An unmanned ship cluster safe formation game control method and controller

Abstract

The application discloses a kind of unmanned vehicle cluster security formation game control method and controller, comprising the following steps: establishing a plurality of underactuated unmanned vehicle mathematical model affected by external disturbance;Based on the underactuated unmanned vehicle mathematical model, the position information estimation of unmanned vehicle to nearby neighbor unmanned vehicle is realized;Based on the first filter adaptive extended state observer, the estimation of unknown unmanned vehicle model and external disturbance in earth coordinate system is realized;Based on the control-Lyapunov equation-control barrier function control method ， Design model-free optimal thrust control law in earth coordinate system;Based on the stability constraint set of control barrier function, the collision avoidance safety constraint set between unmanned ship is obtained, and the optimal longitudinal thrust is obtained based on the longitudinal thrust optimization problem of unmanned vehicle;Based on the second filter adaptive extended state observer, the estimation of unknown unmanned vehicle model and external disturbance in yaw direction is realized;Design model-free optimal yaw moment control law;Based on yaw moment optimization problem, the optimal yaw moment is obtained, and the game safety control in the process of unmanned vehicle cluster formation is realized based on the optimal yaw moment.

Description

Technical Field

[0001] This invention relates to the field of motion control of unmanned surface vessels (USVs) swarms, and more particularly to a structure and design method for a safe formation game controller for USV swarms. Background Technology

[0002] Unmanned surface vessels (USVs) are important tools for humankind in developing and protecting the oceans, possessing advantages such as unmanned operation, miniaturization, and intelligence. Equipped with various sensors, navigation systems, and autonomous motion control systems, USVs can navigate autonomously on the water and perform operational tasks, finding widespread application in military and civilian fields. Countries worldwide are increasing their efforts in the research, development, and utilization of USVs.

[0003] Cooperative control of unmanned surface vessel (USV) swarms has become a hot research topic in recent years, with its methods being widely studied due to their significant advantages in improving the efficiency of offshore exploration and development. A common characteristic of existing research on cooperative control of USV swarms is that most studies only consider the cooperative relationship between USVs, i.e., the USV swarm achieves its collective formation goal through swarm collaboration. However, in reality, each USV may have its own individual interests due to energy consumption or safety considerations, potentially leading to conflicts between individual interests and the collective formation goal, resulting in non-cooperative relationships among USV swarm members. Game theory is an effective method for solving non-cooperative problems, and considerable research results have been obtained in general nonlinear swarm systems. In the field of non-cooperative motion control of USV swarms, some scholars have proposed a non-cooperative dynamic positioning control method for USV swarms, achieving a Nash equilibrium between the swarm's dynamic positioning goal and individual interest goals.

[0004] However, existing unmanned surface vessel swarm control systems still have the following shortcomings:

[0005] First, existing unmanned surface vessel (USV) swarm formation control methods only consider cooperative relationships and only need to achieve the global formation objective. However, existing non-cooperative USV swarm control methods only consider the dynamic positioning control scenario of non-cooperative swarms and cannot achieve non-cooperative formation control of USV swarms.

[0006] Second, in existing non-cooperative control methods for unmanned surface vessel (USV) swarms, the control law design for USVs does not consider collision avoidance issues between USVs or between USVs and obstacles. If the navigation safety of USV swarms cannot be guaranteed, it may lead to formation failure or even accidents.

[0007] Third, the design of dynamic controllers in existing unmanned surface vessel (USV) swarm non-cooperative control methods relies on the prior mathematical model information of the USV. In other words, the design of the underlying controller of the USV cannot be applied to the non-cooperative control of USV swarms where the model parameters are completely unknown. Summary of the Invention

[0008] To address the shortcomings of existing technologies, a method for safety control in unmanned surface vessel (USV) swarm formation game includes the following steps:

[0009] Establish multiple mathematical models of underactuated unmanned surface vessels affected by external disturbances;

[0010] Based on the mathematical model of underactuated unmanned surface vessels (USVs), the position information of USVs of nearby USVs can be estimated.

[0011] Based on the first filter adaptive extended state observer, the estimation of external disturbances in the unknown unmanned surface vessel model and the Earth coordinate system is realized;

[0012] Based on the control-Lyapunov equation-control barrier function control method, a model-free optimal thrust control law is designed in the Earth coordinate system.

[0013] Based on the stability constraint set of the control obstacle function, the collision avoidance safety constraint set between unmanned vessels is obtained, and the optimal longitudinal thrust is obtained based on the longitudinal thrust optimization problem of unmanned vessels.

[0014] Based on the second-filter adaptive extended state observer, the estimation of the unknown unmanned surface vessel model and external disturbances in the bow roll direction is realized;

[0015] Design a model-free optimal bow roll torque control law;

[0016] Based on the problem of optimizing the bow roll moment, the optimal bow roll moment is obtained, and game-theoretic safety control is achieved during the formation of unmanned surface vessel swarms based on the optimal bow roll moment.

[0017] Furthermore, the process of estimating the position information of neighboring unmanned surface vessels (USVs) based on the underactuated USV mathematical model is as follows:

[0018] Consider N non-cooperative formation game motion generators with the following dynamics:

[0019]

[0020] The meanings of the symbols in the above formula are as follows: These are the position vector and input vector of the i-th motion generator, respectively; J i (s i Let ) represent the cost function of the i-th unmanned surface vessel; The gradient of the cost function is represented.

[0021] In formula (2) Where s ij The estimation of the position of the j-th motion generator by the i-th motion generator has the following dynamics:

[0022]

[0023] The meanings of the symbols in the above formula are as follows: Represents the neighbor set of the i-th motion generator; To estimate the gain; s kj This is the estimate of the position of the j-th motion generator by the k-th motion generator.

[0024] Furthermore: the first filtered adaptive extended state observer is established as follows:

[0025] Simultaneously estimate f i q and The first filter adaptive extended state observer is established as follows:

[0026]

[0027] The meanings of the symbols in the above formula are as follows: q i f i q b i u The estimated value; This indicates the speed estimation error of the unmanned surface vessel; It is the observer that estimates the gain; Proj represents the projection operator; sgn represents the sign function. It is an estimate of the integral variable; q if , and It is the output of the filter.

[0028] Furthermore: the control method based on the control-Lyapunov equation-control barrier function designs the model-free optimal thrust control law in Earth coordinates as follows:

[0029]

[0030] The meanings of the symbols in the above formula are as follows: It is the observer gain; The thrust in the northeast coordinate system; This indicates the speed estimation error of the unmanned surface vessel; f i q b i u The estimated value, This represents the optimal thrust in the Earth coordinate system.

[0031] Furthermore: the stability constraint set based on the control obstacle function yields the collision avoidance safety constraint set between unmanned surface vessels (USVs), and the process of obtaining the optimal longitudinal thrust based on the longitudinal thrust optimization problem of USVs is as follows:

[0032] The stability constraint set based on the control barrier function is represented as follows:

[0033]

[0034] In the formula A i1 =[02,I2; 02,02]; B i1 =[02,I2] T ; Q i1 and It is a symmetric positive definite matrix.

[0035] The collision avoidance behavior between unmanned surface vessels is encoded as a candidate input-state safety-control obstacle function: h ij (p i )=||p ij || 2 -R c 2 , Defined function family h ij (p i ) is χ ij,0 =h ij , The set of safety constraints for collision avoidance between unmanned vessels is then represented as:

[0036]

[0037] In the formula This represents the optimal thrust in the Earth coordinate system. h ij For f i z Lie derivative in direction; h ij For Lie derivative in direction; κ i1 (·),κ i2 (·) belongs to class K functions;

[0038] Obstacle avoidance behavior is coded as h io (p i )=||p io || 2 -(R o +ρ o ) 2 , The obstacle avoidance safety constraints are then set as follows:

[0039]

[0040] The symbols in the formula are defined as follows:

[0041] To unify stability constraints and security constraints The longitudinal thrust optimization problem is formulated as follows:

[0042]

[0043] The meanings of the symbols in the above formula are as follows: This represents the cost function of the unmanned surface vessel under optimal thrust in the Earth coordinate system. δ i It is a slack variable; Ψ i1 ,Ψ i2 Represents the constraint variables of the optimization problem.

[0044] The optimal control force is obtained by solving the optimization problem (9). And the optimal longitudinal thrust is obtained.

[0045]

[0046] Furthermore, the process of estimating the unknown unmanned surface vessel model and external disturbances in the bow direction based on the second-filtered adaptive extended state observer is as follows:

[0047] Simultaneously estimate f i r and The second filtered adaptive extended state observer is established as follows:

[0048]

[0049] The meanings of the symbols in the above formula are as follows: r i f i r b i r The estimated value; This indicates the turning speed error of the unmanned surface vessel; It is an estimate of the integral variable; It is the observer's estimated gain.

[0050] Furthermore, the process of designing the model-free optimal bow roll moment control law is as follows:

[0051] Consider the desired heading signal Define its derivative along equation (2) as right Find the time derivative. To stabilize ψ ie The model-free control law is designed as follows:

[0052]

[0053] The meanings of the symbols in the above formula are as follows: It is the observer gain; For bow roll torque; in This indicates the estimation error of the bow roll rate of the unmanned surface vessel; f i r b i r The estimated value; This represents the optimal control torque.

[0054] Furthermore, the design of the bow roll moment optimization problem is as follows:

[0055]

[0056] In the formula Ψ represents the cost function of the unmanned surface vessel under optimal control torque. i3 ,Ψ i4 Represents the constraint variables of the optimization problem.

[0057] A safety controller device for unmanned surface vessel swarm formation gaming includes:

[0058] Underactuated unmanned surface vessel (USV) mathematical model unit: Establish multiple mathematical models of underactuated USVs affected by external disturbances;

[0059] Non-cooperative formation game motion generator design unit: used to estimate the position information of neighboring unmanned surface vessels based on the mathematical model of underactuated unmanned surface vessels;

[0060] First Filter Adaptive Extended State Observer Unit: Used to estimate the unknown unmanned surface vessel model and external disturbances in the Earth coordinate system based on the first filter adaptive extended state observer;

[0061] Model-free optimal forward thrust control law unit: used for designing model-free optimal forward thrust control law in the Earth coordinate system based on the control-Lyapunov equation-control obstacle function control method;

[0062] Longitudinal thrust optimization unit: used to obtain the collision avoidance safety constraint set between unmanned vessels based on the stability constraint set of the control obstacle function, and to obtain the optimal longitudinal thrust based on the longitudinal thrust optimization problem of unmanned vessels;

[0063] Second Filter Adaptive Extended State Observer Unit: Based on the second filter adaptive extended state observer, the estimation of the unknown unmanned surface vessel model and external disturbances in the bow roll direction is realized;

[0064] Model-free optimal bow roll moment control law unit: used for designing model-free optimal bow roll moment control laws;

[0065] The bow pitch moment optimization unit is used to obtain the optimal bow pitch moment based on the bow pitch moment optimization problem, and to realize game-theoretic safety control during the formation of unmanned surface vessel swarms based on the optimal bow pitch moment.

[0066] This invention aims to develop a safe formation game controller for underactuated unmanned surface vessel (USV) swarms with completely unknown model parameters, enabling multiple USVs to achieve their individual interests while tracking a reference trajectory in formation. To achieve this objective, the invention discloses a structure for a safe formation game controller for USV swarms as follows: Figure 1 As shown, it includes an underactuated unmanned surface vessel mathematical model unit, a non-cooperative formation game motion generator design unit, a filtered adaptive extended state observer unit, a model-free optimal forward thrust control law unit, a model-free optimal yaw moment control law unit, a longitudinal thrust optimization unit, and a yaw moment optimization unit.

[0067] The output of the underactuated unmanned surface vessel (USV) mathematical model unit is connected to the input of the first filtered adaptive extended state observer unit in the optimal longitudinal thrust design, the second filtered adaptive extended state observer unit in the optimal yaw moment design, and the non-cooperative game motion generator design unit; the output of the longitudinal thrust optimization unit, the first filtered adaptive extended state observer unit in the optimal longitudinal thrust design, and the non-cooperative game motion generator design unit is connected to the input of the model-free optimal forward thrust control law unit; the output of the yaw moment optimization unit and the second filtered adaptive extended state observer unit in the optimal yaw moment design is connected to the input of the model-free optimal yaw moment control law unit; and the output of the model-free optimal forward thrust control law unit and the model-free optimal yaw moment control law unit is connected to the input of the underactuated USV mathematical model unit.

[0068] Compared with existing technologies, the main innovations of this invention are summarized as follows:

[0069] First, compared with existing unmanned surface vessel (USV) swarm control methods based on cooperative relationships, this invention designs a motion generator based on game theory for each USV, realizing the Nash point seeking problem between the global swarm objective and the individual interest objectives of USVs, and achieving non-cooperative swarm control.

[0070] Second, compared with existing non-cooperative control methods for unmanned surface vessel (USV) swarms, this invention proposes a non-cooperative control scheme based on the control Lyapunov equation and the control obstacle function, which satisfies the non-cooperative control requirements of USVs while ensuring the safety of non-cooperative USV swarm control.

[0071] Third, compared with existing non-cooperative formation control methods for unmanned surface vessel (USV) swarms, the filter adaptive extended state observer proposed in this invention can achieve online estimation of USV model uncertainties, external environmental disturbances, and unknown control input gains, making non-cooperative USV swarm control independent of any prior model parameters. Attached Figure Description

[0072] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0073] Figure 1 This is a schematic diagram of a controller structure for a safe formation game between unmanned surface vessels (USVs).

[0074] Figure 2 This is a diagram illustrating a non-cooperative formation of three unmanned surface vessels.

[0075] Figure 3 This is a schematic diagram illustrating the tracking errors of three unmanned surface vessels;

[0076] Figure 4 It is the distance between unmanned surface vessels that meets all safety constraints;

[0077] Figure 5 It is the distance between the unmanned surface vessel and the obstacle that satisfies all safety constraints. Detailed Implementation

[0078] It should be noted that, unless otherwise specified, the embodiments and features in the embodiments of the present invention can be combined with each other. The present invention will be described in detail below with reference to the accompanying drawings and embodiments.

[0079] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The following description of at least one exemplary embodiment is merely illustrative and is in no way intended to limit the present invention or its application or use. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0080] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the scope of exemplary embodiments according to the invention. As used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise. Furthermore, it should be understood that when the terms "comprising" and / or "including" are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.

[0081] Unless otherwise specifically stated, the relative arrangement, numerical expressions, and values ​​of the components and steps described in these embodiments do not limit the scope of the invention. It should also be understood that, for ease of description, the dimensions of the various parts shown in the drawings are not drawn to actual scale. Techniques, methods, and devices known to those skilled in the art may not be discussed in detail, but where appropriate, such techniques, methods, and devices should be considered part of the specification. In all examples shown and discussed herein, any specific values ​​should be interpreted as merely exemplary and not as limitations. Therefore, other examples of exemplary embodiments may have different values. It should be noted that similar reference numerals and letters in the following figures denote similar items; therefore, once an item is defined in one figure, it need not be further discussed in subsequent figures.

[0082] In the description of this invention, it should be understood that the orientation or positional relationship indicated by directional terms such as "front, back, up, down, left, right", "horizontal, vertical, horizontal" and "top, bottom" is generally based on the orientation or positional relationship shown in the accompanying drawings, and is only for the convenience of describing this invention and simplifying the description. Unless otherwise stated, these directional terms do not indicate or imply that the device or element referred to must have a specific orientation or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation on the scope of protection of this invention. The directional terms "inner" and "outer" refer to the inner and outer contours relative to the outline of each component itself.

[0083] For ease of description, spatial relative terms such as "above," "over," "on the upper surface of," "above," etc., are used herein to describe the spatial positional relationship of a device or feature as shown in the figures to other devices or features. It should be understood that spatial relative terms are intended to encompass different orientations in use or operation besides the orientation of the device as described in the figures. For example, if the device in the figures is inverted, a device described as "above" or "above" other devices or structures would subsequently be positioned as "below" or "under" other devices or structures. Thus, the exemplary term "above" can include both "above" and "below." The device may also be positioned in other different ways (rotated 90 degrees or in other orientations), and the spatial relative descriptions used herein will be interpreted accordingly.

[0084] Furthermore, it should be noted that the use of terms such as "first" and "second" to define components is merely for the purpose of distinguishing the corresponding components. Unless otherwise stated, the above terms have no special meaning and therefore should not be construed as limiting the scope of protection of this invention.

[0085] A method for security control of unmanned surface vessel (USV) swarm formation game includes the following steps:

[0086] Based on external disturbances, multiple mathematical models of underactuated unmanned surface vessels affected by external disturbances are established respectively;

[0087] Based on the mathematical model of underactuated unmanned surface vessels (USVs), the position information of USVs of nearby USVs can be estimated.

[0088] Based on the first filter adaptive extended state observer, the estimation of external disturbances in the unknown unmanned surface vessel model and the Earth coordinate system is realized;

[0089] Based on the control-Lyapunov equation-control barrier function control method, a model-free optimal forward thrust control law is designed in the Earth coordinate system.

[0090] Based on the stability constraint set of the control obstacle function, the collision avoidance safety constraint set between unmanned vessels is obtained, and the optimal longitudinal thrust is obtained based on the longitudinal thrust optimization problem of unmanned vessels.

[0091] Based on the second-filter adaptive extended state observer, the estimation of unknown unmanned surface vessel model and external disturbances in the bow roll direction is realized;

[0092] Design a model-free optimal bow roll torque control law;

[0093] Based on the problem of optimizing the bow roll moment, the optimal bow roll moment is obtained, and game-theoretic safety control is achieved during the formation of unmanned surface vessel swarms based on the optimal bow roll moment.

[0094] Furthermore, the mathematical model unit of the underactuated unmanned surface vessel

[0095] Consider a multi-unmanned surface vessel (USV) system consisting of N underactuated USVs, where the equation of motion for the i-th USV is described as follows:

[0096]

[0097] The meanings of the symbols in the above formula are as follows: p i =[x i ,y i ] T This represents the location information of the unmanned surface vessel in the northeast coordinate system; x i This represents the position coordinates of the unmanned surface vessel on the horizontal axis within the northeast coordinate system, y i The unmanned surface vessel's position coordinates on the vertical axis are represented in the northeast coordinate system; the velocity vector q i =R i (ψ i )[u i ,v i ] T ;R i (ψ i )=[cos(ψ i ),-sin(ψ i sin(ψ) i ),cos(ψ i )] is the rotation matrix, where ψ i ∈(-π,π] represents the heading angle of the unmanned surface vessel; ν i =[u i ,v i ,r i ] T Represents the velocity vector of the unmanned surface vessel; u i v represents the forward velocity in the unmanned surface vessel's hull coordinate system. i r represents the lateral velocity in the unmanned surface vessel's hull coordinate system. i This represents the bow roll rate in the unmanned surface vessel's hull coordinate system. and These are the inertia coefficients in the longitudinal and turning directions, respectively; This is the control input vector in the Earth coordinate system; Indicates longitudinal thrust; f i q f represents the lumped perturbation in the q direction, which includes model uncertainty and external disturbances; i r This represents the lumped perturbation in the r direction, which includes both model uncertainty and external disturbances. This refers to the bow roll torque.

[0098] Furthermore, the process of estimating the position information of neighboring unmanned surface vessels (USVs) based on the underactuated USV mathematical model is as follows:

[0099] Consider N non-cooperative formation game motion generators with the following dynamics:

[0100]

[0101] The meanings of the symbols in the above formula are as follows: These are the position vector and input vector of the i-th motion generator, respectively; J i (s i Let ) represent the cost function of the i-th unmanned surface vessel; The gradient of the cost function is represented.

[0102] In formula (2) Where s ij The estimation of the position of the j-th motion generator by the i-th motion generator has the following dynamics:

[0103]

[0104] The meanings of the symbols in the above formula are as follows: Represents the neighbor set of the i-th motion generator; To estimate the gain; s kj This is the estimate of the position of the j-th motion generator by the k-th motion generator.

[0105] Furthermore: the first filtered adaptive extended state observer is established as follows:

[0106] Simultaneously estimate f i q and The first filter adaptive extended state observer is established as follows:

[0107]

[0108] The meanings of the symbols in the above formula are as follows: q i f i q b i u The estimated value; This indicates the speed estimation error of the unmanned surface vessel; It is the observer that estimates the gain; Proj represents the projection operator; sgn represents the sign function. It is an estimate of the integral variable; q if , and It is the output of the filter.

[0109] Furthermore, to ensure the safety of each unmanned surface vessel (USV) in tracking the Nash equilibrium point, a control method based on the control-Lyapunov equations and control obstacle functions is proposed. This control method designs the model-free optimal thrust control law in the Earth coordinate system as follows:

[0110]

[0111] The meanings of the symbols in the above formula are as follows: It is the observer gain; The thrust in the northeast coordinate system; This indicates the speed estimation error of the unmanned surface vessel; f i q b i u The estimated value. This represents the optimal thrust in the Earth coordinate system.

[0112] Furthermore: the stability constraint set based on the control obstacle function yields the collision avoidance safety constraint set between unmanned surface vessels (USVs), and the process of obtaining the optimal longitudinal thrust based on the longitudinal thrust optimization problem of USVs is as follows:

[0113] The stability constraint set based on the control barrier function can be expressed as:

[0114]

[0115] In the formula A i1 =[02,I2; 02,02]; B i1 =[02,I2] T ; Q i1 and It is a symmetric positive definite matrix;

[0116] The collision avoidance behavior between unmanned surface vessels is encoded as a candidate input-state safety-control obstacle function: Defined function family h ij (p i ) is χ ij,0 =h ij , The set of safety constraints for collision avoidance between unmanned vessels is then represented as:

[0117]

[0118] In the formula This represents the optimal thrust in the Earth coordinate system. h ij For f i z Lie derivative in direction; h ij For Lie derivative in direction; κ i1 (·),κ i2 (·) belongs to class K functions;

[0119] Similarly, obstacle avoidance behavior is coded as h io (p i )=||p io || 2 -(R o +ρ o ) 2 , The obstacle avoidance safety constraints are then set as follows:

[0120]

[0121] The symbols in the formula are defined as follows:

[0122] To unify stability constraints and security constraints The longitudinal thrust optimization problem is formulated as follows:

[0123]

[0124] The meanings of the symbols in the above formula are as follows: This represents the cost function of the unmanned surface vessel under optimal thrust in the Earth coordinate system. δ i It is a slack variable; Ψ i1 ,Ψ i2 Represents the constraint variables of the optimization problem.

[0125] The optimal control force is obtained by solving the optimization problem (9). And the optimal longitudinal thrust is obtained.

[0126]

[0127] Furthermore, the process of estimating external disturbances in the bow roll direction based on the second-filtered adaptive extended state observer is as follows:

[0128] Simultaneously estimate f i r and The second filtered adaptive extended state observer is established as follows:

[0129]

[0130] The meanings of the symbols in the above formula are as follows: r i f i r b i r The estimated value; This indicates the turning speed error of the unmanned surface vessel; It is an estimate of the integral variable; It is the observer's estimated gain.

[0131] Furthermore, the process of designing the model-free optimal bow roll moment control law is as follows:

[0132] Consider the desired heading signal Define its derivative along equation (2) as right Find the time derivative. To stabilize ψ ie The model-free control law is designed as follows:

[0133]

[0134] The meanings of the symbols in the above formula are as follows: It is the observer gain; For bow roll torque; in This indicates the estimation error of the bow roll rate of the unmanned surface vessel; f i r b i r The estimated value; This represents the optimal control torque.

[0135] Furthermore, the design of the bow roll moment optimization problem is as follows:

[0136]

[0137] In the formula Ψ represents the cost function of the unmanned surface vessel under optimal control torque. i3 ,Ψ i4 Represents the constraint variables of the optimization problem.

[0138] The present invention discloses a structure for a safe formation game controller for unmanned surface vessel swarms, as follows: Figure 1 As shown;

[0139] A safety controller device for unmanned surface vessel swarm formation gaming includes:

[0140] Underactuated unmanned surface vessel (USV) mathematical model unit: Establish multiple mathematical models of underactuated USVs affected by external disturbances;

[0141] Non-cooperative formation game motion generator design unit: used to estimate the position information of neighboring unmanned surface vessels based on the mathematical model of underactuated unmanned surface vessels;

[0142] First Filter Adaptive Extended State Observer Unit: Used to estimate the unknown unmanned surface vessel model and external disturbances in the Earth coordinate system based on the first filter adaptive extended state observer;

[0143] Model-free optimal forward thrust control law unit: used for designing model-free optimal forward thrust control law in the Earth coordinate system based on the control-Lyapunov equation-control obstacle function control method;

[0144] Longitudinal thrust optimization unit: used to obtain the collision avoidance safety constraint set between unmanned vessels based on the stability constraint set of the control obstacle function, and to obtain the optimal longitudinal thrust based on the longitudinal thrust optimization problem of unmanned vessels;

[0145] Second Filter Adaptive Extended State Observer Unit: Based on the second filter adaptive extended state observer, the estimation of the unknown unmanned surface vessel model and external disturbances in the bow roll direction is realized;

[0146] Model-free optimal bow roll moment control law unit: used for designing model-free optimal bow roll moment control laws;

[0147] The bow pitch moment optimization unit is used to obtain the optimal bow pitch moment based on the bow pitch moment optimization problem, and to realize game-theoretic safety control during the formation of unmanned surface vessels.

[0148] The output of the underactuated unmanned surface vessel mathematical model unit is connected to the first filtered adaptive extended state observer unit and the second filtered adaptive extended state observer unit.

[0149] The output terminals of the first and second filtered adaptive extended state observer units are connected to the input terminal of the model-free optimal forward thrust control law unit.

[0150] The output of the model-free optimal forward thrust control law unit is connected to the input of the longitudinal thrust optimization unit;

[0151] The output of the underactuated unmanned surface vessel mathematical model unit is connected to the input of the second filtered adaptive extended state observer unit;

[0152] The output of the longitudinal thrust optimization unit and the output of the model-free optimal yaw moment control law unit are connected to the input of the yaw moment optimization unit.

[0153] The output of the second filter adaptive extended state observer unit is connected to the input of the model-free optimal yaw moment control law unit;

[0154] The output of the bow roll moment optimization unit is connected to the mathematical model unit of the underactuated unmanned surface vessel.

[0155] Consider three unmanned surface vessels navigating in a marine environment with obstacles. A reference trajectory is given as p. 0d =[t,t] T The formation objective of an unmanned surface vessel (USV) swarm is to enable three USVs to track a reference trajectory. However, considering the energy consumption of the USVs themselves, some USVs may have individual interests and attempt to follow other USVs, resulting in non-cooperative behavior. Under this background, the cost function chosen is... The first item represents the cluster formation task, and the second item represents individual interests. ij This represents the offset distance of an unmanned surface vessel with individual interests. The simulation results are as follows: Figures 2-5 As shown:

[0156] Figure 2 This is a schematic diagram of a non-cooperative formation of three unmanned surface vessels (USVs), illustrating how a non-cooperative motion generator can produce Nash equilibrium trajectories. The USV swarm can track the generated Nash equilibrium trajectories, achieving a Nash balance between swarm formation objectives and individual interests. Figure 3 This is a schematic diagram illustrating the tracking errors of three unmanned surface vessels; Figure 4 Describes the distances between unmanned surface vessels that satisfy all safety constraints; Figure 5 This describes the distance between the unmanned surface vessel and the obstacle while satisfying all safety constraints.

[0157] This invention is not limited to this embodiment. Any equivalent concept or modification within the technical scope disclosed in this invention shall be included within the protection scope of this invention.

[0158] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for safety control in unmanned surface vessel (USV) swarm formation game, characterized in that: Includes the following steps: Establish multiple mathematical models of underactuated unmanned surface vessels affected by external disturbances; Based on the mathematical model of underactuated unmanned surface vessels (USVs), the position information of USVs of nearby USVs can be estimated. Based on the first filter adaptive extended state observer, the estimation of external disturbances in the unknown unmanned surface vessel model and the Earth coordinate system is realized; Based on the control-Lyapunov equation-control barrier function control method, a model-free optimal thrust control law is designed in the Earth coordinate system. Based on the stability constraint set of the control obstacle function, the collision avoidance safety constraint set between unmanned vessels is obtained, and the optimal longitudinal thrust is obtained based on the longitudinal thrust optimization problem of unmanned vessels. Based on the second-filter adaptive extended state observer, the estimation of unknown unmanned surface vessel model and external disturbances in the bow roll direction is realized; Design a model-free optimal bow roll torque control law; Based on the problem of optimizing the bow pitch moment, the optimal bow pitch moment is obtained, and game-theoretic safety control is achieved during the formation of unmanned surface vessel swarms based on the optimal bow pitch moment; The first filtered adaptive extended state observer is established as follows: Simultaneously estimate and The first filter adaptive extended state observer is established as follows: （4） The meanings of the symbols in the above formula are as follows: , , They are respectively , , The estimated value; This indicates the speed estimation error of the unmanned surface vessel; , , It is the observer that estimates the gain; ; ; Represents the projection operator; Represents a symbolic function; It is an estimate of the integral variable; , , and It is the output of the filter.

2. The method for security control of unmanned surface vessel swarm formation game as described in claim 1, characterized in that: The process of estimating the position information of neighboring unmanned surface vessels (USVs) based on the underactuated USV mathematical model is as follows: Consider N non-cooperative formation game motion generators with the following dynamics: The meanings of the symbols in the above formula are as follows: , These are the position vector and input vector of the i-th motion generator, respectively; ; Let represent the cost function of the i-th unmanned surface vessel; The gradient of the cost function is represented. In formula (2) ,in The estimation of the position of the j-th motion generator by the i-th motion generator has the following dynamics: The meanings of the symbols in the above formula are as follows: Represents the neighbor set of the i-th motion generator; To estimate the gain; This is the estimate of the position of the j-th motion generator by the k-th motion generator.

3. The method for security control of unmanned surface vessel swarm formation game as described in claim 1, characterized in that: The control method based on the control-Lyapunov equations-control barrier function designs the model-free optimal thrust control law in Earth coordinates as follows: The meanings of the symbols in the above formula are as follows: It is the observer gain; ; The thrust in the northeast coordinate system; This indicates the speed estimation error of the unmanned surface vessel; , They are respectively , The estimated value, This represents the optimal thrust in the Earth coordinate system.

4. The method for security control of unmanned surface vessel swarm formation game as described in claim 1, characterized in that: The stability constraint set based on the control obstacle function yields the collision avoidance safety constraint set between unmanned surface vessels (USVs). The process of obtaining the optimal longitudinal thrust based on the USV longitudinal thrust optimization problem is as follows: The stability constraint set based on the control barrier function is represented as follows: In the formula ; ; ; ; ; ; ; and It is a symmetric positive definite matrix; The collision avoidance behavior between unmanned surface vessels is encoded as a candidate input-state safety-control obstacle function: , ; Defined function family for , , Then the safety constraint set for collision avoidance between unmanned vessels can be represented as: In the formula This represents the optimal thrust in the Earth coordinate system. express For Lie derivative in direction; express For Lie derivative in direction; , It belongs to class K functions; Obstacle avoidance behavior is coded as , The obstacle avoidance safety constraints are then set as follows: The symbols in the formula are defined as follows: ; To unify stability constraints and security constraints , The longitudinal thrust optimization problem is formulated as follows: The meanings of the symbols in the above formula are as follows: This represents the cost function of the unmanned surface vessel under optimal thrust in the Earth coordinate system. ; ; It is a slack variable; Represents the constraint variables of the optimization problem; The optimal control force is obtained by solving the optimization problem (9). And the optimal longitudinal thrust is obtained as:

5. The method for security control of unmanned surface vessel swarm formation game as described in claim 1, characterized in that: The process of estimating external disturbances in the bow roll direction based on the second-filtered adaptive extended state observer is as follows: Simultaneously estimate and The second filtered adaptive extended state observer is established as follows: （11） The meanings of the symbols in the above formula are as follows: , , They are respectively , , The estimated value; This indicates the turning speed error of the unmanned surface vessel; ; ; It is an estimate of the integral variable; , , It is the observer's estimated gain.

6. The method for security control of unmanned surface vessel swarm formation game as described in claim 1, characterized in that: The process of designing the model-free optimal bow roll moment control law is as follows: Consider the desired heading signal Define its derivative along equation (2) as ,right Find the time derivative. In order to stabilize The model-free control law is designed as follows: The meanings of the symbols in the above formula are as follows: It is the observer gain; For bow roll torque; ,in ; This indicates the estimation error of the bow roll rate of the unmanned surface vessel; , They are respectively , The estimated value; ; ; This represents the optimal control torque.

7. The method for security control of unmanned surface vessel swarm formation game as described in claim 1, characterized in that: The design of the bow roll moment optimization problem is as follows: In the formula Let represent the cost function of the unmanned surface vessel under optimal control torque. Represents the constraint variables of the optimization problem.

8. A safety controller device for unmanned surface vessel swarm formation gaming, characterized in that: include: Underactuated unmanned surface vessel (USV) mathematical model unit: Establish multiple mathematical models of underactuated USVs affected by external disturbances; Non-cooperative formation game motion generator design unit: used to estimate the position information of neighboring unmanned surface vessels based on the mathematical model of underactuated unmanned surface vessels; First Filter Adaptive Extended State Observer Unit: Used to estimate the unknown unmanned surface vessel model and external disturbances in the Earth coordinate system based on the first filter adaptive extended state observer; Model-free optimal forward thrust control law unit: used for designing model-free optimal forward thrust control law in the Earth coordinate system based on the control-Lyapunov equation-control obstacle function control method; Longitudinal thrust optimization unit: used to obtain the collision avoidance safety constraint set between unmanned vessels based on the stability constraint set of the control obstacle function, and to obtain the optimal longitudinal thrust based on the longitudinal thrust optimization problem of unmanned vessels; Second Filter Adaptive Extended State Observer Unit: Based on the second filter adaptive extended state observer, the estimation of the unknown unmanned surface vessel model and external disturbances in the bow roll direction is realized; Model-free optimal bow roll moment control law unit: used for designing model-free optimal bow roll moment control laws; Boom torque optimization unit: used to obtain the optimal boom torque based on the boom torque optimization problem, and to realize game-theoretic safety control during unmanned surface vessel swarm formation based on the optimal boom torque; The first filtered adaptive extended state observer is established as follows: Simultaneously estimate and The first filter adaptive extended state observer is established as follows: （4） The meanings of the symbols in the above formula are as follows: , , They are respectively , , The estimated value; This indicates the speed estimation error of the unmanned surface vessel; , , It is the observer that estimates the gain; ; ; Represents the projection operator; Represents a symbolic function; It is an estimate of the integral variable; , , and It is the output of the filter.

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