Heterogeneous ship formation autonomous detection control method of quantitative trigger mechanism

Abstract

The invention discloses a heterogeneous ship formation autonomous detection control method based on a quantitative trigger mechanism, and the method comprises the steps: obtaining a heading angle of a follower ship under the action of an artificial potential field through building a gravitational function of an intrusion target for a follower dynamic virtual ship; establishing a virtual control law of a ship heading angle and a propeller rotating speed based on a position error between the ship and the dynamic virtual ship; and an event quantification triggering mechanism based on a hysteresis quantizer is established to obtain propeller control input and steering engine control input, so that autonomous detection control of the heterogeneous ship formation is realized. According to the invention, control can be carried out according to the difference of heterogeneous ship formations, the number of times of switching and changing of control signals is reduced, and the problem that a closed-loop control algorithm is unstable due to the existence of event trigger threshold parameters can be solved. The method effectively improves the robustness of a ship control system, reduces the energy consumption of the ship, and has an important application prospect in the engineering field of autonomous patrol detection of the unmanned ship.

Description

Technical Field

[0001] The present invention relates to the technical field of underactuated ship control engineering, and in particular to an autonomous detection and control method for a heterogeneous ship formation with a quantized trigger mechanism. Background Art

[0002] Hysteresis quantization algorithms have been applied in the field of ship motion control. Especially in the field of ship formation motion control. Compared with homogeneous unmanned ship formations, formations composed of heterogeneous unmanned ships are more flexible and practical in performing maritime tasks, and they can give full play to the respective advantages of various unmanned ships. However, in the existing research results, the coordinated control research is mainly carried out on the same type of intelligent agents and 1st / 2nd order heterogeneous intelligent agents, and a series of results have been achieved in the coordinated control of homogeneous ships. However, for the needs of heterogeneous unmanned ship collaborative navigation engineering, a complete control theory system has not yet been formed.

[0003] Based on the above analysis, the existing unmanned ship formation path tracking control algorithm still has the following two defects:

[0004] At present, most of the research is aimed at the formation control of the same type of ships. There is no effective control research on the differences in heterogeneous ship formations. There is a lack of application of multiple control algorithms for heterogeneous ship formation control. This has limited the development of heterogeneous ship control to a certain extent and made it difficult to meet the increasingly complex maritime mission requirements.

[0005] In the hysteresis quantization control algorithm, although it uses a quantization algorithm to reduce the execution frequency between actuators, the trigger frequency still has room for further reduction. This problem can be improved by coupling event triggering mechanism, but the research on heterogeneous ship formation control lacks the optimization of the number of execution transformations, which is not conducive to the economy of ocean navigation. In addition, at the same time, the existence of system model uncertainties and event trigger threshold parameters may also lead to instability of the closed-loop control algorithm. Summary of the invention

[0006] The present invention discloses a heterogeneous ship formation autonomous detection and control method with a quantized trigger mechanism to overcome the above technical problems.

[0007] In order to achieve the above object, the technical solution of the present invention is:

[0008] A method for autonomous detection and control of a heterogeneous ship formation with a quantitative trigger mechanism comprises the following steps:

[0009] S1: Establish a nonlinear system model of the unmanned ship considering the uncertainty of the system model;

[0010] S2: Establishing an L2 virtual ship of the leader ship, so as to establish dynamic virtual ships of the ships in the ship formation according to the improved L2-VS guidance algorithm, wherein the dynamic virtual ships include the dynamic virtual ship of the leader ship and the dynamic virtual ships of the follower ships;

[0011] S3: establishing a gravitational function of the invading target to the dynamic virtual ship of the follower ship, so as to obtain the heading angle of the follower ship under the action of the artificial potential field according to the dynamic virtual ship of the follower ship;

[0012] S4: according to the heading angle of the follower ship under the action of the artificial potential field, obtaining the position error between the ship and the dynamic virtual ship, so as to establish a virtual control law of the heading angle of the ship and a virtual control law of the propeller speed;

[0013] S5: Introducing dynamic surface control technology, according to the virtual control law of the ship heading angle and the virtual control law of the propeller speed, obtaining the variable filtered by the virtual control law of the propeller speed and the variable filtered by the virtual control law of the ship heading angle;

[0014] S6: Establish an event quantization trigger mechanism based on a hysteresis quantizer to obtain propeller control input and steering gear control input according to the variables filtered by the virtual control law of the propeller speed and the virtual control law of the bow angle and the nonlinear system model of the unmanned ship, so as to realize autonomous detection and control of heterogeneous ship formations.

[0015] Beneficial effects: The method for autonomous detection and control of heterogeneous ship formations with a quantitative trigger mechanism of the present invention establishes a gravitational function of the intruding target on the follower dynamic virtual ship, so as to obtain the heading angle of the follower ship under the action of the artificial potential field according to the dynamic virtual ship of the follower ship; then obtains the position error between the ship and the dynamic virtual ship, establishes the virtual control law of the ship heading angle and the virtual control law of the propeller speed; and establishes an event quantization trigger mechanism based on a hysteresis quantizer, so as to obtain the propeller control input and the steering gear control input according to the variables filtered by the virtual control law of the propeller speed and the ship heading angle, so as to realize autonomous detection and control of heterogeneous ship formations. The present invention can control the differences of heterogeneous ship formations, and at the same time, the event quantization trigger mechanism based on the hysteresis quantizer can reduce the number of switching changes of the control signal, and can also solve the problem of instability of the closed-loop control algorithm caused by the existence of the event trigger threshold parameter. The present invention effectively improves the robustness of the ship control system, and couples the event trigger response mechanism based on hysteresis quantization, further reducing the energy consumption of the ship and ensuring the economy of the ship's navigation. It has important application prospects in the engineering field of autonomous patrol and detection of unmanned ships. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0017] Figure 1 This is a flow chart of the autonomous detection and control method for a heterogeneous ship formation of the present invention;

[0018] Figure 2 It is the overall roadmap of the cooperative control of heterogeneous unmanned ship formation in the embodiment of the present invention;

[0019] Figure 3 A trajectory diagram of a collaborative path tracking of heterogeneous unmanned ships in an embodiment of the present invention;

[0020] Figure 4 Schematic diagram of position error and attitude error of the follower ship 1 in an embodiment of the present invention;

[0021] Figure 5 Schematic diagram of position error and attitude error of the follower ship 2 in an embodiment of the present invention;

[0022] Figure 6 Schematic diagram of position and attitude errors of a leader ship in an embodiment of the present invention;

[0023] Figure 7 Schematic diagram of the rudder angles and quantized triggered signals of the follower ship 1 and the follower ship 2 in an embodiment of the present invention;

[0024] Figure 8 Schematic diagram of the rotation speed input of the follower ships 1 and 2 in an embodiment of the present invention;

[0025] Fig. 9 This is a schematic diagram of the rotation speed and rudder angle control input of the leader ship in an embodiment of the present invention;

[0026] Fig.10 A schematic diagram of the interval durations of three trigger indicators in an embodiment of the present invention;

[0027] Fig.11a A schematic diagram of the effect of triggering with the average trigger interval duration in an embodiment of the present invention;

[0028] Fig.11b This is a schematic diagram of the trigger effect when the trigger interval is longer than 1 second in an embodiment of the present invention. DETAILED DESCRIPTION

[0029] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0030] This embodiment introduces a method for autonomous detection and control of heterogeneous ship formations with a quantitative trigger mechanism. Figure 1 and Figure 2 As shown, the following steps are included:

[0031] S1: Establish the nonlinear system model of unmanned ship;

[0032] Preferably, the nonlinear system model of the unmanned ship is established as follows:

[0033]

[0034] in,

[0035]

[0036] Where: x i represents the coordinate of the ith ship on the x-axis; y i represents the coordinate of the i-th ship on the y-axis; ψ i represents the heading angle of the i-th ship; u i represents the forward speed of the ith ship; v i represents the transverse drift speed of the i-th ship; r i represents the turning rate of the i-th ship; i represents the index number of the ship; f ui (u) represents the nonlinear term of the moment of the ship model in the forward direction; f vi (v) represents the nonlinear term of the moment of the ship model in the drift direction; f ri (r) represents the nonlinear term of the moment of the ship model in the bow turning direction; m ui Indicates the inertial mass of the ship in the forward direction; m vi Indicates the inertial mass of the ship in the transverse drift direction; m ri Indicates the inertial mass in the direction of the ship's turning; d wui Indicates the interference in the ship's forward direction; d wvi Indicates the disturbance in the ship's transverse drift direction; d wri Indicates the disturbance in the ship's steering direction; T ui (·) represents the structural parameters of the propeller; F ri (·) represents the structural parameters of the servo; TQki It is the quantized steering command signal after the event is triggered; n i Indicates the rotation speed of the ship system;

[0037] S2: Establishing an L2 virtual ship of the leader ship, so as to establish dynamic virtual ships of the ships in the ship formation according to the improved L2-VS guidance algorithm, wherein the dynamic virtual ships include the dynamic virtual ship of the leader ship and the dynamic virtual ships of the follower ships;

[0038] Preferably, the L2 virtual ship of the leader ship is established as follows:

[0039]

[0040] r d =u d / R

[0041] Where: x d Indicates the horizontal coordinate of the position of the L2 virtual ship; y d represents the vertical coordinate of the position of the L2 virtual ship; ψ d Indicates the heading angle of the L2 virtual ship; u d represents the forward speed of the L2 virtual ship; r d represents the bow angular velocity of the L2 virtual ship, where only the leader has an L2 virtual ship; represents the first-order derivative; R is the length of the ship.

[0042] Preferably, the dynamic virtual ship of the ship is established as follows:

[0043] S21, establish a dynamic virtual ship model of the ship as follows: where it is assumed that the reference trajectory of the unmanned ship is generated by real-time planning of the virtual unmanned ship, then:

[0044]

[0045] Where: x vi The horizontal coordinate of the position of the dynamic virtual ship (DVS); vi Represents the vertical coordinate of the dynamic virtual ship's position; ψ vi Indicates the heading angle of the dynamic virtual ship; u vi Indicates the forward speed of the dynamic virtual ship; r vi It represents the pitch angular velocity of the dynamic virtual ship, where each ship in the fleet has a DVS;

[0046] Specifically, the turning radius R of the ship is selected according to the maneuverability of the unmanned ship. i And the maximum turning radius R of the dynamic virtual ship max and the minimum turning radius R of the dynamic virtual ship minSince ships have large inertia and long time lag, R is the length of the ship. In addition, the minimum turning radius of the dynamic virtual ship is selected as R min =R, the maximum turning radius is R max =5R. Among them, the bow angular velocity r of the L2 virtual ship d =u d / R.

[0047] S22, when i=1, the ship is the leader ship.

[0048]

[0049] Based on the improved L2-VS guidance algorithm, we get

[0050]

[0051] Where: r v1 is the turning rate of the first dynamic virtual ship, that is, the turning rate of the dynamic virtual ship of the leader ship; u v1 represents the forward speed of the first dynamic virtual ship, that is, the forward speed of the leader's dynamic virtual ship; η is the auxiliary angle of the improved L2-VS guidance algorithm; η1 is the angle between the dynamic virtual ship and the L2 virtual ship; ψ v1 represents the heading angle of the first dynamic virtual ship, that is, the heading angle of the leader's dynamic virtual ship; |ψ v1 |denotes ψ v1 The absolute value of; L is the distance between the L2 virtual ship and the dynamic virtual ship; x d Indicates the horizontal coordinate of the position of the L2 virtual ship; y d Indicates the vertical coordinate of the position of the L2 virtual ship; x v1 The horizontal coordinate of the dynamic virtual ship position of the leader ship; y v1 It represents the vertical coordinate of the position of the dynamic virtual ship of the leader ship; R is the length of the ship.

[0052] When i≠1, the ship is a follower ship. At this time,

[0053]

[0054] Where: di represents the expected distance between the dynamic virtual ship of the follower ship and the dynamic virtual ship of the leader ship; di Represents the desired angle between the dynamic virtual ship of the follower ship and the dynamic virtual ship of the leader ship.

[0055] Specifically, the model of the L2 virtual ship (L2-VS) is consistent with the model of the ordinary dynamic virtual ship, but the input is different, because the improved L2-VS guidance algorithm of this embodiment is improved from the L2 algorithm, which is different from the moving point of the L2 guidance algorithm. This embodiment regards it as a moving virtual ship and derives the DVS virtual ship. The input of the DVS is obtained according to the positions of the L2 virtual ship and the DVS virtual ship. This algorithm eliminates the cumulative error caused by time generated by traditional guidance at the corner. The improved L2-VS guidance algorithm of this embodiment does not require calculation time, so the cumulative error generated during the turning process is eliminated.

[0056] S3: Establishing the gravitational function of the invading target to the follower dynamic virtual ship, so as to obtain the heading angle of the follower ship under the action of the artificial potential field according to the dynamic virtual ship of the follower ship;

[0057] Preferably, the heading angle of the follower ship under the action of the artificial potential field is obtained as follows:

[0058] S31: Establish the gravity function of the invasion target on the dynamic virtual ship of the mission follower as follows:

[0059]

[0060]

[0061] In the formula, F att F is the gravitational function of the invasion target on the follower dynamic virtual ship; attp is the position gravity; F attv is the velocity gravity; The unit vector of the position of the mission virtual ship pointing to the invasion target; K is the velocity unit vector of the mission virtual ship pointing to the invasion target; p , K v are gravitational coefficients, both are positive constants; ρ pg is the auxiliary variable of gravitational distance; ρ vg is the auxiliary variable of gravitational velocity; x g The horizontal coordinate of the unknown ship position; y g The ordinate of the unknown ship's position; v xg represents the speed of the unknown ship in the x direction; v yg represents the speed of the unknown ship in the y direction;

[0062] Specifically, in this embodiment, for a task ship that needs to detect an intruding ship, its detection distance L d =700m, the dynamic virtual ship is affected by the gravitational field of the position ship:

[0063] S32: Obtain the heading angle of the follower ship under the action of the artificial potential field as follows:

[0064] ψ v =arctan(F att ) (6)

[0065] Where: v It represents the heading angle of the follower dynamic virtual ship under the action of the artificial potential field;

[0066] S4: According to the heading angle of the follower ship under the action of the artificial potential field, the position error between the ship and the dynamic virtual ship is obtained to establish a virtual control law of the ship's heading angle and a virtual control law of the propeller speed:

[0067] Preferably, the method for establishing the virtual control law of the ship heading angle and the virtual control law of the propeller speed is as follows:

[0068] S41: The position error between the ship and the dynamic virtual ship is obtained as follows:

[0069]

[0070] Where: x ei is the position error in the x-axis direction; y ei is the position error in the y-axis direction; ψ ei Indicates the heading angle error; z ei represents the position error; ρ PG is the set gravity distance threshold;

[0071] Specifically, in this embodiment, when ρ pg ≤700m, ψ vi =ψ v .

[0072] S42: According to the position error between the ship and the dynamic virtual ship, the virtual control law of the ship's heading angle and the virtual control law of the propeller speed are established as follows:

[0073]

[0074] Where: α ri represents the virtual control law of the ship's heading angle; α ui A virtual control law representing the propeller speed; represents the rudder angle control parameter; k zei Represents position control parameters;

[0075] S5: When the virtual control law is further derived, in order to avoid the exponential explosion problem, the dynamic surface control technology is introduced to obtain the virtual control law filtered variables of the propeller speed and the virtual control law filtered variables of the ship bow angle;

[0076] Preferably, the formula used to obtain the variable after the virtual control law filtering of the propeller speed and the variable after the virtual control law filtering of the ship heading angle is as follows:

[0077]

[0078] Where: ε ui ,ε ri are all time constants greater than zero; β ui The filtered variable of the virtual control law representing the propeller speed; β ri represents the variable after filtering of the virtual control law of the ship's heading angle; β ui (0) indicates β ui The initial value of α ui (0) indicates α ui The initial value of α ri (0) indicates α ri The initial value of β ri (0) indicates β ri The initial value of

[0079] S6: Establish an event quantization trigger mechanism based on a hysteresis quantizer to obtain propeller control input and steering gear control input according to the variables filtered by the virtual control law of the propeller speed and the virtual control law of the bow angle and the nonlinear system model of the unmanned ship, so as to realize autonomous detection and control of heterogeneous ship formations.

[0080] Preferably, the event quantization triggering mechanism based on the hysteresis quantizer is established as follows:

[0081] First, the quantized steering command is obtained as follows: Specifically, for the hysteresis quantizer, its input and output satisfy the following relationship:

[0082]

[0083] Where: Q i (δ) represents the quantized steering order of the i-th ship; δ j represents the auxiliary variable of the quantizer, where δ j =ρ 1-j δ min,j =1,2,3…, j represents the quantization level; ρ = (1-κ) / (1+κ) represents the quantization density; δ is the control signal (steering command); k is the quantization level, k belongs to (0,1); |δ| represents the absolute value of δ; represents the first derivative of δ; δ min is the artificially set quantization dead zone, which is a positive number; δ(t - ) indicates the steering order at the last moment; Q i (δ(t -)) represents the quantized steering order at the last moment;

[0084] Secondly, according to the quantized signal, the trigger error is obtained to establish an event quantization trigger mechanism as follows:

[0085]

[0086]

[0087] Where: Indicates event trigger error; T Qki is the quantized steering signal after the event is triggered; inf{} represents the lower limit function; b δ Indicates event triggering auxiliary variable; d δ represents a positive constant; where b δ ,d δ Satisfied: 0 δ ≤1,d δ >0. k represents the simulation step length; r represents the steering rate of the rudder angle; t represents the time variable; represents the time of the k-th simulation step; Indicates T Qki exist The value of the moment;

[0088] Preferably, the method for obtaining the propeller control input and the steering gear control input is as follows:

[0089] make:

[0090]

[0091]

[0092] h ui =m ui / T ui (·)

[0093] h ri =m ri / (F ri (·)G i (1+ξ 1i )),

[0094] but

[0095] Where: N ui Indicates propeller control input; N ri Indicates the servo control input; n i Indicates the rotation speed of the ship system; δ i represents the rudder order of the i-th ship; h ui represents the adaptive parameters related to the hysteresis quantizer; h​ri represents the adaptive parameters related to the parameters of the event triggering mechanism; τ ui represents the propeller auxiliary control input; τ ri Indicates the auxiliary control input of the servo; Indicates h ui An estimated value of Indicates h ri Estimated value of m ui Indicates the inertial mass of the ship in the forward direction; m ri Indicates the inertial mass in the direction of the ship's turning; T ui (·) represents the structural parameters of the propeller; F ri (·) represents the structural parameters of the servo; G i represents the auxiliary variable of the quantizer; ξ 1i Auxiliary variables representing event triggering mechanism; β ui The filtered variable of the virtual control law representing the propeller speed; β ri k represents the variable after filtering of the virtual control law of the ship's heading angle; uei represents the propeller control parameter; k rei Indicates the control parameters of the servo; u ei represents the speed error; r ei Indicates the steering speed error; represents the adaptive parameter λ related to the ship mass ui An estimated value of represents the adaptive parameter λ related to the ship speed ri The estimated value of Φ ui Represents the auxiliary variable of the neural network in the direction of forward speed; Φ ri represents the auxiliary variable of the neural network in the direction of bow turning speed; ui represents the adaptive parameter related to ship quality; ri represents the adaptive parameters related to ship speed;

[0096] Among them, the adaptive law of the adaptive parameter is:

[0097]

[0098] In the formula, Γ ui ,Γ ri ,Γ hui ,Γ hri ,k λui ,k λri ,k hui ,k hri are all design parameters greater than zero; Φ ui Represents the auxiliary variable of the neural network in the direction of forward speed; Φ rirepresents the auxiliary variable of the neural network in the direction of the bow turning speed; express The initial value of express The initial value of express The initial value of express The initial value of .

[0099] In order to verify the accuracy and effectiveness of the autonomous detection control scheme of the ship formation in this embodiment, two simulation cases were carried out on the numerical simulation platform: Simulation Case A is a collaborative path planning verification case of this embodiment, which is used to verify the deductive process of the collaborative autonomous detection task of heterogeneous ships under communication constraints; Simulation Case B is a comparative experiment between the control algorithm of this embodiment and the single-input quantization algorithm and the single-event trigger algorithm.

[0100] Simulation Case A:

[0101] In order to perform the task of collaborative path tracking of heterogeneous unmanned ships, this section selects four waypoints (W1 (0m, 0m), W2 (1000m, 50m), W3 (2420m, 1200m), W4 (3100m, 1300m)) to form the waypoint path. The controlled objects are three ships, of which the first ship is the leader ship, the second ship and the third ship are follower ships, respectively recorded as follower ship 1 and follower ship 2, and the initial states of the three ships are:

[0102] [x1(0),y1(0),ψ1(0),u1(0),v1(0),r1(0)]=[-130m,-20m,0°,3.5m / s,0m / s,0m / s];

[0103] [x2(0),y2(0),ψ2(0),u2(0),v2(0),r2(0)]=[-200m,-205m,0°,3.5m / s,0m / s,0m / s];

[0104] [x3(0),y3(0),ψ3(0),u3(0),v3(0),r3(0)]=[-100m,-280m,0°,3.5m / s,0m / s,0m / s];

[0105] The following sine and cosine interferences are selected:

[0106]

[0107] Figure 4-Figure 6 They are the simulation results of autonomous detection of intruding ships by heterogeneous unmanned ships in simulated marine environments. Figure 3Represents the trajectory curve of the collaborative path tracking of the heterogeneous unmanned ship formation. Figure 3 It can be seen that the reference path of the leader unmanned ship is planned according to the waypoint information, and further provides a navigation reference signal for the virtual unmanned ship; in addition, compared with the homogeneous unmanned ship formation system, the heterogeneous unmanned ship formation collaborative control algorithm of this embodiment can enable different types of unmanned ships to track the reference signal at the desired speed at the same time, and can realize autonomous detection of suddenly encountered intrusion targets. Figure 3 The figure shows the process of the close detection mission of two intrusion targets. Figure 4 , 5 The two figures show the position error and attitude error of the heterogeneous unmanned ship collaborative system. It can be found from the two figures that follower ship 1 and follower ship 2 have large errors in different sections. This is due to the sudden change in the position of the virtual ship when they complete the task and re-form a formation, and finally achieve effective tracking of the reference path. Figure 6 The position and attitude errors of the leader ship are shown. Figure 7 , 8 , 9 represent the control input of the heterogeneous unmanned ship collaborative system, where the unmanned ship control input T Qki The curve changes less frequently, indicating that the control algorithm proposed in this embodiment significantly reduces the execution frequency.

[0108] Simulation Case B:

[0109] In order to explore the superiority of the composite control algorithm of this embodiment, this section compares it with the single-input quantization control and single-event trigger control algorithms. Taking the same underactuated ship as the control object, three types of control are applied respectively, and three indicators of the trigger rule are displayed: trigger interval duration, average trigger interval duration, and the number of times the trigger interval duration exceeds one second. The final trigger effect is shown in Figure 2. Fig.10 and Fig.11a and Fig.11b As can be seen from the figure, the combined application of hysteresis quantizer and event trigger increases the trigger interval, reduces the number of control signal changes, greatly reduces the execution frequency of the actuator, and further reduces the degree of wear of the actuator, which is beneficial to the economy of ship navigation.

[0110] Combined with the existing technology, controller design and simulation test, this embodiment aims at the detection task requirements of intrusion targets at sea, and performs collaborative control on heterogeneous unmanned ship formations, which can build a connection between heterogeneous unmanned ships. This embodiment is based on hysteresis quantization-event trigger control input, and uses neural network functions and dynamic surface technology to deal with the structural uncertainty and excessive calculation problems in the heterogeneous unmanned ship collaborative system. Under the condition of ensuring acceptable control accuracy, it can effectively reduce the occupation of communication resources in the ship, reduce the actuator operation frequency, and thus reduce the wear of the actuator and servo system, thereby ensuring the economy of ship navigation. . The guidance and control algorithm proposed in this embodiment can realize the autonomous detection task requirements of the formation of heterogeneous unmanned ships, significantly play the advantages of each heterogeneous ship, and enable it to autonomously complete the detection of intrusion targets. Through the simulation experiment of cooperative path tracking of heterogeneous unmanned ships and the comparison experiment of triggering conditions, the superiority of the guidance strategy and control algorithm of this embodiment is verified. Heterogeneous unmanned ship formation navigation control is an important application in the complex unmanned field of the ocean, and has important application prospects in unmanned search and unmanned patrol in the ocean.

[0111] In summary, this embodiment has two main features:

[0112] 1) In the control algorithm, the hysteresis quantizer can first discretize the continuous signal to reduce the occupancy of communication resources on board. The quantized signal is then recoupled with the event trigger mechanism as the final output signal, which further reduces the execution frequency of the actuator, significantly reduces the wear of the actuator, and extends its service life.

[0113] 2) Aiming at the needs of maritime autonomous detection missions, an improved L2-VS guidance algorithm based on artificial potential field mechanism is proposed, which can realize the autonomous approach detection of intrusion targets by sub-ships when heterogeneous ship formations are sailing. For the instability that may be caused by the introduction of hysteresis quantizer and event trigger strategy, an adaptive parameter for quantization trigger is designed to offset the adverse effects, further improving the stability and robustness of the system, which has important practical significance for the autonomous execution of navigation missions by heterogeneous ship formations.

[0114] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements 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 autonomous detection and control of heterogeneous ship formations with a quantitative trigger mechanism, characterized in that: The steps include: S1: Establish a nonlinear system model of the unmanned ship considering the uncertainty of the system model; S2: Establishing an L2 virtual ship of the leader ship, so as to establish dynamic virtual ships of the ships in the ship formation according to the improved L2-VS guidance algorithm, wherein the dynamic virtual ships include the dynamic virtual ship of the leader ship and the dynamic virtual ships of the follower ships; S3: establishing a gravitational function of the invading target to the dynamic virtual ship of the follower ship, so as to obtain the heading angle of the follower ship under the action of the artificial potential field according to the dynamic virtual ship of the follower ship; S4: according to the heading angle of the follower ship under the action of the artificial potential field, obtaining the position error between the ship and the dynamic virtual ship, so as to establish a virtual control law of the heading angle of the ship and a virtual control law of the propeller speed; S5: Introducing dynamic surface control technology, according to the virtual control law of the ship heading angle and the virtual control law of the propeller speed, obtaining the variable filtered by the virtual control law of the propeller speed and the variable filtered by the virtual control law of the ship heading angle; S6: Establish an event quantization trigger mechanism based on a hysteresis quantizer to obtain propeller control input and steering gear control input according to the variables filtered by the virtual control law of the propeller speed and the virtual control law of the bow angle and the nonlinear system model of the unmanned ship, so as to realize autonomous detection and control of heterogeneous ship formations.

2. According to the method of autonomous detection and control of heterogeneous ship formations with a quantitative trigger mechanism according to claim 1, it is characterized in that: In S6, the event quantization trigger mechanism based on the hysteresis quantizer is established as follows: First, obtain the quantized steering command as follows: Where: Q i (δ) represents the quantized steering order of the i-th ship; δ j represents the auxiliary variable of the quantizer, where δ j =ρ 1-j δ min ,j=1,2,3…, j represents the quantization level; ρ=(1-κ) / (1+κ) represents the quantization density; δ is the control signal; κ is the quantization level, κ belongs to (0,1); |δ| represents the absolute value of δ; represents the first derivative of δ; δ min is the artificially set quantization dead zone, which is a positive number; δ(t - ) indicates the steering order at the last moment; Q i (δ(t - )) represents the quantized steering order at the last moment; Secondly, according to the quantized signal, the trigger error is obtained to establish an event quantization trigger mechanism as follows: Where: Indicates event trigger error; T Qki is the quantized steering signal after the event is triggered; inf{} represents the lower limit function; b δ Indicates event triggering auxiliary variable; d δ represents a positive constant; where b δ ,d δ Satisfied: 0 δ ≤1,d δ >0; k represents the simulation step length; r represents the steering rate of the rudder angle; t represents the time variable; represents the time of the k-th simulation step; Indicates T Qki exist The value of the moment.​ 3. The method for autonomous detection and control of heterogeneous ship formations with a quantitative trigger mechanism according to claim 1 is characterized in that: In S1, the nonlinear system model of the unmanned ship is established as follows: in, Where: x i represents the coordinate of the ith ship on the x-axis; y i represents the coordinate of the i-th ship on the y-axis; ψ i represents the heading angle of the i-th ship; u i represents the forward speed of the ith ship; v i represents the transverse drift speed of the i-th ship; r i represents the turning rate of the i-th ship; i represents the index number of the ship; f ui (u) represents the nonlinear term of the moment of the ship model in the forward direction; f vi (v) represents the nonlinear term of the moment of the ship model in the drift direction; f ri (r) represents the nonlinear term of the moment of the ship model in the bow turning direction; m ui Indicates the inertial mass of the ship in the forward direction; m vi Indicates the inertial mass of the ship in the transverse drift direction; m ri Indicates the inertial mass in the direction of the ship's turning; d wui Indicates the interference in the ship's forward direction; d wvi Indicates the disturbance in the ship's transverse drift direction; d wri Indicates the disturbance in the ship's steering direction; T ui (·) represents the structural parameters of the propeller; F ri (·) represents the structural parameters of the servo; T Qki It is the quantized steering command signal after the event is triggered; n i Indicates the rotational speed of the ship system.

4. The method for autonomous detection and control of heterogeneous ship formations with a quantitative trigger mechanism according to claim 1 is characterized in that: In S2, the L2 virtual ship of the leader ship is established as follows: r d =u d / R Where: x d Indicates the horizontal coordinate of the position of the L2 virtual ship; y d represents the vertical coordinate of the position of the L2 virtual ship; ψ d Indicates the heading angle of the L2 virtual ship; u d represents the forward speed of the L2 virtual ship; r d represents the yaw angular velocity of the L2 virtual ship; represents the first-order derivative; R is the length of the ship.

5. The method for autonomous detection and control of heterogeneous ship formations with a quantitative trigger mechanism according to claim 1 is characterized in that: In S2, the dynamic virtual ship of the ship is established as follows: The dynamic virtual ship model of the ship is established as follows: Where: x vi Indicates the horizontal coordinate of the position of the dynamic virtual ship; y vi Represents the vertical coordinate of the dynamic virtual ship's position; ψ vi Indicates the heading angle of the dynamic virtual ship; u vi Indicates the forward speed of the dynamic virtual ship; r vi Indicates the bow angular velocity of the dynamic virtual ship; When i=1, the ship is the leader ship. Based on the improved L2-VS guidance algorithm, we get Where: r v1 is the turning rate of the first dynamic virtual ship, that is, the turning rate of the dynamic virtual ship of the leader ship; u v1 Indicates the forward speed of the first dynamic virtual ship, that is, the forward speed of the leader's dynamic virtual ship; η is the auxiliary angle of the improved L2-VS guidance algorithm; η1 is the angle between the dynamic virtual ship and the L2 virtual ship; ψ v1 represents the heading angle of the first dynamic virtual ship, that is, the heading angle of the leader's dynamic virtual ship; |ψ v1 |denotes ψ v1 The absolute value of; L is the distance between the L2 virtual ship and the dynamic virtual ship; x d Indicates the horizontal coordinate of the position of the L2 virtual ship; y d Indicates the vertical coordinate of the position of the L2 virtual ship; x v1 The horizontal coordinate of the dynamic virtual ship position of the leader ship; y v1 The vertical coordinate of the dynamic virtual ship representing the leader ship; R is the length of the ship; When i≠1, the ship is a follower ship. At this time, Where: di represents the expected distance between the dynamic virtual ship of the follower ship and the dynamic virtual ship of the leader ship; di Represents the desired angle between the dynamic virtual ship of the follower ship and the dynamic virtual ship of the leader ship.

6. The method for autonomous detection and control of heterogeneous ship formations with a quantitative trigger mechanism according to claim 1 is characterized in that: In S3, the heading angle of the follower ship under the action of the artificial potential field is obtained as follows: S31: Establish the gravity function of the invasion target to the dynamic virtual ship of the mission follower ship as follows: In the formula, F att F is the gravitational function of the invasion target on the follower dynamic virtual ship; attp is the position gravity; F attv is the velocity gravity; The unit vector of the position of the mission virtual ship pointing to the invasion target; K is the velocity unit vector of the mission virtual ship pointing to the invasion target; p , K v are gravitational coefficients; ρ pg is the auxiliary variable of gravitational distance; ρ vg is the auxiliary variable of gravitational velocity; x g The horizontal coordinate of the unknown ship position; y g The ordinate of the unknown ship's position; v xg represents the speed of the unknown ship in the x direction; v yg represents the speed of the unknown ship in the y direction; S32: Obtain the heading angle of the follower ship under the action of the artificial potential field as follows: ψ v =arctan(F att ) Where: v It represents the heading angle of the follower dynamic virtual ship under the action of the artificial potential field.

7. The method for autonomous detection and control of heterogeneous ship formations with a quantitative trigger mechanism according to claim 1 is characterized in that: In S4, the method of establishing the virtual control law of the ship heading angle and the virtual control law of the propeller speed is as follows: S41: The position error between the ship and the dynamic virtual ship is obtained as follows: Where: x ei is the position error in the x-axis direction; y ei is the position error in the y-axis direction; ψ ei Indicates the heading angle error; z ei represents the position error; ρ PG is the set gravity distance threshold; S42: According to the position error between the ship and the dynamic virtual ship, the virtual control law of the ship's heading angle and the virtual control law of the propeller speed are established as follows: Where: α ri represents the virtual control law of the ship's heading angle; α ui A virtual control law representing the propeller speed; represents the rudder angle control parameter; k zei Indicates position control parameters.

8. The method for autonomous detection and control of heterogeneous ship formations with a quantitative trigger mechanism according to claim 1 is characterized in that: In S5, the formula used to obtain the variable of the virtual control law filtered by the propeller speed and the variable of the virtual control law filtered by the ship heading angle is as follows: Where: ε ui ,ε ri are all time constants greater than zero; β ui The filtered variable of the virtual control law representing the propeller speed; β ri represents the variable after filtering of the virtual control law of the ship's heading angle; β ui (0) indicates β ui The initial value of α ui (0) indicates α ui The initial value of α ri (0) indicates α ri The initial value of β ri (0) indicates β ri The initial value of .

9. The method for autonomous detection and control of heterogeneous ship formations with a quantitative trigger mechanism according to claim 1 is characterized in that: In S6, the method for obtaining the propeller control input and the steering gear control input is as follows: make: h ui =m ui / T ui (·) h ri =m ri / (F ri (·)G i (1+ξ 1i )), but Where: N ui Indicates propeller control input; N ri Indicates the servo control input; n i Indicates the rotation speed of the ship system; δ i represents the rudder order of the i-th ship; h ui represents the adaptive parameters related to the hysteresis quantizer; h ri represents the adaptive parameters related to the parameters of the event triggering mechanism; τ ui represents the propeller auxiliary control input; τ ri Indicates the auxiliary control input of the servo; Indicates h ui An estimated value of Indicates h ri Estimated value of m ui Indicates the inertial mass of the ship in the forward direction; m ri Indicates the inertial mass in the direction of the ship's turning; T ui (·) represents the structural parameters of the propeller; F ri (·) represents the structural parameters of the servo; G i represents the auxiliary variable of the quantizer; ξ 1i Auxiliary variables representing event triggering mechanism; β ui The filtered variable of the virtual control law representing the propeller speed; β ri k represents the variable after filtering of the virtual control law of the ship's heading angle; uei represents the propeller control parameter; k rei Indicates the control parameters of the servo; u ei represents the speed error; r ei Indicates the steering speed error; represents the adaptive parameter λ related to the ship mass ui An estimated value of represents the adaptive parameter λ related to the ship speed ri The estimated value of Φ ui Represents the auxiliary variable of the neural network in the direction of forward speed; Φ ri represents the auxiliary variable of the neural network in the direction of bow turning speed; ui represents the adaptive parameter related to ship quality; ri Represents the adaptive parameters related to ship speed; in, In the formula, Γ ui ,Γ ri ,Γ hui ,Γ hri ,k λui ,k λri ,k hui ,k hri are all design parameters greater than zero; Φ ui Represents the auxiliary variable of the neural network in the direction of forward speed; Φ ri represents the auxiliary variable of the neural network in the direction of the bow turning speed; express The initial value of express The initial value of express The initial value of express The initial value of .

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