CN114756029A - Unmanned ship model-free control method based on dynamic event triggering - Google Patents

Unmanned ship model-free control method based on dynamic event triggering Download PDF

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CN114756029A
CN114756029A CN202210410554.3A CN202210410554A CN114756029A CN 114756029 A CN114756029 A CN 114756029A CN 202210410554 A CN202210410554 A CN 202210410554A CN 114756029 A CN114756029 A CN 114756029A
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usv
dynamic event
dynamic
unmanned ship
sliding mode
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CN114756029B (en
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张磊
郑宇鑫
黄子玚
应燕青
唐玥琪
杜祥
易广傑
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Harbin Engineering University
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Abstract

The invention discloses an unmanned ship model-free control method based on dynamic event triggering, which belongs to the technical field of unmanned ship control and specifically comprises the following steps: establishing a USV kinematics and dynamics model, and converting the USV kinematics and dynamics model into an Euler-Lagrange equation; designing a control law and an adaptive law by utilizing a sliding mode variable structure control and an Euler-Lagrange equation to construct a dynamic event trigger controller, wherein a control instruction is updated only when a trigger condition is met; and defining a Lyapunov candidate function to perform stability analysis on the dynamic event trigger controller, and meanwhile, proving that the Zeno phenomenon does not exist. The method overcomes the dependence of the traditional controller on a system model, improves the robustness of the system, avoids frequent controller signal updating, and obviously reduces the calculation cost, the loss of an actuating mechanism and the energy consumption.

Description

Unmanned ship model-free control method based on dynamic event triggering
Technical Field
The invention relates to the technical field of unmanned ship control, in particular to a model-free controller combining sliding mode variable structure control and a self-adaptive algorithm and a dynamic event trigger mechanism.
Background
As an autonomous surface mobile intelligent platform, an Unmanned Surface Vessel (USV) has wide and important functions in military and civil fields, such as hydrographic and geographic survey, marine search, and various war and non-war military missions. The trajectory tracking control is taken as an important guarantee for the USV to complete various tasks, and attracts the attention of numerous scholars in various countries. However, in practical applications, the complexity of the marine environment and the strongly coupled non-linearity of the dynamics system make the design of USV trajectory tracking controllers extremely challenging. Despite these challenges, researchers have made extensive efforts to do so, proposing sliding mode variable structure control, back-stepping control, fault-tolerant control, predictive performance control, fuzzy control, and the like.
In practical engineering applications, the control methods described above have a common disadvantage in that they require accurate USV model parameters. However, in the absence of a precise measurement instrument, it is difficult to accurately obtain the model parameters of the USV. In order to improve the control performance under uncertain dynamics, a control algorithm based on a neural network with a pervasive approximation characteristic is widely researched, and in the parameter identification process, a neural node weight matrix is compressed into a norm of the weight matrix by using a minimum parameter learning method, so that the calculation complexity is effectively reduced. Although the above-described methods improve transient and steady-state performance of the USV control system to some extent, these methods still require some model parameters, either directly or indirectly. In order to better maintain the robustness of the system, further research into the USV trajectory tracking controller without the need for model parameters is needed.
During actual sailing of the USV, the control signals are generally updated by means of time sampling. In such a communication mode, in order to ensure the stability and effectiveness of the system, a small sampling period is generally set, however, a high sampling frequency causes frequent updating of the controller, which results in problems of actuator loss and energy waste, and in most cases, when the system tends to be stable, frequent data updating is not needed to maintain the performance of the system. In view of the above problems, an event trigger mechanism is proposed, which is a control strategy for sampling and updating the sampling interval, i.e. data update and transmission only when the predefined event in the event trigger control is true. It is noted that the design of event-triggered control requires elimination of the Zeno phenomenon, which otherwise would make the corresponding control action impossible to perform, and even cause system instability. Note that the event-triggered control strategies referred to in the above work are all derived under static event-triggered conditions. With such a design, communication costs can be effectively reduced when static triggering conditions are not easily met, but as the threshold becomes smaller and smaller, events are frequently triggered, thereby causing unnecessary triggering transients. Therefore, more flexible event triggering conditions need to be developed to further reduce the signal update frequency of the controller.
Disclosure of Invention
The present invention is directed to solving, at least in part, one of the technical problems in the related art.
Therefore, the invention aims to provide a model-free control method of the unmanned ship based on dynamic event triggering, which overcomes the dependence of the traditional controller on a system model, improves the robustness of the system, avoids frequent controller signal updating, and obviously reduces the calculation cost, the loss of an actuating mechanism and the energy consumption.
In order to achieve the above object, an embodiment of the present invention provides a method for controlling an unmanned ship model-free system based on dynamic event triggering, including the following steps: step S1, building USV kinematics and dynamics model, and converting the USV kinematics and dynamics model into Euler-Lagrange equation; step S2, designing a control law and an adaptive law by using a sliding mode variable structure control and the Euler-Lagrange equation to construct a dynamic event trigger controller; and step S3, defining a Lyapunov candidate function to perform stability analysis on the dynamic event trigger controller, and simultaneously proving that the Zeno phenomenon does not exist.
According to the unmanned ship model-free control method based on dynamic event triggering, the model-free controller combining sliding mode variable structure control and a self-adaptive algorithm is adopted, so that the unmanned ship has high robustness, and the problems of parameter uncertainty and external disturbance when the unmanned ship executes a track tracking task are solved; meanwhile, a dynamic event trigger mechanism is provided, and a control instruction can be updated only when a trigger condition is met, so that the problems of actuator abrasion and energy waste caused by frequent control input of the unmanned ship due to the trigger mechanism in the conventional time are solved, and the calculation cost, the actuator loss and the energy consumption are greatly reduced.
In addition, the unmanned ship model-free control method based on dynamic event triggering according to the above embodiment of the present invention may further have the following additional technical features:
further, in one embodiment of the present invention, the USV kinematic and kinetic model is:
Figure RE-GDA0003698517490000021
Figure RE-GDA0003698517490000022
wherein,
Figure RE-GDA0003698517490000023
is a position vector of the USV, including the position [ x, y]TAnd the heading
Figure RE-GDA0003698517490000024
v＝[u,v,r]TThe velocity vector of the USV comprises a forward velocity u, a transverse drift velocity v and a yawing angular velocity r; τ ═ τ [ τ ]u,τv,τr]TThrust and moment vectors of the USV are shown; tau isb＝[τbu,τbv,τbr]TThe USV external interference vector is obtained;
Figure RE-GDA0003698517490000025
m, C (v), D (v) are respectively a transformation matrix, a mass inertia matrix, a Coriolis centripetal matrix and a hydrodynamic damping matrix between an inertial coordinate system and a satellite coordinate system.
Further, in one embodiment of the present invention, the euler-lagrange equation is:
Figure RE-GDA0003698517490000026
wherein M isQ、CQ、DQ、
Figure RE-GDA0003698517490000027
Respectively representing a mass inertia matrix, a Coriolis centripetal matrix, a hydrodynamic damping matrix and an USV external interference vector under an Euler-Lagrange equation, wherein eta is a current USV position vector, and J is a conversion matrix between an inertial coordinate system and a satellite coordinate system.
Further, in an embodiment of the present invention, the step S2 specifically includes: step S201, a sliding mode switching function is designed by using sliding mode variable structure control and the Euler-Lagrange equation; step S202, designing a control law and an adaptive law through the sliding mode switching function; step S203, a dynamic variable is proposed based on the Euler-Lagrange equation; step S204, assume the first trigger time is t 1And when the dynamic variable is 0, obtaining a trigger time sequence as the dynamic event trigger controller by introducing the dynamic variable.
Further, in an embodiment of the present invention, the sliding mode switching function is:
Figure RE-GDA0003698517490000031
wherein s is a synovial membrane switching function,
Figure RE-GDA0003698517490000032
Figure RE-GDA0003698517490000033
is USV track tracking error, eta is current USV position vector, etadPosition vector, k, expected for USV1Is a 3 x 3 tuning diagonal matrix.
Further, in an embodiment of the present invention, the control law and the adaptive law are:
Figure RE-GDA0003698517490000034
Figure RE-GDA0003698517490000035
Figure RE-GDA0003698517490000036
Figure RE-GDA0003698517490000037
wherein k is1、k2、a1、a2、a3、a4、a5、a6、μ1、μ2And mu3Are all normal numbers, and are all positive numbers,
Figure RE-GDA0003698517490000038
and
Figure RE-GDA0003698517490000039
in order for the parameters to be unknown,
Figure RE-GDA00036985174900000310
are respectively
Figure RE-GDA00036985174900000311
And
Figure RE-GDA00036985174900000312
tau is the control rate, J is the transformation matrix between the inertial and satellite coordinate systems,
Figure RE-GDA00036985174900000313
derivative of the current USV position vector, s (t)k) Is tkAnd (4) a sliding mode switching function corresponding to the moment.
Further, in one embodiment of the present invention, the dynamic variable is:
Figure RE-GDA00036985174900000314
wherein, ω (0)>0，β>0，λ∈[0,1]α ∈ 0,1), ω (t) is a function of ω with respect to time t, β is a dynamic event triggering parameter,
Figure RE-GDA00036985174900000315
and
Figure RE-GDA00036985174900000316
in order for the parameters to be unknown,
Figure RE-GDA00036985174900000317
are respectively
Figure RE-GDA00036985174900000318
And
Figure RE-GDA00036985174900000319
s (t) is tkA sliding mode switching function of time, eta is the current USV position vector, es(t)＝s(tk) S (t) is a dynamic event trigger function, tkTo trigger the time, k 2Is a known normal number.
Further, in an embodiment of the present invention, the trigger time sequence is:
Figure RE-GDA0003698517490000041
Figure RE-GDA0003698517490000042
wherein t is an arbitrary time, tkFor the time of triggering, θ is a normal number, k2Is a known normal number, es(t) is a dynamic event trigger function,
Figure RE-GDA0003698517490000043
and
Figure RE-GDA0003698517490000044
in order for the parameters to be unknown,
Figure RE-GDA0003698517490000045
are respectively
Figure RE-GDA0003698517490000046
And
Figure RE-GDA0003698517490000047
with η being the current USV position vector, ω (t) being a function of ω at time t, β being an event trigger parameter, λ ∈ [0,1 ∈ []，α∈0,1)。
Additional aspects and advantages of the invention will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the invention.
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The foregoing and/or additional aspects and advantages of the present invention will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:
FIG. 1 is a flow chart of a method for model-less control of an unmanned vehicle based on dynamic event triggering according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of an inertial and satellite coordinate system of one embodiment of the present invention;
FIG. 3 is a block diagram of a dynamic event trigger based model-free adaptive control system according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of USV trajectory tracking according to one embodiment of the present invention;
FIG. 5 is an actuator control input τ of one embodiment of the present inventionrSchematic representation, wherein (a) is τ in three casesdXIn the case of (b) is τ in three casesdYIn the case of (c) is τ in three casesdNA change in (c);
FIG. 6 is a diagram of estimated variables for one embodiment of the present invention, where (a) is the three cases
Figure RE-GDA0003698517490000048
In the case of (b) being in three cases
Figure RE-GDA0003698517490000049
In three cases, (c) is
Figure RE-GDA00036985174900000410
A change in (c);
FIG. 7 is a dynamic variable diagram of one embodiment of the present invention;
FIG. 8 is a diagram illustrating USV triggering times and trigger time intervals under dynamic event triggering conditions, where (a) is case 1, (b) is case 2, (c) is case 3, and (d) is a comparison of communication times, according to an embodiment of the present invention.
Detailed Description
Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the drawings are illustrative and intended to be illustrative of the invention and are not to be construed as limiting the invention.
The unmanned ship model-free control method based on dynamic event triggering according to the embodiment of the invention is described below with reference to the accompanying drawings.
Fig. 1 is a flowchart of an unmanned surface vehicle model-less control method based on dynamic event triggering according to an embodiment of the present invention.
As shown in fig. 1, the unmanned ship model-free control method based on dynamic event triggering includes the following steps:
in step S1, USV kinematic and kinetic models are established and converted into euler-lagrange equations.
Specifically, the embodiment of the invention only considers the horizontal motion of the USV, the inertial coordinate system OXY and the following coordinate system ObXbYbThe kinematic and kinetic models can be simplified as shown in fig. 2:
Figure RE-GDA0003698517490000051
Figure RE-GDA0003698517490000052
in the formula:
Figure RE-GDA0003698517490000053
position vector representing USV, containing position [ x, y ]]TAnd the heading
Figure RE-GDA0003698517490000054
v＝[u,v,r]TThe velocity vector of the USV comprises a forward velocity u, a transverse drift velocity v and a yawing angular velocity r; τ ═ τ [ τ ]u,τv,τr]TRepresenting thrust and moment vectors of the USV; tau isb＝[τbu,τbv,τbr]TRepresenting an USV external interference vector;
Figure RE-GDA0003698517490000055
m, C (v), D (v) respectively represent a transformation matrix, a mass inertia matrix, a Coriolis centripetal matrix and a hydrodynamic damping matrix between an inertial coordinate system and a satellite coordinate system, and the specific expressions are as follows:
Figure RE-GDA0003698517490000056
Figure RE-GDA0003698517490000057
for simplicity, J, C, D is adopted in the embodiment of the invention
Figure RE-GDA0003698517490000058
C(v)、D(v)。
Assume 1 that the model parameters J and are present and bounded, and further that the first derivative of J and is bounded. Thus, there is a normal number J 1And J2Satisfies the following conditions:
Figure RE-GDA0003698517490000059
Figure RE-GDA00036985174900000510
hypothesis 2 model parameters M, C (v), D (v), and
Figure RE-GDA00036985174900000511
is bounded, i.e.:
‖M‖≤γ1,‖C(v)‖≤γ2‖v‖,
‖D(v)‖≤γ3‖v‖,
Figure RE-GDA00036985174900000512
suppose 3 time-varying external interference τbIs bounded, i.e. there is a normal number
Figure RE-GDA00036985174900000513
Satisfy the requirements of
Figure RE-GDA00036985174900000514
Wherein
Figure RE-GDA00036985174900000515
Is an unknown variable.
Assume reference trajectory η of 4USVdIs second order conductive and satisfies | ηd‖<η0、
Figure RE-GDA00036985174900000516
And
Figure RE-GDA00036985174900000517
wherein eta isiAnd i is 1,2,3 is a normal number.
For the design of a follow-up self-adaptive model-free trajectory tracking controller, a system kinematics and dynamics model is converted into an Euler-Lagrange equation, which is expressed as:
Figure RE-GDA00036985174900000518
wherein M isQ＝J-TMJ-1；
Figure RE-GDA00036985174900000519
DQ＝J-TDJ-1，
Figure RE-GDA00036985174900000520
MQ、CQ、 DQ、
Figure RE-GDA00036985174900000521
Respectively representing a mass inertia matrix, a Coriolis centripetal matrix, a hydrodynamic damping matrix and an USV external interference vector under an Euler-Lagrange equation, wherein eta is a current USV position vector, and J is a conversion matrix between an inertial coordinate system and a satellite coordinate system.
In step S2, a control law and an adaptive law are designed using the sliding mode variable structure control and the euler-lagrange equation to construct a dynamic event triggered controller.
Further, in an embodiment of the present invention, the step S2 specifically includes:
step S201, a sliding mode switching function is designed by using sliding mode variable structure control and the Euler-Lagrange equation;
step S202, designing a control law and an adaptive law through the sliding mode switching function;
Step S203, a dynamic variable is proposed based on the Euler-Lagrange equation;
step S204, suppose the first triggering time is t1And when the dynamic variable is 0, obtaining a trigger time sequence as the dynamic event trigger controller by introducing the dynamic variable.
Specifically, based on the model criterion, the control target can be expressed as:
and (3) controlling the target: at external disturbance τbUnder the influence condition, a self-adaptive control law tau is designed, the problem of USV model-free parameter trajectory tracking control is solved, and the position of the USV is converged to an expected position, namely:
Figure RE-GDA0003698517490000061
wherein,
Figure RE-GDA0003698517490000062
representing the USV track tracking error; Δ is a normal number.
It should be noted that, as shown in fig. 3, in order to achieve the control objective, the embodiment of the present invention proposes the scheme, and firstly proposes a sliding mode variable structure controller, and effectively alleviates the buffeting phenomenon through a hyperbolic tangent function; then, a dynamic event trigger mechanism is used for adjusting the USV data interaction frequency, so that communication resources are saved; finally, it turns out that the tracking error is always finally bounded and that the Zeno phenomenon is absent.
Compared with a control mechanism depending on model parameters, the embodiment of the invention provides a control strategy without model parameters by utilizing the properties of sliding mode variable structure control and an Euler-Lagrange system, and the USV model can still realize satisfactory performance despite the inherent highly-coupled nonlinear characteristic. The method comprises the following specific steps:
Firstly, a sliding mode switching function s is designed as follows:
Figure RE-GDA0003698517490000063
wherein s is a synovial membrane switching function,
Figure RE-GDA0003698517490000064
Figure RE-GDA0003698517490000065
is USV track tracking error, eta is current USV position vector, etadPosition vector, k, expected for USV1Is a 3 x 3 tuning diagonal matrix.
In case 1-4 is true, the above formula is derived and combined to give:
Figure RE-GDA0003698517490000066
for convenience, the following parameters are defined:
Figure RE-GDA0003698517490000067
Figure RE-GDA0003698517490000068
Figure RE-GDA0003698517490000069
substituting the above equation, it can be further described as:
then there are:
Figure RE-GDA0003698517490000071
wherein,
Figure RE-GDA0003698517490000072
Figure RE-GDA0003698517490000073
Figure RE-GDA0003698517490000074
it can be seen that
Figure RE-GDA0003698517490000075
Unknown to the designer. For the control target, the embodiment of the invention estimates the unknown parameters by designing an adaptive law.
According to the above analysis, the control law and the adaptive law are designed as follows:
Figure RE-GDA0003698517490000076
Figure RE-GDA0003698517490000077
Figure RE-GDA0003698517490000078
Figure RE-GDA0003698517490000079
wherein k is1、k2、a1、a2、a3、a4、a5、a6、μ1、μ2And mu3Are all normal numbers, and are all positive numbers,
Figure RE-GDA00036985174900000710
and
Figure RE-GDA00036985174900000711
in order for the parameters to be unknown,
Figure RE-GDA00036985174900000712
are respectively
Figure RE-GDA00036985174900000713
And
Figure RE-GDA00036985174900000714
tau is the control rate, J is the transformation matrix between the inertial and satellite coordinate systems,
Figure RE-GDA00036985174900000715
derivative of the current USV position vector, s (t)k) Is tkAnd (4) a sliding mode switching function corresponding to the moment.
The dynamic event triggered error function is defined as a1
es(t)＝s(tk)-s(t)
Wherein, tkIndicating the moment of trigger.
A dynamic variable omega (t) is proposed for a USV Euler-Lagrange system:
Figure RE-GDA00036985174900000716
wherein, ω (0)>0；β>0；λ∈[0,1](ii) a α ∈ 0,1), ω (t) is a function of ω with respect to time t, β is a dynamic event triggering parameter,
Figure RE-GDA00036985174900000717
And
Figure RE-GDA00036985174900000718
is unknownThe number of the first and second groups is counted,
Figure RE-GDA00036985174900000719
are respectively
Figure RE-GDA00036985174900000720
And
Figure RE-GDA00036985174900000721
s (t) is tkA sliding mode switching function of time, eta is the current USV position vector, es(t)＝s(tk) S (t) is a dynamic event trigger function, tkTo trigger the time, k2Known as normal.
Suppose the first trigger time is t1When 0, the time sequence is triggered by introducing a dynamic variable ω (t)
Figure RE-GDA00036985174900000722
Can be designed as follows:
Figure RE-GDA0003698517490000081
wherein t is any time, tkFor the trigger time, θ is a normal number, k2Known normal number, es(t) is a dynamic event trigger function,
Figure RE-GDA0003698517490000082
and
Figure RE-GDA0003698517490000083
in order for the parameters to be unknown,
Figure RE-GDA0003698517490000084
are respectively
Figure RE-GDA0003698517490000085
And
Figure RE-GDA0003698517490000086
is estimated value ofEta is the current USV position vector, omega (t) is a function of omega at time t, beta is an event triggering parameter, and lambda belongs to [0,1 ]]，α∈0,1)。
From the above can be derived
Figure RE-GDA0003698517490000087
Therefore, the method can obtain:
Figure RE-GDA0003698517490000088
in step S3, the lyapunov candidate function is defined to perform stability analysis on the dynamic event-triggered controller, and meanwhile, the Zeno phenomenon is proved to be absent.
The stability analysis process in the embodiment of the invention comprises the following steps:
defining the lyapunov function as:
Figure RE-GDA0003698517490000089
and substituting the upper derivative to obtain:
Figure RE-GDA0003698517490000091
according to unequal relation
Figure RE-GDA0003698517490000092
Wherein,
Figure RE-GDA0003698517490000093
0.2785, it can be further derived as:
Figure RE-GDA0003698517490000094
according to the Young's inequality
Figure RE-GDA0003698517490000095
And
Figure RE-GDA0003698517490000096
Figure RE-GDA0003698517490000097
obtaining:
Figure RE-GDA0003698517490000101
substituting the dynamic event to trigger the dynamic variable to obtain:
Figure RE-GDA0003698517490000102
Order to
Figure RE-GDA0003698517490000103
Obtaining:
Figure RE-GDA0003698517490000104
in the formula:
Figure RE-GDA0003698517490000105
Figure RE-GDA0003698517490000106
therefore, the pose error of the USV can be converged to a small area near zero by adopting the control law and the self-adaptive law, and all signals in the system meet the global final consistency and the bounding property, so that the certification is finished.
Further, the Zeno phenomenon proves to be absent in the dynamic event-triggered control system, as follows:
it is assumed that the Zeno phenomenon exists, i.e. a normal number T exists0Satisfy limt→+∞tk＝T0。
Order to
Figure RE-GDA0003698517490000111
From the limiting nature, there is a positive integer N (ε)0) Satisfies the following conditions:
Figure RE-GDA0003698517490000112
from the above, it follows that sufficient conditions to guarantee the inequality are:
Figure RE-GDA0003698517490000113
according to the Lyapunov stability verification, a normal number gamma exists, and at any triggering time tkAll satisfy
Figure RE-GDA0003698517490000114
Then one sufficient condition that the above inequality holds is to be found:
Figure RE-GDA0003698517490000115
finally, it can be found that:
Figure RE-GDA0003698517490000116
in contradiction to the above, the Zeno phenomenon is therefore absent.
The effectiveness and robustness of the controller under different external interference environments are proved through simulation comparison experiments. The USV model parameters are shown in table 1. Control law and adaptive law parameter selection are shown in table 2. Initial state of USV is etaT＝[-2.1,-1.01,0]T，vT＝[0.01,0.01,0.01]T。
The USV reference trajectory is represented as follows:
Figure RE-GDA0003698517490000117
in the formula: t is1＝1.5π/ω；T2＝2/ω；ω＝0.04。
TABLE 1
Figure RE-GDA0003698517490000118
Figure RE-GDA0003698517490000121
TABLE 2
Figure RE-GDA0003698517490000122
For better proof robustness, the time-varying external interference is given by the following equation: case 1:
Figure RE-GDA0003698517490000123
Case 2:
Figure RE-GDA0003698517490000124
case 3:
Figure RE-GDA0003698517490000125
Figure RE-GDA0003698517490000131
the simulation results are shown in fig. 4-8:
FIG. 4 is a diagram of the trajectory tracking effect of the USV under different external disturbance conditions. The result shows that under the time-varying interference of three different conditions, the controller still has good tracking performance, and even under the condition that the interference amplitude is gradually increased from the condition one to the condition three, the USV can stably and quickly track the expected track.
Fig. 5 shows the control input signals of the USV. It can be seen that when the magnitude of the external disturbance becomes large, the control input is immediately adjusted and good robustness is maintained.
It can be seen from a review of fig. 6 that the adaptive estimation variables are bounded.
Fig. 7 depicts the time response curve of the dynamic variable, and we can see that the dynamic variable converges around zero around 40 s.
FIG. 8 illustrates the trigger time interval and number of triggers of the USV under dynamic event trigger conditions. It is evident that the USV saves more than 95% of communication resources under the dynamic event triggered communication mechanism. Therefore, in the USV trajectory tracking process, the communication frequency can be effectively reduced, the communication quantity between the controller and the actuator is reduced, and meanwhile, the closed-loop control performance is kept. Furthermore, from experiments we can also see that under the dynamic triggering law, there is no Zeno phenomenon.
According to the unmanned ship model-free control method based on dynamic event triggering, the model-free controller combines sliding mode variable structure control with a self-adaptive algorithm, so that the unmanned ship has strong robustness, and the problems of parameter uncertainty and external disturbance when the unmanned ship executes a track tracking task are solved; meanwhile, a dynamic event trigger mechanism is provided, and a control instruction can be updated only when a trigger condition is met, so that the problems of actuator abrasion and energy waste caused by frequent control input due to the trigger mechanism in the conventional time of the unmanned ship are solved, and the calculation cost, the actuator loss and the energy consumption are greatly reduced.
Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or to implicitly indicate the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of the feature. In the description of the present invention, "a plurality" means at least two, e.g., two, three, etc., unless explicitly specified otherwise.
In the description of the specification, reference to the description of "one embodiment," "some embodiments," "an example," "a specific example," or "some examples" or the like means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Moreover, various embodiments or examples and features of various embodiments or examples described in this specification can be combined and combined by one skilled in the art without being mutually inconsistent.
Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention, and that variations, modifications, substitutions and alterations can be made to the above embodiments by those of ordinary skill in the art within the scope of the present invention.

Claims (8)

1. A model-free control method of an unmanned ship based on dynamic event triggering is characterized by comprising the following steps:
Step S1, building USV kinematics and dynamics model, and converting the USV kinematics and dynamics model into Euler-Lagrange equation;
step S2, designing a control law and an adaptive law by using a sliding mode variable structure control and the Euler-Lagrange equation to construct a dynamic event trigger controller;
and step S3, defining a Lyapunov candidate function to perform stability analysis on the dynamic event trigger controller, and simultaneously proving that the Zeno phenomenon does not exist.
2. The unmanned boat model-free control method based on dynamic event triggering of claim 1, wherein the USV kinematic and kinetic models are:
Figure FDA0003603994550000011
Figure FDA0003603994550000012
wherein,
Figure FDA0003603994550000013
is a position vector of the USV, including the position [ x, y]TAnd the heading
Figure FDA0003603994550000014
v＝[u,v,r]TThe velocity vector of the USV comprises a forward velocity u, a transverse drift velocity v and a yawing angular velocity r; τ ═ τ [ τ ]u,τv,τr]TThrust and moment vectors of the USV are shown; tau isb＝[τbu,τbv,τbr]TThe USV external interference vector is obtained;
Figure FDA0003603994550000015
m, C (v), D (v) are respectively a transformation matrix, a mass inertia matrix, a Coriolis centripetal matrix and a hydrodynamic damping matrix between an inertial coordinate system and a satellite coordinate system.
3. The unmanned ship model-free control method based on dynamic event triggering of claim 1, wherein the Euler-Lagrangian equation is as follows:
Figure FDA0003603994550000016
Wherein, MQ、CQ、DQ、
Figure FDA0003603994550000017
Respectively representing a mass inertia matrix, a Coriolis centripetal matrix, a hydrodynamic damping matrix and an USV external interference vector under an Euler-Lagrange equation, wherein eta is a current USV position vector, and J is a conversion matrix between an inertial coordinate system and a satellite coordinate system.
4. The unmanned ship model-free control method based on dynamic event triggering according to claim 1, wherein the step S2 specifically comprises:
step S201, designing a sliding mode switching function by using sliding mode variable structure control and the Euler-Lagrange equation;
step S202, designing a control law and an adaptive law through the sliding mode switching function;
step S203, a dynamic variable is proposed based on the Euler-Lagrange equation;
step S204, assume the first trigger time is t1And when the dynamic variable is 0, obtaining a trigger time sequence as the dynamic event trigger controller by introducing the dynamic variable.
5. The unmanned ship model-free control method based on dynamic event triggering according to claim 4, wherein the sliding mode switching function is:
Figure FDA0003603994550000021
wherein s is a sliding mode switching function,
Figure FDA0003603994550000022
Figure FDA0003603994550000023
in order to be an USV track-following error,eta is the current USV position vector, etadPosition vector, k, expected for USV 1Is a 3 x 3 tuning diagonal matrix.
6. The unmanned ship model-free control method based on dynamic event triggering according to claim 4, wherein the control law and the adaptive law are as follows:
Figure FDA0003603994550000024
Figure FDA0003603994550000025
Figure FDA0003603994550000026
Figure FDA0003603994550000027
wherein k is1、k2、a1、a2、a3、a4、a5、a6、μ1、μ2And mu3Are all normal numbers, and are all positive numbers,
Figure FDA0003603994550000028
and
Figure FDA0003603994550000029
in order for the parameters to be unknown,
Figure FDA00036039945500000210
are respectively
Figure FDA00036039945500000211
And
Figure FDA00036039945500000212
tau is the control rate, J is the transformation matrix between the inertial and satellite coordinate systems,
Figure FDA00036039945500000213
derivative of the current USV position vector, s (t)k) Is tkAnd (4) a sliding mode switching function corresponding to the moment.
7. The unmanned ship model-free control method based on dynamic event triggering of claim 4, wherein the dynamic variables are:
Figure FDA00036039945500000214
wherein, ω (0)>0，β>0，λ∈[0,1]α ∈ 0,1), ω (t) is a function of ω with respect to time t, β is a dynamic event triggering parameter,
Figure FDA00036039945500000215
and
Figure FDA00036039945500000216
in order for the parameters to be unknown,
Figure FDA00036039945500000217
are respectively
Figure FDA00036039945500000218
And
Figure FDA00036039945500000219
s (t) is tkA sliding mode switching function of time, eta is the current USV position vector, es(t)＝s(tk) S (t) is a dynamic event trigger function, tkTo trigger the time, k2Known as normal.
8. The unmanned ship model-free control method based on dynamic event triggering of claim 4, wherein the triggering time sequence is as follows:
Figure FDA00036039945500000220
Figure FDA00036039945500000221
wherein t is any time, t kFor the time of triggering, θ is a normal number, k2Is a known normal number, es(t) is a dynamic event trigger function,
Figure FDA0003603994550000031
and
Figure FDA0003603994550000032
in order for the parameters to be unknown,
Figure FDA0003603994550000033
are respectively
Figure FDA0003603994550000034
And
Figure FDA0003603994550000035
with η being the current USV position vector, ω (t) being a function of ω at time t, β being an event trigger parameter, λ ∈ [0,1 ∈ []，α∈0,1)。
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