Unmanned ship network marine environment area coverage control method based on observer

Abstract

The invention discloses an unmanned ship network marine environment area coverage control method based on an observer, and relates to the technical field of control engineering and control science, and the method comprises the steps: obtaining time-varying disturbance estimation generated by external environment factors to an unmanned ship in finite time through a finite time disturbance observer based on an unmanned ship network; the expected speed of the unmanned ship network is designed, and under the designed expected speed, the optimal coverage effect on the ocean task area is achieved through the unmanned ship network; and based on the external disturbance estimated by the time-varying disturbance observer, a robust coverage controller of the unmanned ship network is established, and an expected speed designed for tracking the actual speed of the unmanned ship within a fixed time is realized. According to the method, the finite time disturbance observer and the unmanned ship cluster area coverage controller are designed, analysis and simulation verification of related theories are carried out, and the optimal coverage effect of the unmanned ship network on the marine environment task area is achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of control engineering and control science, and particularly relates to a method for controlling the regional coverage of an unmanned surface vehicle network in a marine environment based on an observer. Background Art

[0002] Multi-agent distributed collaborative operations have received extensive attention due to their obvious advantages over single agents in terms of adaptability, flexibility, and reliability. Among them, unmanned surface vehicle clusters are widely used in civilian and military fields such as marine environment monitoring, waterway vigilance patrol, marine pollutant removal, and port coverage protection, all of which involve the technology of regional coverage control of unmanned surface vehicle networks in the marine environment. The regional coverage control technology mainly changes the distribution state of the agent network in the task area by controlling the movement of multiple agents in the task area, so as to achieve the optimal coverage monitoring effect of the agent network on the task area under a certain metric.

[0003] In Chinese Patent CN202311355703.1, a coverage control method, storage medium, and device for robot environmental monitoring are disclosed. In the specification of this invention patent, a control barrier function is constructed based on the energy constraint of the robot, and the control input of the robot is obtained by combining the coverage performance function to achieve the maximum continuous coverage of the area. In Chinese Patent CN202210679725.2, an air pollution source early warning and positioning method based on multi-robot formation is disclosed. In the specification of this invention patent, the centroid is calculated through Voronoi partitioning, and the Turtlebot3 robot using the differential drive control model goes to the centroid, and the regional pollution source density function is calculated according to the collected pollution concentration to achieve the positioning of the pollution source location. In Chinese Patent CN202311811151.0, a robot cluster coverage method and system with different maximum speeds based on sliding mode control are disclosed. In the specification of this invention patent, according to the customer set corresponding to each robot, the optimal coverage position of each robot in each iteration is calculated, and a robot cluster coverage system with different maximum speeds based on the first-order uniycle model of sliding mode control is proposed.

[0004] However, in the existing achievements of coverage control technology, the agent model is a simple first-order model. When the task area is a marine environment area, the agent model for performing the area coverage task is an unmanned boat model. The motion control of the unmanned boat is determined by two orders of kinematic model and dynamic model, which has higher coupling and complexity. Therefore, the existing coverage control methods based on the first-order agent model are no longer applicable. In addition, the existing achievements of coverage control technology do not consider the unknown time-varying disturbances existing in the agent control input under the influence of the external environment. When the coverage task area is a water area environment area such as the ocean, an unmanned boat needs to be used to perform the area coverage task. The unmanned boat has a high degree of freedom of movement, and the kinematic model and dynamics are more complex. There are external disturbance effects in the motion control of the unmanned boat affected by factors such as wind, waves, and currents in the marine environment. The existing achievements of area coverage control technology cannot be directly applied to the area coverage control problem of the unmanned boat network in the marine environment task area. Summary of the Invention

[0005] Aiming at the coverage control problem that the external unknown time-varying disturbances affect the unmanned boat network to perform the area coverage task in the marine environment task area, the present invention proposes an observer-based area coverage control method for the unmanned boat network in the marine environment area, solves the area coverage control problem under the influence of the high-coupling complex unmanned boat model and unknown time-varying disturbances, and realizes the optimal coverage effect of the unmanned boat network on the marine environment task area.

[0006] In the first aspect, the present invention provides an observer-based area coverage control method for the unmanned boat network in the marine environment area, including:

[0007] Based on the finite-time disturbance observer of the unmanned boat network, obtain the time-varying disturbance estimation generated by external environmental factors on the unmanned boat within a finite time;

[0008] Design the desired speed of the unmanned boat network. Under the designed desired speed, the unmanned boat network realizes the optimal coverage effect on the marine task area;

[0009] Based on the external disturbance estimated by the time-varying disturbance observer, establish a robust coverage controller for the unmanned boat network to realize that the actual speed of the unmanned boat tracks the designed desired speed within a fixed time.

[0010] In some examples, the finite-time disturbance observer based on the unmanned boat network obtains the time-varying disturbance estimation generated by external environmental factors on the unmanned boat within a finite time, including:

[0011] Establish the motion model of the unmanned boat in the environment according to the disturbance influence received by the unmanned boat in the marine environment;

[0012] The performance function is used to describe the impact of the unmanned boat on the mission area when it is at the target location, and the environmental risk density function is used to describe the risk level of any point in the mission area;

[0013] The mission area is divided according to the principle of maximum effect of the unmanned boat load, and the metric function is used to quantify the coverage effect of the unmanned boat network on the mission area.

[0014] A finite-time disturbance observer is designed to estimate the unknown time-varying disturbances generated by the ocean environment.

[0015]

[0016] In some instances, The unknown time-varying disturbances generated by the ocean environment are estimated, where is the external disturbance τ of the unmanned boat d =[τ ud τ vd τ rd ] T The estimate, Constant coefficients c1, c2>0, is the estimated vector of the unmanned boat velocity vector V = [u, v, r], M is the number of unmanned boats, u, v, r are the surge velocity, sway velocity and bow pitch velocity of the unmanned boat, C(V) is the Coriolis centripetal force matrix of the unmanned boat dynamics model, D(V) is the damping matrix of the unmanned boat dynamics model, is the control force input of the unmanned boat, τ d =[τ ud τ vd τ rd ] T The force caused by the disturbance of the external environment.

[0017] In some instances, Get the expected speed of the unmanned boat, where k r1 ,k u1 >0,ε1,ε2>0,k r2 , k u2 is a constant, ψ e is the angle error, u d is the expected surging speed of the unmanned boat, r d is the expected bow speed of the unmanned boat, C(t) is the generalized centroid of the environmental risk density in the Voronoi sub-region, is the error between the position of the unmanned boat and the generalized centroid of the Voronoi subregion to which it belongs, ψ r =arctan2(x e ,y e ) is the desired angle of the unmanned boat, ψ e =ψr - ψ deviation between the angle of the unmanned boat and the expected value.

[0018] In some instances, by A robust coverage controller for the unmanned boat network is established, where is a constant coefficient, ξ1 > 0, ξ2 > 0, M = diag{m 11 , m 22 , m 33} is the inertia matrix of the unmanned boat dynamics model, D(V) = diag{d 11 , d 22 , d 33} is the damping matrix of the unmanned boat dynamics model, V = [u, v, r] T is the unmanned boat velocity vector, u e , r e is the error between the actual velocity and the designed expected velocity of the unmanned boat.

[0019] Generally speaking, compared with the prior art, the above technical solutions conceived by the present invention can achieve the following beneficial effects:

[0020] To solve the control problem of the unmanned boat network performing area coverage tasks in the ocean environment mission area under unknown time-varying disturbances, the present invention proposes a method for controlling the area coverage of the unmanned boat network in the ocean environment under unknown disturbances based on a designed finite-time disturbance observer to achieve the optimal coverage effect of the unmanned boat network on the ocean mission area. The method proposed based on the present invention can solve the influence of external disturbances of the ocean environment on the unmanned boat in practical applications, and at the same time provides an optimal coverage control method for the unmanned boat network to perform coverage tasks in the ocean mission area, provides an implementation method for the unmanned boat network to perform tasks such as area monitoring, search and defense, and training and alert in the ocean environment area, and provides a certain solution for expanding the application of the agent network in other task environment scenarios, with broad application prospects. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] To more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are only some embodiments of the present invention. For those skilled in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0022] Figure 1 It is a flowchart of the method for controlling the area coverage of the unmanned boat network in the ocean environment based on an observer provided by the embodiment of the present invention;

[0023] Figure 2Flowchart of the operation of the unmanned boat network main control module provided by the embodiment of the present invention;

[0024] Figure 3 Schematic diagram of the motion amount of the unmanned boat provided by the embodiment of the present invention;

[0025] Figure 4 Schematic diagram of Voronoi division provided by the embodiment of the present invention;

[0026] Figure 5 Motion evolution diagram of the network area coverage of the unmanned boat provided by the embodiment of the present invention;

[0027] Figure 6 Variation curve diagram of the disturbance estimation error of the disturbance observer provided by the embodiment of the present invention, where (a) is the estimation error τ ud of the unmanned boat network disturbance τ ue , (b) is the estimation error τ v of the unmanned boat network disturbance τ ve d, (c) is the estimation error τ rd of the unmanned boat network disturbance τ re ;

[0028] Figure 7 Variation curve diagram of the position error and angle error of the unmanned boat under the expected speed provided by the embodiment of the present invention, where (a) is the variation curve of the unmanned boat network position error, and (b) is the variation curve of the unmanned boat network angle error;

[0029] Figure 8 Variation curve diagram of the speed error of the unmanned boat driven by the robust coverage controller provided by the embodiment of the present invention, where (a) is the variation curve of the surge speed error of the unmanned boat network, and (b) is the variation curve of the yaw speed error of the unmanned boat network;

[0030] Figure 9 Variation diagram of the metric function provided by the embodiment of the present invention. Detailed implementation manners

[0031] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative efforts belong to the scope of protection of the present invention.

[0032] In the following description, specific embodiments of the present invention will be described with reference to steps and symbols performed by one or more computers, unless otherwise specified. Therefore, these steps and operations will be referred to several times as being performed by a computer, and the computer execution referred to herein includes the operation of a computer processing unit on electronic signals representing data in a structured form. This operation transforms the data or maintains it in a position in the computer's memory system, which can reconfigure or otherwise change the operation of the computer in a manner well known to those skilled in the art. The data structure in which the data is maintained is a physical location in the memory, which has specific characteristics defined by the data format. However, the principles of the present invention are described in the above text, which is not meant to be a limitation, and those skilled in the art will understand that the following various steps and operations can also be implemented in hardware.

[0033] As used herein, the terms "module" or "unit" can be regarded as software objects executed on the computing system. Different components, modules, engines, and services herein can be regarded as implementation objects on the computing system. The devices and methods herein are preferably implemented in software, but of course can also be implemented in hardware, all within the protection scope of the present invention.

[0034] Those skilled in the art of the present technology can understand that, unless specifically stated otherwise, the singular forms "a", "an", and "the" used herein can also include the plural forms. It should be further understood that the term "comprising" used in the specification of the present invention means the presence of features, integers, steps, operations, elements, and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof. It should be understood that when we say an element is "connected" or "coupled" to another element, it can be directly connected or coupled to other elements, or there can also be intermediate elements. In addition, the "connection" or "coupling" used herein can include wireless connection or wireless coupling. The phrase "and / or" used herein includes all or any unit and all combinations of one or more related listed items.

[0035] Embodiments of the present invention solve the technical problems of how to estimate the unknown time-varying disturbances input to an unmanned boat caused by the marine environment, and how to design a coverage controller for the unmanned boat network to achieve the optimal coverage effect of the unmanned boat network for the mission area. It involves the theory and method of estimating unknown time-varying disturbances in the marine environment of the unmanned boat and optimizing the collaborative control area coverage of the unmanned boat network. By designing a finite-time disturbance observer and an unmanned boat cluster area coverage controller, and conducting relevant theoretical analysis and simulation verification, the optimal coverage effect of the unmanned boat network for the marine environment mission area is achieved.

[0036] Embodiments of the present invention provide an observer-based method for controlling the coverage of an unmanned boat network in a marine environment area, asFigure 1-2 As shown in the figure, it includes:

[0037] S1: Based on the finite-time disturbance observer of the unmanned boat, estimate the time-varying disturbance τ caused by the marine environment on the unmanned boat within a finite time d and use the approximate value to compensate for the time-varying disturbance τ d so as to solve the disturbance effect of the marine environment on the motion control of the unmanned boat.

[0038] Furthermore, step S1 includes:

[0039] According to the disturbance τ d = [τ ud τ vd τ rd T acting on the unmanned boat in the marine environment, the motion model of the unmanned boat in the environment is Use the performance function to describe the influence of the unmanned boat on the mission area at the position p i = [x i , y i T Use the environmental risk density function to describe the risk level of any position point in the mission area; divide the mission area according to the principle of maximizing the effect of the unmanned boat load (Voronoi division), and the Voronoi sub-region V(p ) where the unmanned boat is located is: i

[0040]

[0041] Use the metric function H(P, t) to quantify the coverage effect of the unmanned boat network on the mission area:

[0042]

[0043] The designed finite-time disturbance observer of the unmanned boat is:

[0044]

[0045] Among them, is the estimate of the external disturbance τ d = [τ ud τ vd τ rd T on the unmanned boat, The constant coefficients c1, c2 > 0, is the estimated vector of the unmanned boat speed vector.

[0046] ​​​​Specifically, step S1 includes:

[0047] L1: Model and analyze the problem of coverage control for the unmanned surface vehicle network in the marine environment. When an unmanned surface vehicle network composed of M unmanned surface vehicles performs coverage-related tasks in the marine environment mission area A, without considering heaving, rolling, and pitching, the kinematic model of the unmanned surface vehicle in the earth coordinate system is:

[0048]

[0049] where x, y, and ψ are the positions in the X and Y directions and the angle in the Z direction, and u, v, and r are the surge speed, sway speed, and yaw rate of the unmanned surface vehicle, as Figure 3 shown.

[0050] In the marine environment mission area, considering that the control force input of the unmanned surface vehicle is affected by external disturbance forces such as wind, waves, and currents in the marine environment, and the hull of the unmanned surface vehicle is symmetric left and right, its dynamic model is:

[0051]

[0052] Let M = diag{m 11 , m 22 , m 33} be the inertia matrix of the unmanned surface vehicle dynamic model, V = [u, v, r] T be the unmanned surface vehicle speed vector, be the Coriolis centripetal force matrix of the unmanned surface vehicle dynamic model, D(V) = diag{d 11 , d 22 , d 33} be the damping matrix of the unmanned surface vehicle dynamic model, be the control force of the unmanned surface vehicle, τ d = [τ ud τ vd τ rd T be the disturbance force of the external environment. The unmanned surface vehicle dynamic model can be:

[0053]

[0054] When the unmanned surface vehicle performs tasks such as environmental monitoring and pollutant removal in the marine environment area, the unmanned surface vehicle is equipped with corresponding payloads for the tasks, and the effect of the payload is related to the distance, and the effect of the payload weakens as the distance increases. Let p i = [x i , y i T be the position vector of the unmanned surface vehicle , and a ∈ A be any position point in the mission area. Here, the performance function is used​​ to describe the load effect of the mission execution payload of the unmanned boat i at different positions in the mission area on the mission area, where β i , k f are normal coefficients, which are a common attenuation function - Gaussian distance attenuation function, often used to describe the signal power attenuation characteristics. Use the environmental risk density function to describe the risk degree of any position point in the mission area, where α j is a normal coefficient, j = 1, 2, …, N are important risk sources in the mission area, is the influence of the risk source j at its position s j on the environmental risk density value of any point a in the mission area, and θ is the standard deviation. Use the Voronoi partitioning method to partition the mission area. Here, the mission area is partitioned according to the principle of the maximum load effect of the unmanned boat. When each unmanned boat is equipped with the same load, the Voronoi partition is as Figure 4 shown, the unmanned boat where the Voronoi sub-region V(p i ) is:

[0055]

[0056] It can be seen from the performance function describing the load effect of the unmanned boat that the effect of each unmanned boat outside the Voronoi sub-region V(p i ) is very small and is ignored to simplify the problem. Use the metric function H(P, t) to quantify the coverage effect of the unmanned boat network on the mission area:

[0057]

[0058] where P = [p1, p2,..., p m Τ is the position set of the unmanned boat network. The meaning of this metric function is to quantify the "attention degree" of the load effect of the unmanned boat network on the environmental risk density of the mission area. When the position where the unmanned boat network is located has a stronger load effect to "pay attention" to the area with a larger environmental risk density value, it means that the coverage effect of the unmanned boat network on the mission area is better, and the metric function value is larger. Therefore, the coverage mission objective of the unmanned boat network for the marine environment mission area is to control the position distribution of the unmanned boat network in the mission area to achieve the optimal coverage monitoring effect of the unmanned boat network on the mission area, so that the coverage effect metric function reaches the maximum value.

[0059] L2. Design a finite-time disturbance observer to estimate the unknown time-varying disturbance generated by the marine environment. Here, it is assumed that the change rate of the unknown time-varying disturbance is bounded, that is This is in line with the characteristics of the disturbance in the actual marine environment.​

[0060] Define the variable matrix:

[0061]

[0062] Design the finite-time disturbance observer for the unmanned boat as:

[0063]

[0064] For the estimation of the external disturbance τ d = [τ ud τ vd τ rd T of the unmanned boat, The constant coefficients c1, c2 > 0, is the estimated vector of the unmanned boat speed vector.

[0065] Using the nonlinear system theory, it can be proved that the designed finite-time disturbance observer can achieve That is, to achieve the effective estimation of the unknown time-varying disturbance τ d in a finite time.

[0066] The above completes the estimation of the unknown time-varying disturbance caused by the environment.

[0067] As Figure 5 shown, there are three risk sources with different intensities (N = 3) in a 100×100 mission area, and 8 unmanned boats are performing area coverage tasks (M = 8). As Figure 6 shown, the error variation of the disturbance estimation by the finite-time disturbance observer can be seen, and it can be seen that each unmanned boat can accurately estimate the external disturbance it receives.

[0068] S2. Based on the estimated external disturbance by the observer Design the desired speed of the unmanned boat as to achieve the optimal coverage effect of the unmanned boat network on the mission area. Where k r1 , k u1 > 0, ε1, ε2 > 0 are constants.

[0069] Specifically, step S2 is to design the desired speed of the unmanned boat.

[0070] The derivative of the coverage effect metric function H(P, t) with respect to the unmanned boat position vector P can be obtained as:

[0071]

[0072] Where is the contribution of the i-th unmanned boat to its affiliated Voronoi sub-region V i ​The coverage effect measure, H i (p i ,t) for p i Taking the derivative we get:

[0073]

[0074] in It can be understood as the Voronoi subregion V i The generalized mass and generalized center of mass of the environmental risk density. Therefore, it can be known that when the position of the unmanned boat is p i The generalized centroid C of the Voronoi subregion to which it belongs i (t) time (p i =C i (t)), H i (p i ,t) reaches the maximum value. Therefore, the generalized centroid of the Voronoi sub-region is the optimal position distribution of the unmanned boat network covering the mission area. The goal of optimizing the coverage control of the unmanned boat network on the mission area is to control the movement of the unmanned boat network in the mission area so that the position of the unmanned boat network is distributed at the generalized centroid of the Voronoi sub-region.

[0075] Define the error between the position of the unmanned boat and the generalized centroid of the Voronoi subregion to which it belongs:

[0076] Let ψ r =arctan2(x e ,y e ), define the angle error: ψ e =ψ r -ψ.

[0077] Design the expected surge speed u of the unmanned boat d and the desired bow speed r d for:

[0078]

[0079] where k r1 ,k u1 >0, ε1,ε2>0 are constants.

[0080] The input-state stability theory and the cascade system stability theory can prove that the desired speed of the design can be achieved: That is, the position of the unmanned boat can be located at the generalized centroid of the Voronoi sub-region to which it belongs, and the unmanned boat achieves the optimal coverage of its Voronoi partition. When each unmanned boat achieves the optimal coverage of its Voronoi partition, the unmanned boat network achieves the local optimal coverage of the mission area Q.

[0081] Figure 7 The sum of the error norms between each unmanned boat position and its optimal position (generalized Voronoi centroid position) at the desired speed of the design Angle error ψ e The curve of variation with time shows that the position error and the angle error can converge to 0, achieving effective optimal position trajectory tracking.

[0082] S3. Design the robust coverage controller of the unmanned boat to drive the unmanned boat network to achieve the optimal coverage effect of the marine environment mission area. Define the error u between the actual speed of the unmanned boat and the desired speed of the design e = u - u d 、r e = r - r d . Design the controller of the unmanned boat:

[0083]

[0084] where is a constant coefficient, and the expressions of λ1(ξ1), are:

[0085]

[0086] ξ1 > 0, ξ2 > 0,

[0087] Specifically, step S3 is to design the controller of the unmanned boat network.

[0088] Because the designed finite-time disturbance observer can estimate the actual disturbance of the unmanned boat control input within a finite time, when the finite-time disturbance observer estimates the actual disturbance, there is:

[0089]

[0090] When |u e | < 1, there is Let There is

[0091] When u e |≥1, there is Let y = |u e |, there is

[0092] For system, the conservative time for u e to converge to 0 can be calculated. When the initial value of u e is infinite (y(0) → ∞), the fixed time required for the error u e to converge from infinity to 0 is:

[0093]

[0094] Similarly, the yaw rate error r can be analyzed and obtained. e It can converge from infinity to 0 within a fixed time. Therefore, when the finite-time disturbance observer estimates the disturbance generated by the actual marine environment within a finite time, the designed controller for the unmanned surface vehicle coverage can make the speed of the unmanned surface vehicle track the designed desired speed within a fixed time. Under the designed desired speed, the unmanned surface vehicle network can achieve the optimal coverage effect for the mission area. Therefore, through the designed finite-time disturbance observer and the robust coverage controller of the unmanned surface vehicle, the optimal coverage effect of the unmanned surface vehicle network on the marine environment mission area can be realized in the presence of unknown time-varying disturbances.

[0095] Figure 8 For the errors u e and r e between the actual surge speed and yaw rate of the unmanned surface vehicle and the designed desired speed under the designed robust coverage controller, as well as the curves of their changes with time, it can be seen that the coverage controller of the unmanned surface vehicle network can drive the speed of the unmanned surface vehicle to reach the designed desired speed. Figure 9 For the curve of the metric function H(P,t) of the coverage effect of the unmanned surface vehicle network on the mission area changing with time, it can be seen that the coverage effect of the unmanned surface vehicle network on the mission area has been well optimized.

[0096] According to the embodiments of the present invention, a finite-time disturbance observer is designed to estimate the unknown time-varying disturbance caused by the marine environment, and the estimation of the external disturbance within a finite time is realized to solve the disturbance influence of the marine environment on the motion control of the unmanned surface vehicle. Then, the desired speed of the unmanned surface vehicle is designed, and it is analyzed that under the designed desired speed, the unmanned surface vehicle network can achieve the optimal coverage effect for the mission area. Finally, based on the finite-time disturbance observer, a coverage controller for the underactuated unmanned surface vehicle network is designed to drive the motion speed of the unmanned surface vehicle to track the designed desired speed within a finite time, and finally the optimal coverage effect for the marine mission area is realized.

[0097] The agent model considered in the embodiments of the present invention is the unmanned surface vehicle model commonly used in the marine environment. The unmanned surface vehicle model has a high degree of freedom, and its speed change is controlled by the control force input of the dynamic model, so as to cause a change in its position. Compared with the agent moving on land, the unmanned surface vehicle has higher complexity; in addition, the control input dimension of the unmanned surface vehicle is lower than its motion dimension, with underactuated characteristics, and different inputs jointly affect the speed change in a certain dimension, with a high degree of coupling. The embodiments of the present invention design an intelligent agent network coverage control method for the unmanned surface vehicle model based on the cascade system theory and the stability theory, and solve the problem of the coverage control of the unmanned surface vehicle network in the marine environment area.

[0098] In the embodiment of the present invention, considering the influence of external unknown time-varying disturbances on the unmanned surface vehicle, a finite-time disturbance observer is designed, which can estimate the time-varying disturbances within a finite time. Different from the general asymptotic disturbance estimation, the finite-time disturbance estimation can completely estimate the unknown disturbances within a certain time. In addition, the designed finite-time disturbance observer can estimate the time-varying disturbances and includes the case of estimating non-time-varying disturbances, having better adaptability and being more in line with practical applications.

[0099] The above has introduced in detail a method for regional coverage control of an unmanned surface vehicle network in a marine environment based on an observer. Specific examples are used in this article to elaborate on the principle and implementation manner of the present invention. The description of the above embodiments is only used to help understand the method and its core idea of the present invention. At the same time, for those skilled in the art, according to the idea of the present invention, there will be changes in the specific implementation manner and application scope. In summary, the content of this specification should not be construed as a limitation to the present invention.

Claims

1. A method for controlling the coverage of an unmanned boat network marine environment area based on an observer, characterized in that: include: A finite-time disturbance observer based on the UAV network is used to obtain the time-varying disturbance estimation caused by external environmental factors on the UAV within a finite time. Design the expected speed of the unmanned boat network. Under the designed expected speed, the unmanned boat network can achieve the optimal coverage effect of the marine mission area. Based on the external disturbance estimated by the time-varying disturbance observer, a robust coverage controller of the unmanned boat network is established to achieve the desired speed designed by tracking the actual speed of the unmanned boat within a fixed time.

2. The method according to claim 1, characterized in that The finite-time disturbance observer based on the unmanned boat network obtains the time-varying disturbance estimation caused by external environmental factors on the unmanned boat within a finite time, including: According to the disturbance effect on the unmanned boat in the marine environment, a motion model of the unmanned boat in the environment is established; The performance function is used to describe the impact of the unmanned boat on the mission area when it is at the target location, and the environmental risk density function is used to describe the risk level of any point in the mission area; The mission area is divided according to the principle of maximum effect of the unmanned boat load, and the metric function is used to quantify the coverage effect of the unmanned boat network on the mission area. A finite-time disturbance observer is designed to estimate the unknown time-varying disturbances generated by the ocean environment.

3. The method according to claim 2, characterized in that Depend on The unknown time-varying disturbances generated by the ocean environment are estimated, where is the external disturbance τ of the unmanned boat d =[τ ud τ vd τ rd ] T The estimate, Constant coefficients c1, c2>0, is the estimated vector of the unmanned boat velocity vector V = [u, v, r], M is the number of unmanned boats, u, v, r are the surge velocity, sway velocity and bow pitch velocity of the unmanned boat, C(V) is the Coriolis centripetal force matrix of the unmanned boat dynamics model, D(V) is the damping matrix of the unmanned boat dynamics model, is the control force input of the unmanned boat, τ d =[τ ud τ vd τ rd ] T The force caused by the disturbance of the external environment.

4. The method according to claim 3, characterized in that Depend on Get the expected speed of the unmanned boat, where k r1 ,k u1 >0,ε1,ε2>0,k r2 , k u2 is a constant, ψ e is the angle error, u d is the expected surging speed of the unmanned boat, r d is the expected bow speed of the unmanned boat, C(t) is the generalized centroid of the environmental risk density in the Voronoi sub-region, is the error between the position of the unmanned boat and the generalized centroid of the Voronoi subregion to which it belongs, ψ r =arctan2(x e ,y e ) is the desired angle of the unmanned boat, ψ e =ψ r -ψ Deviation of the angle of the unmanned boat from the expected value.

5. The method according to claim 4, characterized in that Depend on A robust coverage controller for the unmanned watercraft network is established, where is a constant coefficient, ξ1>0,ξ2>0, M = diag{m 11 ,m 22 ,m 33 } is the inertia matrix of the unmanned boat dynamics model, D(V)=diag{d 11 ,d 22 ,d 33 } is the damping matrix of the unmanned boat dynamics model, V = [u, v, r] T is the speed vector of the unmanned boat, u e 、r e is the error between the actual speed of the unmanned boat and the designed expected speed.

Images