Ship anti-deception attack control method based on self-feedback extended state observer

Abstract

The application discloses a ship anti-deception attack control method based on a self-feedback extended state observer, which comprises the following steps: setting a virtual ship and a dynamic virtual ship to construct an L2-DVS guidance strategy; constructing a deception attack additional signal model of an unmanned ship, and acquiring a ship position signal under the deception attack according to a kinematic model of a target unmanned ship; acquiring a longitudinal speed virtual control law of the target unmanned ship and a deception attack compensation law of a yaw angle according to an error model constructed by the application, so as to obtain a yaw angular speed virtual control law / adaptive law; constructing a state memory type event triggering mechanism, and acquiring a rudder angle / rotational speed controller / adaptive law of the target unmanned ship in combination with a self-feedback compensation reduced order extended state observer, and realizing the anti-deception attack control of the target unmanned ship according to the yaw angular speed virtual control law / adaptive law and the rudder angle / rotational speed controller / adaptive law. The application solves the problem that the current application research under the network attack environment is not perfect enough, and the problem that the actuator continuously responds to the disturbances in the marine environment, which greatly increases the over-wear of the rudder.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of unmanned autonomous ship control network security and control engineering, and particularly relates to a ship anti-deception attack control method based on a self-feedback extended state observer. BACKGROUND

[0002] In the past field of unmanned ship motion control, the system of the unmanned ship mainly consists of two parts: acquisition of a reference signal and design of a controller. After a route is planned by selecting waypoints, a virtual guide ship is generated by a guidance part to generate a real-time reference signal, and a controller is designed to design a suitable control law on an error model between a real ship signal and the reference signal to make it converge [1,2,3] .

[0003] In addition, the extended state observer has been widely used in active disturbance rejection control, compensation of unknown items of a model [4] , and there is an application of disturbance observation in the field of unmanned ships, and the advantage is that the nonlinear part and random disturbance can be estimated and compensated into the controller to make the controller [5-7] , and the design process is simpler, but due to the inherent characteristics of the observer, the accuracy of the system state is higher, and the application in the network attack environment is not perfect. At the same time, due to the disturbance of the unmanned ship in the marine environment, the actuator will respond to the disturbance continuously, especially the over-wearing problem caused by the rudder. However, the existing control algorithm of the unmanned ship still has the following deficiencies:

[0004] 1) In the estimation of nonlinear and random disturbance, the past extended state observer depends on the feedback of the first-order estimation error, and in the case of deception attack, the first-order position signal is already not reliable, which limits the application of the extended state observer in the network attack environment.

[0005] 2) Due to the mutual coupling of the kinematic model signals, the estimated state is in the form of a matrix, and in the actual control process, due to the under-actuated characteristics of the unmanned ship, there is no control input in the y direction, so a large amount of system operation resources is wasted and the unnecessary design difficulty is greatly increased.

[0006] 3) The traditional hybrid threshold event triggering mechanism only considers the state change at the last moment, and when the control input is small in amplitude, the event may be triggered frequently, and when the control command curve is at the peak value, the signal may be released in a small amount [8] . SUMMARY

[0007] The present application provides a ship anti-deception attack control method based on a self-feedback extended state observer to overcome the above technical problems.

[0008] To achieve the above objectives, the technical solution of the present invention is as follows:

[0009] A ship anti-spoofing attack control method based on a self-feedback extended state observer specifically includes the following steps:

[0010] S1: Set up guided virtual ships and dynamic virtual ships to construct L2-DVS guidance strategy;

[0011] S2: Obtain the kinematic and nonlinear dynamic models of the target unmanned vessel;

[0012] S3: Construct a deception attack signal model for unmanned vessels and obtain the vessel position signal under deception attack based on the kinematic model of the target unmanned vessel;

[0013] S4: Based on the kinematic model, obtain the error model of the target unmanned vessel in the appendage coordinate system according to the ship position signal and L2-DVS guidance strategy;

[0014] Based on the error model, construct the longitudinal velocity virtual control law and the yaw angle deception attack compensation law of the target unmanned ship.

[0015] S5: By introducing dynamic surface control technology, the yaw rate virtual control law / adaptive law is obtained based on the longitudinal velocity virtual control law and the deception attack compensation law;

[0016] S6: Based on the nonlinear dynamic model of the target unmanned vessel, construct a reduced-order extended state observer with self-feedback compensation;

[0017] S7: Construct a state memory-type event triggering mechanism and combine it with a self-feedback compensated reduced-order extended state observer to obtain the controller / adaptive law of the target unmanned vessel's rudder angle / speed.

[0018] S8: Based on the virtual control law / adaptive law of yaw rate and the controller / adaptive law of rudder angle / speed, the anti-deception attack control of the target unmanned vessel is realized.

[0019] Furthermore, the L2-DVS guidance strategy constructed in S1 is specifically as follows:

[0020] A guided virtual vessel is set up to obtain the reference path of the target unmanned vessel, and a dynamic virtual vessel is set up to guide the movement of the target unmanned vessel.

[0021] The expression for the guided virtual ship model is:

[0022]

[0023] The expression for the dynamic virtual ship model is:

[0024]

[0025] In the formula: x g ,y g ,ψ g These represent the longitudinal position, lateral position, and heading angle of the guided virtual ship, respectively. They represent x respectively g ,y g ,ψ g First derivative; u g ,v g These represent the longitudinal and lateral velocities of the guided virtual ship, respectively; r d This represents the yaw rate of the guided virtual vessel, i.e., the reference yaw rate of the target unmanned vessel; x d ,y d These represent the longitudinal and lateral positions of the dynamic virtual vessel, respectively, i.e., the position reference signals of the target unmanned vessel; ψ rd ,u d ,v d These represent the yaw angle, longitudinal speed, and lateral speed of the dynamic virtual ship, respectively. and x represents d ,y d First derivative; ψ d The yaw angle of the dynamic virtual vessel is represented by the yaw reference signal of the target unmanned vessel; x and y represent the longitudinal and lateral positions of the target unmanned vessel in the geodetic coordinate system, respectively.

[0026] Obtain the relative distance z between the target unmanned surface vessel and the guided virtual vessel. e ;

[0027] The relative distance z e The expression is

[0028]

[0029] Set distance threshold L d Compare relative distances z e With distance threshold L d Size;

[0030] If the relative distance z is confirmed e Less than distance threshold L d That is, z e vL d Then the position signal of the guided virtual ship will be used as the position reference signal of the target unmanned vessel, that is...

[0031] x d =x g ,y d =y g

[0032] If the relative distance z is confirmed e Greater than or equal to distance threshold L d That is, z e ≥L d Then, based on the guidance of the virtual ship and the distance threshold L d To obtain the position reference signal of the target unmanned vessel, i.e.

[0033] x d =x g +L d cosψ d ,y d =y g +sinψ d .

[0034] Furthermore, the kinematic and nonlinear dynamic models of the target unmanned vessel obtained in S2; the expression of the kinematic model is as follows:

[0035]

[0036] The expression for the nonlinear dynamic model is as follows:

[0037]

[0038] In the formula: x, y, ψ represent the target unmanned surface vessel's position and heading signals, respectively; u, v, r represent the target unmanned surface vessel's longitudinal velocity, lateral velocity, and yaw rate, respectively; n, δ represent the control inputs provided by the main engine and servo motor, respectively; T u (·) and F r (·) represents the control gain function; d wu ,d wv ,d wr These represent disturbances caused by wind, waves, and currents in the marine environment; m u ,m v ,m r ,d u1 ,d v1 ,d r1 ,d u2 ,d v2 ,d r2 ,d u3 ,d v3 ,d r3 The unknown parameters represent the inertia, hydrodynamic damping, and nonlinear damping terms of the unmanned vessel; f u (υ),f v (υ),f r (υ) represents a nonlinear function of higher-order hydrodynamic effects.

[0039] Furthermore, S3 specifically includes the following steps:

[0040] S31: Construct a deception attack signal model for unmanned surface vessels, the expression of which is:

[0041]

[0042] In the formula: Ξ i Let i represent the deception attack signal added to the target unmanned vessel in the x, y directions, where i = [x, y]. T a i ,b i , Denotes the non-zero constant of the design and a i =[a x ,a y ,a ψ ] T ,b i =[a x ,a y ,a ψ ] T , This indicates a nonlinear function that uses trigonometric functions to simulate unknown parameters;

[0043] S32: Based on the kinematic model of the target unmanned vessel and the deception attack signal from the deception attack additional signal model, obtain the vessel's position signal under the deception attack. Its expression is as follows:

[0044]

[0045] Furthermore, S4 specifically includes the following steps:

[0046] S41: Based on the ship's position signal and the L2-DVS guidance strategy, obtain the error model of the target unmanned vessel in the appendage coordinate system;

[0047] The expression for the error model is as follows:

[0048]

[0049] Where: χ x ,χ y These represent deception attack signals Ξ x With Ξ y The first derivative; x e ,y e ,ψ e This represents the longitudinal position error, lateral position error, and heading angle error of the target unmanned surface vessel.

[0050] S42: Construct the first Lyapunov function V1 based on the error model to obtain the derivative of the first Lyapunov function.

[0051] The first Lyapunov function V1 is

[0052]

[0053] The derivative of the first Lyapunov function for

[0054]

[0055] S43: To satisfy the derivative of the first Lyapunov function Stability is determined by constructing a virtual control law for the longitudinal velocity of the target unmanned surface vessel and a deception attack compensation law for the yaw angle, the expression of which is:

[0056]

[0057] In the formula: They represent χ respectively x ,χ y The estimated value of α; u This represents the virtual control law for longitudinal velocity; The deception attack compensation law representing the yaw angle; K u ,K r1 Indicates design parameters.

[0058] Furthermore, S5 specifically includes the following steps:

[0059] S51: By introducing dynamic surface control technology, the longitudinal velocity virtual control law and the deception attack compensation law are filtered, and its expression is:

[0060]

[0061] α i (0)=β i (0)

[0062] i = r, u, ψ e

[0063] Where: β i Denotes a first-order filter; α i This refers to the collective term for the virtual control law of longitudinal velocity, the deception attack compensation law, and the virtual control law of yaw rate; τ i α represents the time constant of the first-order filter; i (0),β i (0) represents α i With β i The initial value;

[0064] S52: Define the first intermediate parameter y according to step S51. u , And y u =α u -β u ,

[0065] And based on the intermediate parameters, a second Lyapunov function V2 is constructed, the expression of which is:

[0066]

[0067] In the formula: This represents the adjustable design parameters of the second Lyapunov function; Represents χ x ,χ y The estimation error, and

[0068] Obtain the derivative of the second Lyapunov function V2 Its expression is

[0069]

[0070] In the formula: τ u , This represents the time constant of a first-order filter;

[0071] S53: To satisfy the derivative of the second Lyapunov function For stability, construct a virtual control law / adaptive law for the yaw rate of the target unmanned surface vessel, the expression of which is:

[0072]

[0073] In the formula: α r K represents the virtual control law for yaw rate. r Indicate design parameters; express The first derivative; τ r This indicates that the virtual control law α for yaw rate is achieved through dynamic surface control technology. r The time constant for performing first-order filtering.

[0074] Furthermore, the expression for the self-feedback compensated reduced-order extended state observer constructed in S6 is as follows:

[0075]

[0076] In the formula: G = [T u ,F r ] T i = [u, r] T U = [|n|n, δ] T L1 and L2 represent the adjustable parameters of the design, Ji Indicates the extended state of the extended state observer and E i Indicates the velocity observation error and Indicates the observation error of the extended state and J represents i The estimated value; This represents the estimated value of i.

[0077] Furthermore, S7 specifically includes the following steps:

[0078] S71: The constructed state-memory-based event triggering mechanism, specifically including...

[0079] S711: Defines the state change E of the target unmanned surface vessel's rudder angle / rotation speed. u Its expression is

[0080] E u =η1E pu +η2E qu

[0081] E pu =U k (t)-U(t)

[0082] E qu =U k (t)-U(t k -τ)

[0083] In the formula: η1, η2 represent positive real numbers and η1 + η2 = 1. ξ1, ξ2 represent the adjustable parameters of the design; E pu E qu Indicates intermediate parameters; U k (t),U(t),U(t k -τ) represent the target unmanned surface vessel's rudder angle / rotation speed at time k, the target unmanned surface vessel's rudder angle / rotation speed continuous output signal, and the rudder angle / rotation speed at time t, respectively. k -Rudder angle / rotation speed at time τ;

[0084] S712: Based on the state change E u Design a state-memory type event triggering mechanism, whose expression is t. k+1 =inf{t>t k ||E u (t)|≥ξ3|U(t)|+ξ4}

[0085] In the formula: t k+1 ,t k ξ3 and ξ4 represent time parameters; ξ3 and ξ4 represent adjustable parameters of the design.

[0086] S713: Define the second intermediate parameter Ω i and

[0087] Based on the second intermediate parameter and a state-memory-based event triggering mechanism, the control input of the target unmanned vessel is obtained, and its expression is:

[0088]

[0089] In the formula: λ1, λ2 represent the adjustable parameters of the design; Represents Ω i The estimated value of α; u χ represents the virtual control law for the longitudinal velocity of the target unmanned surface vessel. i Indicates intermediate parameters and

[0090] S72: Based on the dynamic model of the target unmanned vessel and in conjunction with step S51, define the second intermediate parameter u. e ,r e Andu e =β u -u,r e =β r -r;

[0091] Based on the second intermediate parameter and the control input of the target unmanned vessel, a third Lyapunov function V3 is constructed, the expression of which is:

[0092]

[0093] In the formula: Indicates the design parameters of the third Lyapunov function; Indicates the quantity of the second intermediate parameter Ω u ,Ω r The estimation error; Represents χ u ,χ r The estimation error;

[0094] Obtain the derivative of the third Lyapunov function V3 Its expression is

[0095]

[0096] S73: To satisfy the derivative of the third Lyapunov function For stability, a controller / adaptive law for the rudder angle / rotation speed of the target unmanned vessel is constructed based on a reduced-order extended state observer with self-feedback compensation. Its expression is as follows:

[0097]

[0098] In the formula: α n Indicates the rotational speed of the target unmanned surface vessel controller; α δ Indicates the rudder angle of the target unmanned surface vessel controller; k u2 ,k r3 Indicates adjustable design parameters; This represents the estimates of u,r by the reduced-order extended state observer compensated by self-feedback. Represents χ u ,χ r The estimated value; Indicate design parameters; They represent Ω respectively r ,Ω u The estimated value; Ω u (0),Ω y (0) represents Ω respectively r ,Ω u The initial value; Indicates design parameters; χ y (0),χ u (0) represents χ respectively y ,χ u The initial value; express The first derivative; express The first derivative.

[0099] Beneficial effects: This invention provides a ship anti-spoofing attack control method based on a self-feedback extended state observer, with the following beneficial effects:

[0100] 1) This invention addresses online compensation for deception attack signals. The proposed self-feedback extended state observer abandons the correction of erroneous second-order position signal errors, fundamentally avoiding the impact of deception attacks on error estimation and greatly improving the observation capability of unmanned vessel extended states.

[0101] 2) The influence of the deception attack signal is decomposed onto the coordinate system of the unmanned vessel, and the virtual control law / adaptive law of yaw rate is obtained based on the constructed longitudinal velocity virtual control law and the deception attack compensation law. A set of adaptive parameters is designed for the rate of change of the target unmanned vessel with respect to time, which can accurately compensate the control of the target unmanned vessel under the deception attack.

[0102] 3) The L1 guidance principle of UAVs is improved and applied to the guidance of underactuated UAVs. The L2-DVS guidance strategy is constructed by combining it with the DVS guidance principle. At the route generation level, the problem of the calculation error of the bow angle reference speed signal accumulating over time can be avoided, and a smoother reference path can be generated. At the UAV guidance level, when the distance between the real ship and the logical virtual ship is too large, the target UAV can be guided to approach the logical virtual ship with a smooth route by guiding the virtual ship.

[0103] 4) The state memory type event triggering mechanism proposed in this invention compensates for the problem that the traditional hybrid threshold event triggering mechanism only considers the state of the previous moment and releases a small amount of control signal due to the reduced rate of change before and after the peak by adding the use of past control signal state values, and effectively reduces the excessive wear of the actuator. Attached Figure Description

[0104] 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 from these drawings without creative effort.

[0105] Figure 1 This is a flowchart of the ship anti-spoofing attack control method based on a self-feedback extended state observer according to the present invention;

[0106] Figure 2 This is a system block diagram of ship anti-spoofing attack control in this embodiment;

[0107] Figure 3 This is a schematic diagram illustrating the principle of the L2-DVS guidance strategy in this embodiment;

[0108] Figure 4 This is a path tracking trajectory diagram of the unmanned vessel under a strong deception attack in this embodiment;

[0109] Figure 5 This is a graph showing the variation of the system's position, heading, and position errors in this embodiment.

[0110] Figure 6 This is a diagram showing the speed observation effect in this embodiment;

[0111] Figure 7 This is a diagram showing the nonlinearity and disturbance observation effects of the unmanned vessel model in this embodiment;

[0112] Figure 8 This is the adaptive compensation response diagram for deception attacks in this embodiment;

[0113] Figure 9This is a diagram illustrating the event triggering effect of the state memory-type event triggering mechanism in this embodiment. Detailed Implementation

[0114] 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, not all embodiments. 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.

[0115] This embodiment provides a ship anti-spoofing attack control method based on a self-feedback extended state observer, such as... Figures 1-2 As shown, the specific steps include:

[0116] S1: Set up guided virtual ships and dynamic virtual ships to construct L2-DVS guidance strategy;

[0117] Specifically, in this embodiment, within the engineering context of target unmanned surface vessel (USV) path tracking control, the reference path is generally generated by connecting waypoints, but the USV cannot perform point-to-point turning. Therefore, an improved L1 guidance system is introduced. [9] The L2-DVS guidance strategy, combined with DVS guidance, enables the USV to navigate smoothly; and the basic principle of the L2-DVS guidance strategy is as follows: Figure 3 As shown, the reference signal is generated by two virtual vessels: the guidance virtual vessel (GVS) and the dynamic virtual vessel (DVS). The GVS is used to generate a smooth reference path for the target unmanned vessel (USV), while the DVS is used to guide the USV's course.

[0118] In a specific embodiment, the constructed L2-DVS guidance strategy is as follows:

[0119] A guided virtual vessel is set up to obtain the reference path of the target unmanned vessel, and a dynamic virtual vessel is set up to guide the movement of the target unmanned vessel.

[0120] The expression for the guided virtual ship model is:

[0121]

[0122] The expression for the dynamic virtual ship model is:

[0123]

[0124] In the formula: x g ,y g ,ψ gThese represent the longitudinal position, lateral position, and heading angle of the guided virtual ship, respectively. They represent x respectively g ,y g ,ψ g First derivative; u g ,v g These represent the longitudinal and lateral velocities of the guided virtual ship, respectively; r d This represents the yaw rate of the guided virtual vessel, i.e., the reference yaw rate of the target unmanned vessel; x d ,y d These represent the longitudinal and lateral positions of the dynamic virtual vessel, respectively, i.e., the position reference signals of the target unmanned vessel; ψ rd ,u d ,v d These represent the yaw angle, longitudinal speed, and lateral speed of the dynamic virtual ship, respectively. and x represents d ,y d First derivative; ψ d The yaw angle of the dynamic virtual vessel is represented by the yaw reference signal of the target unmanned vessel; x and y represent the longitudinal and lateral positions of the target unmanned vessel in the geodetic coordinate system, respectively.

[0125] Obtain the relative distance z between the target unmanned surface vessel and the guided virtual vessel. e That is, let z e This represents the actual distance between the USV and GVS;

[0126] The relative distance z e The expression is

[0127]

[0128] Set distance threshold L d Compare relative distances z e With distance threshold L d Size;

[0129] If the relative distance z is confirmed e Less than distance threshold L d That is, z e <L d Then the position signal of the guided virtual ship will be used as the position reference signal of the target unmanned vessel, that is...

[0130] x d =x g ,y d =y g

[0131] If the relative distance z is confirmed e Greater than or equal to distance threshold Ld That is, z e ≥L d Then, based on the guidance of the virtual ship and the distance threshold L d To obtain the position reference signal of the target unmanned vessel, i.e.

[0132] x d =x g +L d cosψ d ,y d =y g +sinψ d ;

[0133] S2: Obtain the kinematic and nonlinear dynamic models of the target unmanned vessel;

[0134] The expression for the kinematic model is as follows:

[0135]

[0136] The expression for the nonlinear dynamic model is as follows:

[0137]

[0138] In the formula: x, y, ψ represent the target unmanned surface vessel's position and heading signals, respectively; u, v, r represent the target unmanned surface vessel's longitudinal velocity, lateral velocity, and yaw rate, respectively; n, δ represent the control inputs provided by the main engine and servo motor, respectively; T u (·) and F r (·) represents the control gain function; d wu ,d wv ,d wr These represent disturbances caused by wind, waves, and currents in the marine environment; m u ,m v ,m r ,d u1 ,d v1 ,d r1 ,d u2 ,d v2 ,d r2 ,d u3 ,d v3 ,d r3 The unknown parameters represent the inertia, hydrodynamic damping, and nonlinear damping terms of the unmanned vessel; f u (υ),f v (υ),f r (υ) represents a nonlinear function of higher-order hydrodynamic effects;

[0139] S3: Construct a deception attack signal model for unmanned vessels and obtain the vessel position signal under deception attack based on the kinematic model of the target unmanned vessel;

[0140] Specifically, it includes the following steps:

[0141] S31: Construct a deception attack signal model for unmanned surface vessels, the expression of which is:

[0142]

[0143] In the formula: Ξ i Let i represent the deception attack signal added to the target unmanned vessel in the x, y directions, where i = [x, y]. T a i ,b i , Denotes the non-zero constant of the design and a i =[a x ,a y ,a ψ ] T ,b i =[a x ,a y ,a ψ ] T , This indicates a nonlinear function that uses trigonometric functions to simulate unknown parameters;

[0144] S32: In this embodiment, the ship's position signal is transmitted from a geodetic coordinate system satellite to the ship station, during which it is subjected to an information injection spoofing attack.

[10] Therefore, the actual received position signal is the deception attack signal obtained by combining the kinematic model of the target unmanned vessel with the deception attack additional signal model. Its expression is:

[0145] x a =x+Ξ x

[0146] y a =y+Ξ y

[0147] S4: Based on the kinematic model, obtain the error model of the target unmanned surface vessel in the appendage coordinate system according to the ship position signal and L2-DVS guidance strategy; construct the longitudinal velocity virtual control law and the yaw angle deception attack compensation law of the target unmanned surface vessel based on the error model;

[0148] Specifically, it includes the following steps:

[0149] S41: Based on the ship's position signal and the L2-DVS guidance strategy, obtain the error model of the target unmanned vessel in the appendage coordinate system;

[0150] The expression for the error model is as follows:

[0151]

[0152] Where: χ x ,χ y These represent deception attack signals Ξ x With Ξ y The first derivative; x e ,y e ,ψ e This represents the longitudinal position error, lateral position error, and heading angle error of the target unmanned surface vessel.

[0153] S42: Construct the first Lyapunov function V1 based on the error model to obtain the derivative of the first Lyapunov function.

[0154] The first Lyapunov function V1 is

[0155]

[0156] The derivative of the first Lyapunov function for

[0157]

[0158] S43: To satisfy the derivative of the first Lyapunov function Stability is determined by constructing a virtual control law for the longitudinal velocity of the target unmanned surface vessel and a deception attack compensation law for the yaw angle, the expression of which is:

[0159]

[0160] In the formula: They represent X respectively x ,X y The estimated value of α; u This represents the virtual control law for longitudinal velocity; The deception attack compensation law representing the yaw angle; K u ,K r1 Indicates design parameters, and

[0161]

[0162] in: Indicates an adjustable positive parameter; X x (0),X y (0) represents X respectively x ,χ y The initial state value;

[0163] S5: By introducing dynamic surface control technology, the yaw rate virtual control law / adaptive law is obtained based on the longitudinal velocity virtual control law and the deception attack compensation law;

[0164] Specifically, it includes the following steps:

[0165] S51: To avoid the exponential explosion problem caused by multiple derivatives in the subsequent derivation, dynamic surface control technology is introduced. In this embodiment, two first-order filters β are used. u and To replace α u and The longitudinal velocity virtual control law and the deception attack compensation law are filtered, and their expression is as follows:

[0166]

[0167] α i (0)=β i (0)

[0168] i = r, u, ψ e

[0169] Where: β i Denotes a first-order filter; α i This refers to the collective term for the virtual control law of longitudinal velocity, the deception attack compensation law, and the virtual control law of yaw rate; τ i α represents the time constant of the first-order filter; i (0),β i (0) represents α i With β i The initial value;

[0170] S52: Define the first intermediate parameter y according to step S51. u , And y u =α u -β u , and

[0171] And based on the intermediate parameters, a second Lyapunov function V2 is constructed, the expression of which is:

[0172]

[0173] In the formula: This represents the adjustable design parameters of the second Lyapunov function; Represents χ x ,χ y The estimation error, and

[0174] Obtain the derivative of the second Lyapunov function V2 Its expression is

[0175]

[0176] In the formula: τ u , This represents the time constant of a first-order filter;

[0177] S53: To satisfy the derivative of the second Lyapunov function For stability, construct a virtual control law / adaptive law for the yaw rate of the target unmanned surface vessel, the expression of which is:

[0178]

[0179] In the formula: α r K represents the virtual control law for yaw rate. r Indicate design parameters; express The first derivative; τ r This indicates that the virtual control law α for yaw rate is achieved through dynamic surface control technology. r The time constant for first-order filtering;

[0180] S6: Based on the nonlinear dynamic model of the target unmanned vessel, construct a self-feedback compensated reduced-order extended state observer, and the expression for the self-feedback compensated reduced-order extended state observer is as follows:

[0181]

[0182] In the formula: G = [T u ,F r ] T i = [u, r] T U = [|n|n, δ] T L1 and L2 represent the adjustable parameters of the design, J i Indicates the extended state of the extended state observer and E i Indicates the velocity observation error and Indicates the observation error of the extended state and J represents i The estimated value; This represents the estimated value of i;

[0183] S7: Construct a state memory-type event triggering mechanism and combine it with a self-feedback compensated reduced-order extended state observer to obtain the controller / adaptive law of the target unmanned vessel's rudder angle / speed.

[0184] S71: To address the issue of excessive actuator wear, this embodiment introduces a state-memory-type event triggering mechanism, specifically including...

[0185] S711: Defines the state change E of the target unmanned surface vessel's rudder angle / rotation speed. u Its expression is

[0186] E u =η1E pu +η2E qu

[0187] E pu =U k (t)-U(t)

[0188] E qu =U k (t)-U(t k -τ)

[0189] In the formula: η1, η2 represent positive real numbers and η1 + η2 = 1. ξ1, ξ2 represent the adjustable parameters of the design; E pu E qu Indicates intermediate parameters; U k (t),U(t),U(t k -τ) represent the target unmanned surface vessel's rudder angle / rotation speed at time k, the target unmanned surface vessel's rudder angle / rotation speed continuous output signal, and the rudder angle / rotation speed at time t, respectively. k -Rudder angle / rotation speed at time τ;

[0190] S712: Based on the state change E u Design a state-memory type event triggering mechanism, whose expression is t. k+1 =inf{t>t k ||E u (t)|≥ξ3|U(t)|+ξ4}

[0191] In the formula: t k+1 ,t k ξ3 and ξ4 represent time parameters; ξ3 and ξ4 represent adjustable parameters of the design.

[0192] S713: Define the second intermediate parameter Ω i and

[0193] Based on the second intermediate parameter and a state-memory-based event triggering mechanism, the control input of the target unmanned vessel is obtained, and its expression is:

[0194]

[0195] In the formula: λ1, λ2 represent the adjustable parameters of the design; Represents Ω i The estimated value of α; u χ represents the virtual control law for the longitudinal velocity of the target unmanned surface vessel. iIndicates intermediate parameters and

[0196] S72: Based on the dynamic model of the target unmanned vessel and in conjunction with step S51, define the second intermediate parameter u. e ,r e Andu e =β u -u,r e =β r -r;

[0197] Based on the second intermediate parameter and the control input of the target unmanned vessel, a third Lyapunov function V3 is constructed, the expression of which is:

[0198]

[0199] In the formula: Indicates the design parameters of the third Lyapunov function; Indicates the quantity of the second intermediate parameter Ω u ,Ω r The estimation error; Represents χ u ,χ r The estimation error;

[0200] Obtain the derivative of the third Lyapunov function V3 Its expression is

[0201]

[0202] S73: To satisfy the derivative of the third Lyapunov function For stability, a controller / adaptive law for the rudder angle / rotation speed of the target unmanned vessel is constructed based on a reduced-order extended state observer with self-feedback compensation. Its expression is as follows:

[0203]

[0204] In the formula: α n Indicates the rotational speed of the target unmanned surface vessel controller; α δ Indicates the rudder angle of the target unmanned surface vessel controller; k u2 ,k r3 Indicates adjustable design parameters; This represents the estimates of u,r by the reduced-order extended state observer compensated by self-feedback. Represents χ u ,χ r The estimated value; Indicate design parameters; They represent Ω respectively r ,Ω u The estimated value; Ω u(0),Ω y (0) represents Ω respectively r ,Ω u The initial value; Indicates design parameters; χ y (0),χ u (0) represents χ respectively y ,χ u The initial value; express The first derivative; express The first derivative;

[0205] S8: Based on the virtual control law / adaptive law of yaw rate and the controller / adaptive law of rudder angle / speed, the anti-deception attack control of the target unmanned vessel is realized.

[0206] Compared with existing technologies, the ship anti-spoofing attack control method based on a self-feedback extended state observer disclosed in this embodiment has the following advantages:

[0207] 1) This invention addresses online compensation for deception attack signals. The proposed self-feedback extended state observer abandons the correction of erroneous second-order position signal errors, fundamentally avoiding the impact of deception attacks on error estimation and greatly improving the observation capability of unmanned vessel extended states.

[0208] 2) The influence of the deception attack signal is decomposed onto the coordinate system of the unmanned vessel, and the virtual control law / adaptive law of yaw rate is obtained based on the constructed longitudinal velocity virtual control law and the deception attack compensation law. A set of adaptive parameters is designed for the rate of change of the target unmanned vessel with respect to time, which can accurately compensate the control of the target unmanned vessel under the deception attack.

[0209] 3) The L1 guidance principle of UAVs is improved and applied to the guidance of underactuated UAVs. The L2-DVS guidance strategy is constructed by combining it with the DVS guidance principle. At the route generation level, the problem of the calculation error of the bow angle reference speed signal accumulating over time can be avoided, and a smoother reference path can be generated. At the UAV guidance level, when the distance between the real ship and the logical virtual ship is too large, the target UAV can be guided to approach the logical virtual ship with a smooth route by guiding the virtual ship.

[0210] 4) The state memory type event triggering mechanism proposed in this invention compensates for the problem that the traditional hybrid threshold event triggering mechanism only considers the state of the previous moment and releases a small amount of control signal due to the reduced rate of change before and after the peak by adding the use of past control signal state values, and effectively reduces the excessive wear of the actuator.

[0211] To verify the effectiveness of the method proposed in this embodiment, numerical simulation was performed using a simulation platform, and the results are shown in the figure below. This embodiment mainly verifies the superiority of the algorithm in the following four aspects:

[0212] 1. The path tracking performance of unmanned vessels under the influence of long-term large-scale deception attacks.

[0213] 2. The observation effect of the extended state observer proposed in this embodiment on the nonlinear part of the model and environmental disturbances under attack environment.

[0214] 3. Does the state memory-type event triggering mechanism proposed in this embodiment effectively reduce the wear of the actuator?

[0215] 4. Whether the adaptive compensation algorithm designed in this embodiment is effective in compensating for deception attacks.

[0216] 5. Whether the path generated by the L2-DVS guidance algorithm is smooth and easy to navigate.

[0217] In this embodiment, in order to perform the path tracking task and determine the navigation path, the waypoints selected in this embodiment are as follows: W1(150m,150m), W2(600m,200m), W3(900m,300m), W4(1350m,350m), W5(1650m,450m). The initial state of the unmanned vessel, that is, its position, initial heading angle and velocity components in the geodetic coordinate system are set as: [x(0),y(0),ψ(0),u(0),v(0),r(0)]=[140m,140m,-60°,0m / s,0m / s,0m / s].

[0218] The following interference model is used to simulate random environmental interference;

[0219]

[0220] like Figures 4-5 As shown, to verify the effectiveness of the attack compensation effect in this embodiment, a long-term continuous strong deception attack was applied. The attack model is shown in the following formula:

[0221] Ξ x =20 + 0.3cos(0.6t)

[0222] Ξ y =20 + 0.5cos(0.6t)

[0223] The attack lasted 90 seconds. The ship's position did not deviate significantly, indicating excellent tracking. The L2-DVS guidance strategy was also highly effective in generating smooth paths, and due to good control, there was no separation between the DVS and LVS. Furthermore, combined with... Figure 8It can be seen that the deception attack compensation method in this embodiment can respond quickly to attacks and has excellent compensation effect.

[0224] like Figures 6-7 The image shows the observation effect of the reduced-order self-error feedback extended state observer in this embodiment. It can be seen that the observer can perform high-precision observation of the velocity layer, thus ensuring accurate observation of the extended state.

[0225] like Figure 9 As shown in the diagram, the vertical axis represents the duration of a single trigger, and the horizontal axis represents the time axis. It can be seen that the release of control commands is effectively filtered, and the wear of the actuator is effectively alleviated.

[0226] The relevant literature involved in this embodiment is as follows:

[0227] [1]Zhang G, ShangX, LiuJ, et al. Improved iterative learningpath-followingcontrol for USVvia the potential-basedDVS guidance[J].OceanEngineering,2023,280

[0228] [2]Lekkas MA,Fossen I T.Integral LOS Path Following for Curved PathsBased on a Monotone CubicHermite SplineParametrization.[J].IEEETrans.Contr.Sys.Techn.,2014,22(6):2287-2301.

[0229] [3]Zhang G, Zhang C, Zhang

[0230] [4]Ye H,Wu S,Liu W,et al.Adaptive neural synergetic heading controlfor USVs with unknown dynamicsanddisturbances[J].OceanEngineering,2024,300117438-.

[0231] [5]Zhang Z,Huang P,Gu H,et al.ESO-based and FTDO-based anti-swingcontrol for overhead craneswith externaldisturbance[J].MeasurementandControl,2025,58(1):50-59.

[0232] [6]Zhao Y,Yang X,Zhao Z.Pitch control for floating offshore windturbines via model-dependent extended state observer-based active disturbancerejection control[J].Ocean Engineering,2025,316119883-119883.

[0233] [7]Wang Z,Liu X,Mou Q,et al.Extended-state-observer-based pressurecompensation anti-disturbance control method for hydraulic secondaryregulation system[J].Nonlinear Dynamics,2024,(prepublish):1-18.

[0234] [8]Mu X,G Z,Lu Q.Memory-event-triggered consensus control for multi-UAV systems against deceptionattacks.[J].ISAtransactions,2023,13995-105.

[0235] [9] Liang Wenxin, Song Shiwang, Zheng Yu, et al. Trajectory tracking control of UAVs based on improved L1 guidance law in high sea state [J / OL]. Journal of Naval Aviation University, 1-13 [2025-01-03].

[0236]

[10] Xu B, Hu

[0237] 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 they can still modify the technical solutions described in the foregoing embodiments, or make equivalent substitutions for 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 ship anti-spoofing attack control method based on a self-feedback extended state observer, characterized in that, Specifically, the following steps are included: S1: Set up guided virtual ships and dynamic virtual ships to construct L2-DVS guidance strategy; S2: Obtain the kinematic and nonlinear dynamic models of the target unmanned vessel; S3: Construct a deception attack signal model for unmanned vessels and obtain the vessel position signal under deception attack based on the kinematic model of the target unmanned vessel; S4: Based on the kinematic model, and according to the ship's position signal and L2-DVS guidance strategy. Obtain the error model of the target unmanned surface vessel in the attached coordinate system; Based on the error model, construct the longitudinal velocity virtual control law and the yaw angle deception attack compensation law of the target unmanned ship. S5: By introducing dynamic surface control technology, the yaw rate virtual control law / adaptive law is obtained based on the longitudinal velocity virtual control law and the deception attack compensation law; S6: Based on the nonlinear dynamic model of the target unmanned vessel, construct a reduced-order extended state observer with self-feedback compensation; S7: Construct a state memory-type event triggering mechanism and combine it with a self-feedback compensated reduced-order extended state observer to obtain the controller / adaptive law of the target unmanned vessel's rudder angle / speed. S8: Based on the virtual control law / adaptive law of yaw rate and the controller / adaptive law of rudder angle / speed, the target unmanned surface vessel is controlled against deception attacks. The L2-DVS guidance strategy constructed in S1 is specifically as follows: A guided virtual vessel is set up to obtain the reference path of the target unmanned vessel, and a dynamic virtual vessel is set up to guide the movement of the target unmanned vessel. The expression for the guided virtual ship model is: The expression for the dynamic virtual ship model is: In the formula: These represent the longitudinal position, lateral position, and heading angle of the guided virtual ship, respectively. They represent The first derivative; These represent the longitudinal and lateral velocities of the guided virtual ship, respectively. This represents the yaw rate of the guided virtual vessel, i.e., the reference yaw rate of the target unmanned vessel; These represent the longitudinal and lateral positions of the dynamic virtual vessel, respectively, i.e., the position reference signals of the target unmanned vessel; These represent the yaw angle, longitudinal speed, and lateral speed of the dynamic virtual ship, respectively. and express The first derivative; The yaw angle of the dynamic virtual vessel is represented by the yaw reference signal of the target unmanned vessel; These represent the longitudinal and lateral positions of the target unmanned surface vessel in the geodetic coordinate system, respectively. Obtain the relative distance between the target unmanned surface vessel and the guided virtual vessel. ; The relative distance The expression is Set distance threshold Compare relative distances With distance threshold Size; If the relative distance is confirmed Less than the distance threshold Right now Then the position signal of the guided virtual ship will be used as the position reference signal of the target unmanned vessel, that is... If the relative distance is confirmed Greater than or equal to the distance threshold Right now Then, based on the guidance of the virtual ship and the distance threshold... To obtain the position reference signal of the target unmanned vessel, i.e. ； The kinematic and nonlinear dynamic models of the target unmanned vessel obtained in S2; The expression for the kinematic model is as follows: The expression for the nonlinear dynamic model is as follows: In the formula: These respectively represent the target unmanned surface vessel's position and heading signals; These represent the longitudinal velocity, lateral velocity, and yaw rate of the target unmanned surface vessel, respectively. These represent the control inputs provided by the main unit and the servo motor, respectively. and Represents the control gain function; These represent disturbances caused by wind, waves, and currents in the marine environment, respectively. The unknown parameters represent the inertia, hydrodynamic damping, and nonlinear damping terms of the unmanned vessel; Nonlinear functions representing higher-order hydrodynamic effects; S3 specifically includes the following steps. S31: Construct a deception attack signal model for unmanned surface vessels, the expression of which is: In the formula: Indicates the target unmanned vessel The directional deception attack signal, and , , , Denotes the non-zero constants of the design and , , ; This indicates a nonlinear function that uses trigonometric functions to simulate unknown parameters; S32: Based on the kinematic model of the target unmanned vessel and the deception attack signal from the deception attack additional signal model, obtain the vessel's position signal under the deception attack. Its expression is as follows: ； S4 specifically includes the following steps. S41: Based on the ship's position signal and the L2-DVS guidance strategy, obtain the error model of the target unmanned vessel in the appendage coordinate system; The expression for the error model is as follows: In the formula: These represent deception attack signals. and The first derivative; This represents the longitudinal position error, lateral position error, and heading angle error of the target unmanned surface vessel. S42: Construct the first Lyapunov function based on the error model. To obtain the derivative of the first Lyapunov function. ; The first Lyapunov function for The derivative of the first Lyapunov function for S43: To satisfy the derivative of the first Lyapunov function Stability is determined by constructing a virtual control law for the longitudinal velocity of the target unmanned surface vessel and a deception attack compensation law for the yaw angle, the expression of which is: In the formula: They represent The estimated value; This represents the virtual control law for longitudinal velocity; The deception attack compensation law representing the yaw angle; Indicate design parameters; S5 specifically includes the following steps. S51: By introducing dynamic surface control technology, the longitudinal velocity virtual control law and the deception attack compensation law are filtered, and its expression is: In the formula: This represents a first-order filter; This refers to the collective term for the virtual control law of longitudinal velocity, the deception attack compensation law, and the virtual control law of yaw rate. This represents the time constant of a first-order filter; express and The initial value; S52: Define the first intermediate parameter quantity according to step S51. , , and , , ; And construct a second Lyapunov function based on the intermediate parameters. Its expression is In the formula: This represents the adjustable design parameters of the second Lyapunov function; express The estimation error, and ; Obtaining the second Lyapunov function derivative Its expression is In the formula: , This represents the time constant of a first-order filter; and Represents the second Lyapunov function The design function of the derivative; S53: To satisfy the derivative of the second Lyapunov function For stability, construct a virtual control law / adaptive law for the yaw rate of the target unmanned surface vessel, the expression of which is: In the formula: This represents the virtual control law for yaw rate; Indicate design parameters; express The first derivative; This indicates that a virtual control law for yaw rate is implemented using dynamic surface control technology. The time constant for first-order filtering; The expression for the self-feedback compensated reduced-order extended state observer constructed in S6 is: In the formula: , , ; This indicates the adjustable parameters of the design. Indicates the extended state of the extended state observer and ; Indicates the velocity observation error and ; Indicates the observation error of the extended state and ; express The estimated value; express The estimated value; S7 specifically includes the following steps: S71: The constructed state-memory-based event triggering mechanism, specifically including... S711: Define the state changes of the target unmanned surface vessel's rudder angle / speed. Its expression is In the formula: Represent positive real numbers and ; Indicates the adjustable parameters of the design; Indicates intermediate parameters; These represent the rudder angle / rotation speed of the target unmanned surface vessel at time k, the continuous output signal of the target unmanned surface vessel's rudder angle / rotation speed, and the... Rudder angle / speed at the moment of triggering; S712: Based on the change in state Design a state-memory-based event triggering mechanism, the expression of which is: In the formula: Indicates time parameters; Indicates the adjustable parameters of the design; S713: Define the second intermediate parameter quantity and , ; Based on the second intermediate parameter and a state-memory-based event triggering mechanism, the control input of the target unmanned vessel is obtained, and its expression is: In the formula: Indicates the adjustable parameters of the design; express The estimated value; The virtual control law representing the longitudinal velocity of the target unmanned surface vessel; Indicates intermediate parameters and , ; S72: Based on the dynamic model of the target unmanned vessel and in conjunction with step S51, define the second intermediate parameter. , and , ; Based on the second intermediate parameter and the control input of the target unmanned vessel, a third Lyapunov function is constructed. Its expression is In the formula: Indicates the design parameters of the third Lyapunov function; Indicates the quantity of the second intermediate parameter The estimation error; express The estimation error; Obtaining the third Lyapunov function derivative Its expression is S73: To satisfy the derivative of the third Lyapunov function For stability, a controller / adaptive law for the rudder angle / rotation speed of the target unmanned vessel is constructed based on a reduced-order extended state observer with self-feedback compensation. Its expression is as follows: In the formula: This indicates the rotational speed of the target unmanned surface vessel's controller; Indicates the rudder angle of the target unmanned surface vessel's controller; Indicates adjustable design parameters; This indicates a reduced-order extended state observer with self-feedback compensation. The estimated value; express The estimated value; Indicate design parameters; They represent The estimated value; They represent The initial value; Indicate design parameters; They represent The initial value; express The first derivative; express The first derivative.

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