navigation control instruction is the power value control instruction of the unmanned ship in the horizontal direction And the power value control command in the vertical direction , the unmanned ship navigation control command is used to control and adjust the horizontal power value and the vertical power value of the unmanned ship so that the power values ​​reach as well as , and after k The moment after time t is the initial moment, and the process returns to step S1 to perform the self-adaptive control of the unmanned ship.

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