Estimator-Based Periodic Dynamic Event-Triggered Encirclement Control Method for Multiple Unmanned Surface Vehicles

Abstract

The present invention discloses an estimator-based periodic dynamic event-triggered pursuit control method for multi-unmanned surface vessels, belonging to the field of multi-unmanned surface vessel pursuit control. The method includes: establishing a multi-unmanned surface vessel system model, and using a target estimator to obtain estimated values of the target speed and position; designing a first controller according to the estimated values obtained by the target estimator and the pursuit mathematical model to calculate the desired speed required for the multi-unmanned surface vessels to achieve target pursuit; designing a second controller according to the desired speed calculated by the first controller, wherein the second controller is provided with a periodic dynamic event-triggering mechanism, and the control input is calculated by the second controller, and the control input signal is transmitted to the multi-unmanned surface vessel motion model at the event-triggering moment. The present invention proposes an estimator-based periodic dynamic event-triggered pursuit control method for multi-unmanned surface vessels under the condition of limited network resources, and controls the fluctuation of the tracking error within a small range, laying a key foundation for fields such as marine monitoring and safety.

Description

Technical Field

[0001] This application relates to the field of multi-unmanned ship encirclement control, and particularly to a periodic dynamic event-triggered encirclement control method for multi-unmanned ships based on an estimator. Background Art

[0002] In the fields of modern marine operations and safety monitoring, the application of unmanned ship technology is becoming increasingly widespread, and its autonomy and flexibility provide new solutions for offshore operations. However, due to the complexity and dynamics of the marine environment, how to effectively control multiple unmanned ships to cooperate in operations, especially to achieve encirclement control of specific targets, has become a technical challenge. Traditional encirclement control methods often rely on manual operations, which are not only inefficient but also difficult to cope with the rapidly changing marine environment and emergencies. Therefore, it is particularly important to develop an automated control method that can adapt to complex marine environments and achieve the goal of multi-unmanned ship cooperative encirclement.

[0003] With the development of control theory and artificial intelligence technology, the control problem of multi-unmanned ship systems has gradually become a research hotspot. The design of the controller is directly related to the stability and response speed of the unmanned ship system, while the periodic dynamic event-triggered mechanism can optimize the transmission of control signals and reduce the computational and communication burdens. Designing a solution that reduces the computational burden and achieves fast and accurate encirclement can provide strong technical support for fields such as marine resource development, maritime search and rescue, and environmental monitoring. Summary of the Invention

[0004] The purpose of this application is to provide a periodic dynamic event-triggered encirclement control method for multi-unmanned ships based on an estimator to solve the problems of heavy computational burden and increased complexity in related technologies and achieve fast and accurate encirclement effects.

[0005] The technical solution adopted by the present invention is as follows:

[0006] According to the first aspect of this application, a periodic dynamic event-triggered encirclement control method for multi-unmanned ships based on an estimator is provided, including:

[0007] Establish a system model of multi-unmanned ships;

[0008] Determine the encirclement target, and obtain the speed estimate value and position estimate value of the target by using a target estimator;

[0009] According to the geometric relationship between the multi-unmanned ships and the target, establish a mathematical model of the encirclement target; according to the mathematical model of the encirclement target and the target speed estimate value and position estimate value obtained by the target estimator, use a first controller to calculate the desired speed required for the multi-unmanned ships to achieve target encirclement;

[0010] Based on the desired speeds of the multi-unmanned vessels obtained by the first controller, the control inputs of the multi-unmanned vessels are calculated using the second controller, and the motion control of the unmanned vessels is achieved by substituting the control inputs into the system model of the multi-unmanned vessels;

[0011] The second controller is provided with a periodic dynamic event-triggering mechanism. Based on the periodic dynamic event-triggering mechanism of the second controller, the event-triggering conditions are verified, the event-triggering moments at which the control inputs calculated by the second controller are transmitted are calculated, and the control input signals are transmitted to the multi-unmanned vessel motion model at the event-triggering moments, so that the multi-unmanned vessel system realizes the encirclement control of the target.

[0012] Furthermore, the system model of the multi-unmanned vessels includes a multi-unmanned vessel dynamics model and a multi-unmanned vessel kinematics model; when constructing the multi-unmanned vessel kinematics model, the position vector of the unmanned vessel in the Earth-fixed inertial frame is defined, including the abscissa, ordinate, and yaw angle; the velocity vector of the unmanned vessel in the Earth-fixed inertial frame is defined, including the longitudinal velocity, transverse drift velocity, and yaw angular velocity.

[0013] When constructing the multi-unmanned vessel dynamics model, unknown nonlinear functions generated by the low-frequency components of hydrodynamic effects and environmental forces such as wind, waves, and currents acting on the unmanned vessels, as well as unknown but bounded high-frequency external disturbances caused by the high-frequency components of the environmental forces, control inputs, longitudinal moments, and yaw moments acting on the multi-unmanned vessels are defined.

[0014] Furthermore, the target controller enables each unmanned vessel to estimate the position information of the target. When designing the target controller, first, a target trajectory generated by a nonlinear system is designed according to the specific situation of the nonlinear target existing in the actual scenario. Considering that not all unmanned vessels can directly obtain the information of the target, the communication topology is used to represent the communication between the systems of the multi-unmanned vessels, and the target estimator enables each unmanned vessel to estimate the information of the target, so as to realize the subsequent encirclement control.

[0015] Furthermore, the mathematical model of the encirclement target needs to be able to achieve distance maintenance and uniform interval surrounding of the multi-unmanned vessels for the target.

[0016] Furthermore, the design of the second controller includes a nonlinear robust term for handling high-frequency external disturbances and neural network weight estimates and their update laws for approximating the nonlinear parts of the velocity subsystem and the yaw subsystem. Thus, according to the second controller, the control inputs of the multi-unmanned vessel system can be calculated.

[0017] Further, a periodic dynamic event-triggering mechanism of the second controller is designed according to the speed error between the desired speed and the actual speed of the multi-unmanned ship and the yaw between the desired yaw speed and the actual yaw speed, so as to limit the control input signal to be updated only at specific moments to the control signal calculated by the second controller.

[0018] According to a second aspect of the present application, there is provided an estimator-based multi-unmanned ship periodic dynamic event-triggering pursuit control device for implementing the method as described in the first aspect. According to a third aspect of the present application, there is provided an electronic device, including:

[0019] One or more processors;

[0020] A memory for storing one or more programs;

[0021] When the one or more programs are executed by the one or more processors, the one or more processors implement the method as described in the first aspect.

[0022] According to a fourth aspect of the present application, there is provided a computer-readable storage medium having computer instructions stored thereon, characterized in that when the instructions are executed by a processor, the steps of the method as described in the first aspect are implemented.

[0023] The technical solution of the present application has the following beneficial effects:

[0024] The target estimator in the multi-unmanned ship pursuit control method proposed in the present application can effectively process the dynamic characteristics of non-linear targets, providing reliable input information for the first controller; the second controller ensures the stability and smoothness of the control process, avoiding the occurrence of chattering phenomena; by introducing a periodic dynamic event-triggering mechanism, the transmission strategy of the control signal is optimized, reducing the communication burden and avoiding the Zeno phenomenon. The proposed method not only realizes the effective pursuit of the target, but also ensures the boundedness of the tracking error, improving the success rate and reliability of the pursuit task.

[0025] It should be understood that the above general description and the following detailed description are only exemplary and explanatory, and cannot limit the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] The accompanying drawings herein are incorporated into the specification and constitute a part of this specification, showing embodiments consistent with the present application and used together with the specification to explain the principles of the present application.

[0027] Figure 1 is a flowchart of an estimator-based multi-unmanned ship periodic dynamic event-triggering pursuit control method shown according to an exemplary embodiment.

[0028] Figure 2It is a schematic diagram of the target encirclement control of the multi-unmanned ship system according to an embodiment of the present invention.

[0029] Figure 3 It is a schematic diagram of the error between the abscissa of the actual position and the abscissa of the desired position and the time response of its reference signal in an embodiment of the present invention.

[0030] Figure 4 It is a schematic diagram of the error between the ordinate of the actual position and the ordinate of the desired position and the time response of its reference signal in an embodiment of the present invention.

[0031] Figure 5 It is a schematic diagram of the error between the actual yaw angle and the desired yaw angle and the time response of its reference signal in an embodiment of the present invention.

[0032] Figure 6 It is a schematic diagram of the time interval and time response of periodic dynamic event triggering in an embodiment of the present invention.

[0033] Figure 7 It is a block diagram of a multi-unmanned ship periodic dynamic event-triggered encirclement control device based on an estimator shown according to an exemplary embodiment. Detailed implementation mode

[0034] Here, the exemplary embodiments will be described in detail, and the examples are shown in the drawings. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The implementation manners described in the following exemplary embodiments do not represent all implementation manners consistent with the present application. On the contrary, they are only examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0035] The terms used in the present application are only for the purpose of describing specific embodiments and are not intended to limit the present application. The singular forms of "a", "the" and "said" used in the present application and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term "and / or" used herein refers to and includes any or all possible combinations of one or more of the associated listed items.

[0036] It should be understood that although the terms first, second, third, etc. may be used in the present application to describe various information, such information should not be limited to these terms. These terms are only used to distinguish the same type of information from each other.

[0037] Figure 1 It is a flowchart of a multi-unmanned ship periodic dynamic event-triggered encirclement control method based on an estimator shown according to an exemplary embodiment. As Figure 1 shown, the method may include the following steps:

[0038] S1: Establish the system model of multiple unmanned boats, including the dynamic model and kinematic model of multiple unmanned boats.

[0039] S2: Determine the encirclement target, design a target estimator, and use the estimator to obtain the estimated velocity value and estimated position value of the target.

[0040] S3: Propose the geometric relationship between the multiple unmanned boats and the target, establish the mathematical model of the encirclement target, and design the first controller according to the estimated velocity value and estimated position value of the target obtained by the target estimator, and calculate the desired velocity required for the multiple unmanned boats to achieve encirclement.

[0041] S4: Design the second controller according to the velocity information of the multiple unmanned boats obtained by the first controller, including a motion controller and a yaw controller, and calculate the control input of the multiple unmanned boats.

[0042] S5: Design the periodic dynamic event-triggering mechanism of the second controller according to the velocity error between the desired velocity and the actual velocity of the multiple unmanned boats and the yaw between the desired yaw velocity and the actual yaw velocity. By periodically verifying the event-triggering condition, calculate the event-triggering moment for transmitting the control signal obtained by the first controller, and transmit the control signal at the event-triggering moment.

[0043] As can be seen from the above embodiments, the present application adopts an encirclement control method based on a multiple unmanned boat system. By establishing the dynamic and kinematic models of multiple unmanned boats, and combining the estimated velocity and estimated position values of the target obtained by the target estimator, the first controller and the second controller are designed to achieve the encirclement of the target. In addition, by adopting the periodic dynamic event-triggering mechanism, the computational burden and the burden on the communication channel are effectively reduced, and the real-time performance and reliability of the system are improved.

[0044] In the specific implementation of S1: Establish the system model of multiple unmanned boats, including the dynamic model and kinematic model of multiple unmanned boats.

[0045] Among them, the kinematic model of the multiple unmanned boats is expressed as:

[0046]

[0047] Among them, i represents the i-th unmanned boat, i ∈ {1, 2,..., N}, and there are N unmanned boats in the system, N ≥ 3. p i = [x i , y i T , [x i , y i , φ i TDenote the position vector of the $i$-th unmanned ship in the Earth-fixed inertial system as $\boldsymbol{x}$ i , $\boldsymbol{y}$ i , $\varphi$ i represent the abscissa, ordinate and yaw angle of the $i$-th unmanned ship respectively, and the superscript $T$ represents transpose; $\boldsymbol{v}$ i = $R(\varphi$ i )[\boldsymbol{u}$ i , $\boldsymbol{v}$ i $ T Denote the velocity vector of the $i$-th unmanned ship in the geodetic coordinate system as $\boldsymbol{v}$, and $[\boldsymbol{u}$ i , $\boldsymbol{v}$ i , $\boldsymbol{r}$ i denote the velocity vector of the unmanned ship in the Earth-fixed inertial system. $\boldsymbol{u}$ i , $\boldsymbol{v}$ i , $\boldsymbol{r}$ i represent the longitudinal velocity, transverse drift velocity and yaw angular velocity of the $i$-th unmanned ship respectively; Denote the rotation matrix of the $i$-th unmanned ship as $R$.

[0048] The multi-unmanned ship dynamics model is expressed as:

[0049]

[0050] where denotes the unknown nonlinear function generated by the hydrodynamic effect and the low-frequency components of environmental forces such as wind, wave and current acting on the unmanned ship; $\boldsymbol{f}$ i $(\boldsymbol{v}$ i , $\boldsymbol{r}$ i ) = $[\boldsymbol{f}$ u，i $(\boldsymbol{v}$ i , $\boldsymbol{r}$ i ) $\boldsymbol{f}$ v，i $(\boldsymbol{v}$ i , $\boldsymbol{r}$ i )]$ T , $\boldsymbol{f}$ i $(\boldsymbol{v}$ i , $\boldsymbol{r}$ i ) denotes the combined force of Coriolis force and centripetal force, and $\boldsymbol{f}$ u，i $(\boldsymbol{v}$ i , $\boldsymbol{r}$ i ), $\boldsymbol{f}$ v，i $(\boldsymbol{v}$ i , $\boldsymbol{r}$ i ), $\boldsymbol{f}$ r，i $(\boldsymbol{v}$ i , $\boldsymbol{r}$ i ) represent Coriolis force, centripetal force and hydrodynamic damping force respectively, denotes the combined conversion quantity of longitudinal velocity and lateral velocity disturbances received by the $i$-th unmanned ship, $R(\varphi$ i ) denotes the derivative of the rotation matrix of the $i$-th unmanned ship, $\boldsymbol{d}$e，u and d e，v and d e，r respectively represent the high-frequency external disturbances that affect the longitudinal speed, cross-drift speed, and yaw angular velocity of the unmanned ship, including unknown but bounded high-frequency external disturbances caused by the high-frequency components of environmental forces, and also including vibrations from the electromechanical system; represents the conversion quantity of the longitudinal torque control input, represents the conversion matrix, m u，i represents the inertial coefficient of the i-th unmanned ship in longitudinal motion, m r，i represents the inertial coefficient of the i-th unmanned ship in yaw motion, τ u，i and τ r，i are control inputs, representing the longitudinal torque and yaw torque acting on the multi-unmanned ship respectively.

[0051] In the specific implementation of S2: Determine the enclosure target, and use the target estimator to obtain the speed estimate value and position estimate value of the target. Specifically, an optional implementation process is as follows:

[0052] Design a target trajectory generated by a nonlinear system according to the specific situation of the nonlinear target existing in the actual scenario, and the position vector of its target p0 = [x0, y0, φ0] T where x0, y0, and φ0 respectively represent the abscissa, ordinate, and yaw angle of the target. is the derivative of the position vector p0 of the target with respect to time, and it satisfies:

[0053]

[0054] where the function g(.) is a globally defined sufficiently smooth function for generating the target trajectory.

[0055] Considering that not all unmanned ships can directly obtain the information of the target, it is necessary to make an assumption about the communication topology so that each unmanned ship can obtain the information of the target. Among them, the communication topology can be represented by a graph, node 0 represents the target, nodes 1 to N represent unmanned ships, and the edges represent the communication connections between unmanned ships, a i ij is used to represent the weight of the edge from the i-th node to the j-th node. If there is a communication connection between these two unmanned ships, then a ij > 0, otherwise it is 0, and the specific value of a ij is set as a known quantity according to the actual situation. It is assumed that the communication topology can be divided into a directed spanning tree with the target as the root, that is, each unmanned ship can obtain the information of the target through a directed path from the root node.

[0056] The target estimator is designed as follows:

[0057]

[0058]

[0059] where γ is a positive constant, represents the position information of the target estimated by the i-th unmanned ship at time t, represents the estimated value of the target speed obtained by the i-th unmanned ship at time t, and both can be directly calculated by formula (4).

[0060] In the present invention, the design of the target estimator enables each unmanned ship to estimate the information of the target, thereby realizing subsequent encirclement control.

[0061] In the specific implementation of S3: Establish the geometric relationship between multiple unmanned ships and the target, establish the mathematical model of the encirclement target, and obtain the estimated target speed and position estimate according to the mathematical model of the encirclement target and the target estimator (4) Design the first controller to calculate the expected speed required for multiple unmanned ships to achieve encirclement. Specifically, an optional implementation process is as follows:

[0062] Establish the geometric relationship between multiple unmanned ships and the target. The relative distance η between the i-th unmanned ship and the target i and the azimuth angle βi are expressed as follows:

[0063]

[0064]

[0065] where x t and y t represent the horizontal and vertical coordinates of the moving target in the earth coordinate system at time t, and x i and y i represent the horizontal and vertical coordinates of the i-th unmanned ship in the earth coordinate system.

[0066] Establish the mathematical model of the encirclement target, that is, to achieve the encirclement of the target by multiple unmanned ships, the following performance needs to be achieved:

[0067] (1) Distance maintenance: For a specific distance η d and any constant ε1 > 0, multiple unmanned ships can be controlled to meet the following requirements for the relative distance η between the i-th unmanned ship and the target i :

[0068]

[0069] (2) Uniformly spaced surrounding: It is required that N unmanned boats cooperate to maintain a circular formation with a uniform interval. That is, for any constant ε2 > 0, the multi-unmanned boats can be controlled to meet the following requirements for the azimuth difference between the ith unmanned boat and the jth unmanned boat:

[0070]

[0071] Among them, represents the error between the actual angular phase β of the ith unmanned boat i and the expected angular phase .

[0072] According to the target position estimate obtained in S2 and the target speed estimate d，i , design the first controller to obtain the expected speed v of the multi-unmanned boats

[0073]

[0074] Among them, represents the difference between the actual position pi of the ith unmanned boat and the target position estimate , η d represents the preset holding distance between the unmanned boat and the target, and ι1 > 0 is a constant. is a skew-symmetric matrix; represents the cooperation variable, and the specific form is as follows:

[0075]

[0076] Among them, ι2 is a positive constant. represents the expected encirclement angular velocity.

[0077] According to the designed first controller (9), the expected speed v required for the multi-unmanned boats to achieve encirclement can be calculated d，i .

[0078] In the specific implementation of S4: According to the expected speed information of the multi-unmanned boats obtained from the first controller, design the second controller, which includes a motion controller and a yaw controller, and calculate the control input of the multi-unmanned boats.

[0079] Define the speed tracking error as e v，i = v d，i - v i , and the yaw tracking error is Among them represents the expected yaw angular velocity, which is a known quantity.

[0080] Design the second controller based on the speed tracking error and the yaw tracking error as follows:

[0081]

[0082] wherein, k1, k2, k3, and k4 are positive constants, k1e v，i and k3e r，i are linear feedback terms, k2tanh(e v，i ) and k4tanh(e r，i ) are non-linear robust terms designed to handle high-frequency external disturbances, h i , h r，i respectively represent the speed radial basis function and the yaw radial basis function set by the i-th unmanned ship according to the neural network center and width; and are used to introduce the neural network, representing the neural network weight estimation values of the i-th unmanned ship for approximating the non-linear parts of the speed subsystem and the yaw subsystem, which are specifically calculated by the following update law:

[0083]

[0084]

[0085] wherein, γ v > 0 and γ r > 0 represent the learning update rates, h i and h r，i represent the radial basis functions, which are determined by the center vector and width of the neural network corresponding to the i-th unmanned ship.

[0086] Thus, according to the second controllers (13) and (14), and τ r，i can be calculated, and further τ is calculated to obtain τ u，i r i , and the control input (τ u，i , τ r，i ) of the multi-unmanned ship system is obtained.

[0087] In the specific implementation of S5: According to the speed error between the desired speed and the actual speed of the multi-unmanned ship, and the error between the desired yaw speed and the actual yaw speed, design the periodic dynamic event trigger mechanism of the second controller. By periodically verifying the event trigger condition, calculate the event trigger moment for the transmission of the control signal obtained by the second controller, and transmit the control signal at the event trigger moment.

[0088] To reduce the computational burden and channel burden, a periodic dynamic event-triggering mechanism is designed for the second controllers (13) and (14) above. It periodically calculates whether the dynamic event-triggering condition is met, and transmits the control input of the multi-unmanned surface vehicle system at specific dynamic event-triggering moments.

[0089] Define the actually transmitted control input signal as Specifically, it is expressed as follows:

[0090]

[0091] where t k represents the time of the k-th meeting the periodic dynamic event-triggering condition, that is, the control input signal is updated to the control signal calculated by the second controller only at t k moments; t k+1 represents the time of the next meeting the periodic dynamic event-triggering condition.

[0092] Define the error between the actually transmitted control input signal caused by the periodic dynamic event-triggering mechanism and the control signal (τ u，i , τ r，i ) calculated in real time by the second controllers (13) and (14) as (e Δ，v，i , e Δ，r，i ), where Accordingly, the periodic dynamic event-triggering conditions for the longitudinal moment and yaw moment inputs controlling the unmanned surface vehicle are designed as follows:

[0093]

[0094] where μ > 0 represents a periodic sampling step with a certain upper bound, jμ represents having passed j periodic sampling steps μ, and the event-triggering condition is checked for each step. represents the set of positive integers; ρ v，i , ρ r，i represent the dynamic event-triggering variables of the side-slip velocity and yaw angular velocity of the i-th unmanned surface vehicle. In the form of dynamic design, the specific expressions are as follows:

[0095]

[0096] where β1 and β2 represent constants and satisfy β2 - β1 - 1 < 0.

[0097] Adopt the periodic dynamic event-triggering conditions shown in formulas (19) and (20). Taking formula (19) as an example, after the moment of t u，k , it is judged whether each periodic sampling step meets Take the greatest lower bound of the set that meets the conditions as the next time t that meets the periodic dynamic event triggering condition u，k+1 。

[0098] The present invention comprehensively utilizes the above-mentioned target estimator, the first controller, and the second controller with a periodic dynamic event triggering mechanism, enabling the multi-unmanned ship system to achieve the encirclement control of the target. Among them, the target estimator (4) obtains the estimated values of the speed and position of the target, providing target information for the encirclement; the first controller (9) calculates the desired speed required for the encirclement based on these estimated values; the second controller, including a motion controller (13) and a yaw controller (14), is used to initially generate a control input signal to adjust the motion attitude of the multi-unmanned ship to achieve the encirclement. The periodic dynamic event triggering mechanism (17) and (18) optimize the transmission of the control signal. By periodically verifying the event triggering conditions (19) and (20), the event triggering moments for the transmission of the control signal obtained by the second controller (9) are calculated, and the control signal is transmitted at the event triggering moments, improving the system efficiency.

[0099] To more effectively illustrate the effectiveness of the method of the present invention, it is verified by simulation. All parameters and parameter matrices are initialized as shown in Table 1:

[0100] Table 1 Parameters and parameter initialization

[0101]

[0102]

[0103] Figure 2 It is the effect diagram of the target encirclement control of the multi-unmanned ship system shown in the embodiment of the present invention. It can be seen that the three unmanned ships achieve the encirclement of the target, and the achieved encirclement effect is satisfactory. Figure 3 represents the error between the abscissa of the actual position and the abscissa of the desired position of each unmanned ship, gradually tending to 0 from a large deviation at the initial moment; Figure 4 represents the error between the ordinate of the actual position and the ordinate of the desired position of each unmanned ship, gradually tending to 0 from a large deviation at the initial moment; Figure 5 represents the error between the actual yaw angle and the desired yaw angle of each unmanned ship, gradually tending to 0 from a large deviation at the initial moment; Figure 6 shows the time interval of the periodic dynamic event triggering. It can be seen that the time interval is a multiple of the periodic sampling time of 0.1 s and only triggers at specific moments to transmit the control input signal.

[0104] Corresponding to the embodiment of the estimator-based periodic dynamic event-triggered multi-unmanned-vessel pursuit control method described above, the present application also provides an embodiment of an estimator-based periodic dynamic event-triggered multi-unmanned-vessel pursuit control device.

[0105] Figure 7 It is a block diagram of an estimator-based periodic dynamic event-triggered multi-unmanned-vessel pursuit control device shown according to an exemplary embodiment. Referring to Figure 7 , the device includes:

[0106] A multi-unmanned-vessel system model module, which is used to receive a control input signal to control the movement of the unmanned vessels and achieve the pursuit of the target by the multi-unmanned-vessel system;

[0107] A target estimator module, which is used to obtain the speed estimate value and position estimate value of the pursuit target;

[0108] A first controller module, which is used to establish a pursuit target mathematical model according to the geometric relationship between the multi-unmanned vessels and the target; according to the pursuit target mathematical model and the target speed estimate value and position estimate value obtained by the target estimator, use the first controller to calculate the desired speed required for the multi-unmanned vessels to achieve target pursuit;

[0109] A second controller module, which has a periodic dynamic event-triggering mechanism, and according to the desired speed of the multi-unmanned vessels obtained by the first controller, uses the second controller to calculate the control input of the multi-unmanned vessels, and transmits the control input signal to the multi-unmanned-vessel motion model at the event trigger moment.

[0110] Regarding the device in the above embodiment, the specific ways for each module to perform operations have been described in detail in the embodiment of the method, and will not be elaborated here.

[0111] For the device embodiment, since it basically corresponds to the method embodiment, the relevant parts can refer to the partial description of the method embodiment. The device embodiments described above are only illustrative. The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of the present application. Those of ordinary skill in the art can understand and implement it without creative efforts.

[0112] Correspondingly, the present application further provides an electronic device, including: one or more processors; a memory for storing one or more programs; when the one or more programs are executed by the one or more processors, the one or more processors implement the estimator-based multi-unmanned vessel periodic dynamic event-triggered enclosing control method as described above.

[0113] Correspondingly, the present application further provides a computer-readable storage medium, on which computer instructions are stored, and when the instructions are executed by a processor, the estimator-based multi-unmanned vessel periodic dynamic event-triggered enclosing control method as described above is implemented.

[0114] It can be understood that the above storage medium may include a random access memory (RAM), and may also include a non-volatile memory (NVM), such as at least one disk memory. At the same time, the storage medium may also be various media such as a USB flash drive, a mobile hard disk, a magnetic disk or an optical disc that can store program codes.

[0115] It can be understood that the above-mentioned processor may be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it may also be a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.

[0116] Those skilled in the art will readily conceive of other embodiments of the present application after considering the specification and practicing the content disclosed herein. The present application is intended to cover any variations, uses, or adaptations of the present application, which follow the general principles of the present application and include common general knowledge or conventional technical means in the technical field not disclosed in the present application. The specification and examples are only regarded as exemplary, and the true scope and spirit of the present application are pointed out by the claims.

[0117] It should be understood that the present application is not limited to the exact structures described above and shown in the drawings, and various modifications and changes can be made without departing from its scope. The scope of the present application is only limited by the appended claims.

Claims

1. A periodic dynamic event-triggered capture control method for multiple unmanned ships based on an estimator, characterized in that: include: Establish a system model of multiple unmanned ships; Determine the capture target, and use the target estimator to obtain the target's speed estimation value and position estimation value; According to the geometric relationship between multiple unmanned ships and the target, a mathematical model for capturing the target is established; According to the mathematical model of the encirclement target and the target speed estimation value and the position estimation value obtained by the target estimator, the first controller is used to calculate the desired speed required for the multiple unmanned ships to achieve the target encirclement; The target estimator enables each unmanned ship to estimate the position information of the target, and the target estimator is expressed as: Among them, γ is a positive constant, They represent the estimated target positions of the i-th unmanned ship and the j-th unmanned ship at time t, respectively. represents the derivative of the estimated target position obtained by the i-th unmanned ship at time t, a ij represents the communication connection weight between the i-th unmanned ship and the j-th unmanned ship, a i0 represents the communication connection weight between the ith unmanned ship and the target, N represents the number of unmanned ships, p0 represents the target position vector determined by the target trajectory generated by the nonlinear system, and g is a smooth function; represents the estimated target speed obtained by the i-th unmanned ship at time t; According to the desired speed of the multiple unmanned ships obtained by the first controller, the control input of the multiple unmanned ships is calculated by the second controller, and the motion control of the unmanned ships is realized by substituting the control input into the system model of the multiple unmanned ships; The second controller is provided with a periodic dynamic event trigger mechanism. The event trigger condition is verified based on the periodic dynamic event trigger mechanism of the second controller, the event trigger time of the control input transmission calculated by the second controller is calculated, and the control input signal is transmitted to the multi-unmanned ship motion model at the event trigger time, so that the multi-unmanned ship system can realize the capture control of the target.

2. The method for controlling the periodic dynamic events of multiple unmanned ships triggered by estimators according to claim 1 is characterized in that: The system model of multiple unmanned ships includes a dynamic model of multiple unmanned ships and a kinematic model of multiple unmanned ships, including: Define the position vector [x i ,y i ,φ i ] T , x i ,y i ,φ i Represent the horizontal coordinate, vertical coordinate and yaw angle respectively; construct the velocity vector [u i ,v i ,r i ],u i ,v i ,r i Representing the longitudinal velocity, drift velocity and yaw angular velocity, the dynamic model of the multi-unmanned ship is obtained: Among them, p i =[x i ,y i ] T represents the actual position of the i-th unmanned ship, v i =R(φ i )[u i ,v i ] T represents the velocity vector of the i-th unmanned ship in the earth coordinate system, R(φ i ) represents the rotation matrix of the i-th unmanned ship; Define the unknown nonlinear function including the low-frequency components of the hydrodynamic effect and the environmental force acting on the unmanned ship. and an unknown but bounded high-frequency external perturbation caused by the high-frequency components of the environmental forces , and obtain the multi-unmanned ship dynamics model: The multi-unmanned ship dynamics model: Among them, f i (v i ,r i ) represents the combined force of the Coriolis force and the centripetal force on the i-th unmanned ship, represents the conversion amount of the longitudinal torque control input of the i-th unmanned ship; τ u,i , τ r,i They represent the longitudinal moment and yaw moment acting on the i-th unmanned ship, respectively, as control inputs; f r,i (v i ,r i ) represents the hydrodynamic damping force on the i-th unmanned ship, m r,i represents the inertia coefficient of the i-th unmanned ship in yaw motion, d e,u d e,v d e,r They represent the high-frequency external disturbances that affect the longitudinal velocity, lateral drift velocity, and yaw angular velocity of the unmanned ship, Γ(v i ) represents the transformation matrix corresponding to the i-th unmanned ship.

3. The method for controlling the periodic dynamic events of multiple unmanned ships triggered by estimators according to claim 1 is characterized in that: The method of establishing a mathematical model for capturing a target based on the geometric relationship between the multiple unmanned ships and the target includes: Establishing a geometric relationship between the multiple unmanned ships and the target, wherein the geometric relationship represents a relative distance and azimuth between the unmanned ships and the target; Establish a mathematical model for capturing targets. The capture of targets by multiple unmanned vessels needs to meet the distance maintenance condition and the uniform interval surrounding condition. Among them, the distance maintenance condition is: for a specific distance η d As for any constant ε1>0, multiple unmanned ships can achieve the following relative distance η between the i-th unmanned ship and the target under control: u Requirements: The uniformly spaced surround condition is: for any constant ε2>0, the multiple unmanned ships can meet the following requirements for the azimuth difference between the i-th unmanned ship and the j-th unmanned ship under control: Where t represents time, They represent the errors between the actual angular phase and the expected angular phase of the i-th and j-th unmanned ships respectively, and N represents the number of unmanned ships.

4. The method for controlling the periodic dynamic events of multiple unmanned ships triggered by estimators according to claim 3 is characterized in that: The first controller is represented as: Among them, v d,i represents the expected speed of the i-th unmanned ship, represents the estimated target speed of the i-th unmanned ship at time t, represents the estimated target position obtained by the i-th unmanned ship at time t, ι1 is a positive constant, η d represents the preset distance between the UAV and the target, ρ ti represents the difference between the actual position of the i-th unmanned ship and the estimated target position, Λ is a symmetric matrix, represents the covariate, represents the expected capture angular velocity, ι2 is a positive constant, a ij represents the communication connection weight between the i-th unmanned ship and the j-th unmanned ship.

5. The method for controlling the periodic dynamic events of multiple unmanned ships triggered by estimators according to claim 2 is characterized in that: The second controller includes a motion controller and a yaw controller; The motion controller is expressed as: The yaw controller is expressed as: Among them, k1, k2, k3 and k4 are positive constants, v d,i represents the expected speed of the i-th unmanned ship, represents the expected yaw speed of the i-th unmanned ship, e v,i represents the speed tracking error of the i-th unmanned ship, e r,i represents the yaw tracking error of the i-th unmanned ship, They represent the estimated weights of the neural network used by the i-th unmanned ship to approximate the nonlinear parts of the speed subsystem and the yaw subsystem, respectively, and h i 、h r,i They represent the speed radial basis function and yaw radial basis function of the i-th unmanned ship according to the center and width of the neural network respectively.

6. The method for controlling the periodic dynamic events of multiple unmanned ships triggered by estimators according to claim 5 is characterized in that: The periodic dynamic event triggering mechanism is based on the speed error e between the expected speed and the actual speed of the multi-unmanned ship. v,i , and the yaw error e between the expected yaw speed and the actual yaw speed r,i The motion controller and the yaw controller are designed separately to independently determine the event triggering moment of the control input transmission; The triggering conditions of the periodic dynamic event triggering mechanism are as follows: Among them, t u,k ,t u,k+1 Indicates the time when the kth and k+1th motion controllers meet the triggering conditions of periodic dynamic events, t r,k ,t r,k+1 represents the time when the kth and k+1th yaw controllers meet the triggering conditions of periodic dynamic events, inf represents the maximum lower bound, ζ represents the periodic sampling step, j represents the jth period, and e Δ,v,i 、e Δ,r,i They represent the control input τ calculated in real time. u,i , τ r,i The control input actually being transmitted The error between represents the set of integers greater than 0, ρ v,i ,ρ r,i Represent the dynamic event trigger variables of the motion controller and yaw controller respectively, expressed as: Among them, β1 and β2 represent constants and satisfy β2-β1-1<0; Represents ρ v,i ,ρ r,i The derivative of .

7. A periodic dynamic event-triggered capture control device for multiple unmanned ships based on an estimator, characterized in that: include: A multi-unmanned ship system model module is used to receive control input signals to control the movement of the unmanned ships, thereby realizing the capture of targets by the multi-unmanned ship system; The target estimator module is used to obtain the velocity estimation value and position estimation value of the captured target, which is expressed as: Among them, γ is a positive constant, They represent the estimated target positions of the i-th unmanned ship and the j-th unmanned ship at time t, respectively. represents the derivative of the estimated target position obtained by the i-th unmanned ship at time t, a ij represents the communication connection weight between the i-th unmanned ship and the j-th unmanned ship, a i0 represents the communication connection weight between the ith unmanned ship and the target, N represents the number of unmanned ships, p0 represents the target position vector determined by the target trajectory generated by the nonlinear system, and g is a smooth function; represents the estimated target speed obtained by the i-th unmanned ship at time t; A first controller module is used to establish a mathematical model of the target to be captured based on the geometric relationship between the multiple unmanned ships and the target; and to calculate the desired speed required for the multiple unmanned ships to capture the target based on the mathematical model of the target to be captured and the target speed estimation value and position estimation value obtained by the target estimator using the first controller; The second controller module has a periodic dynamic event triggering mechanism. According to the expected speed of the multiple unmanned ships obtained by the first controller, the control input of the multiple unmanned ships is calculated by the second controller, and the control input signal is transmitted to the motion model of the multiple unmanned ships at the event triggering moment.

8. An electronic device, characterized in that: include: one or more processors; A memory for storing one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the method according to any one of claims 1 to 5.

9. A computer-readable storage medium having computer instructions stored thereon, characterized in that: When the instruction is executed by a processor, the steps of the method according to any one of claims 1 to 5 are implemented.

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