CN112445236B - Communication control method in event-triggered cooperative control of multiple unmanned aerial vehicles - Google Patents

Communication control method in event-triggered cooperative control of multiple unmanned aerial vehicles Download PDF

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CN112445236B
CN112445236B CN202011275021.6A CN202011275021A CN112445236B CN 112445236 B CN112445236 B CN 112445236B CN 202011275021 A CN202011275021 A CN 202011275021A CN 112445236 B CN112445236 B CN 112445236B
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uav
unmanned aerial
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trigger
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杨秀霞
张毅
方国伟
严瑄
高恒杰
于浩
王晨蕾
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Naval Aeronautical University
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    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
    • G05D1/10—Simultaneous control of position or course in three dimensions
    • G05D1/101—Simultaneous control of position or course in three dimensions specially adapted for aircraft
    • G05D1/104—Simultaneous control of position or course in three dimensions specially adapted for aircraft involving a plurality of aircrafts, e.g. formation flying
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D30/00—Reducing energy consumption in communication networks
    • Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks

Abstract

The invention discloses a communication control method in multi-unmanned aerial vehicle cooperative control based on event triggering, which comprises the following steps: parameter initialization, state quantity estimation during non-communication period, event trigger function calculation, judgment of whether a trigger condition is met, communication and state updating. The communication control method solves the problem that information among unmanned aerial vehicles is frequently updated in the process of multi-unmanned aerial vehicle formation cooperative control, and an event trigger function is designed only by utilizing state estimation information, so that the problem of communication and control updating among the unmanned aerial vehicles is converted into the value taking problem of a judgment trigger function, the complexity of an event trigger function algorithm is simplified, the working process of a trigger mechanism is more visual, and the method has higher actual engineering value.

Description

Communication control method in event-triggered cooperative control of multiple unmanned aerial vehicles
Technical Field
The invention belongs to the field of unmanned aerial vehicle formation control, mainly relates to a communication control method in a multi-unmanned aerial vehicle cooperative control process, and particularly relates to a communication control method in multi-unmanned aerial vehicle cooperative control based on event triggering.
Background
Unmanned Aerial Vehicle (UAV) formation control has been one of the hot issues of research. In both the formation process of the formation and the target tracking process, continuous communication and control updating are required to be kept between the UAVs to keep the formation between the UAVs, information between the UAVs is transmitted through a communication network, and the bandwidth and the computing resources of the communication network are very limited, so that how to reduce the pressure of communication between the UAVs in the formation target tracking process is also an urgent problem to be solved.
In order to overcome the pressure of continuous communication and control update among UAVs, trigger control methods based on fixed time have appeared, such as the documents "NOWZARI C, CORT S J, distributed event-distributed coordination for operating communication on weight-based digraphs [ J ]. automata, 2016,68: 237." and the documents "FAN Y, YANG Y, ZHANG Y, sampling-based event-distributed communication for multi-agent systems [ J ] neuro-serving, 2016,191: 141-. However, from the perspective of actual resource utilization, the periodic communication method still causes unnecessary resource waste to some extent.
In the foregoing context, an event-triggered control strategy is developed that determines whether to perform inter-UAV communication based on set event-triggered conditions. Such as the document "Chen Shi Ming, Sha." control theory and application based on fixed time consistency [ J ] of event triggered nonlinear multi-agent systems, 2019,36(10):1606- > 1614 ", which only uses the state of the last trigger time to determine the next trigger time during which no communication between neighboring UAVs is required, i.e. continuous communication between each other is avoided. However, event-triggered mechanisms may exhibit "Zeno behavior," i.e., an infinite number of event-triggered events occurring within a finite time. In the literature "YANG D, REN W, LIU X, et al, decentralized event-triggered sensors for linear multi-agent systems under general logical directed graphs [ J ]. Automatica,2016,69: 242-. The documents "XU W, HO D W, LI L, et al, event-triggered schemes on lead-following systems under differential protocols [ J ]. IEEE transactions on cybernetics,2015,47(1): 212) 223" respectively propose distributed, centralized and clustered event trigger structures for different topological structures based on the lead-Follower queuing structure, thereby realizing the following of the Follower by the Follower and reducing the frequency of control update, however, when designing the trigger function, the communication pressure is not relieved by adopting continuous adjacent UAV information.
In summary, to integrate the event trigger control strategy into the cooperative control problem of multiple UAV formation, the main difficulties to be solved are: (1) how to adopt proper information and design an event trigger function, thereby avoiding continuous communication and reducing the waste of communication resources as much as possible; (2) how to design the minimum trigger time interval avoids the "Zeno action" that may exist.
Disclosure of Invention
The invention aims to provide a communication control method in event-triggered cooperative control of multiple unmanned aerial vehicles, so that the communication pressure is relieved, and continuous communication is avoided; on the basis of the above, the possible occurrence of an infinite number of event triggering events within a limited time is further avoided, namely the possible occurrence of "Zeno behavior" is avoided.
The invention aims to solve the problem of communication control in cooperative control under the condition that a plurality of unmanned aerial vehicles are formed into a team and kept at a fixed height, so that the unmanned aerial vehicles can only be considered to move in a two-dimensional plane.
The invention provides a communication control method in event-triggered cooperative control of multiple unmanned aerial vehicles, which comprises the following steps:
step S1, parameter initialization
Describing formation of multiple drones as
Figure BDA0002778575230000021
Wherein
Figure BDA0002778575230000022
pi、viAnd uiRespectively representing UAVsiPosition, speed, and control inputs. In the case of a two-dimensional plane,
Figure BDA0002778575230000023
i belongs to {1,2, …, N }, N is the number of unmanned frames, UAV0Being virtual unmanned aerial vehicles, UAVsiKnowing UAV0The information of (a); UAV0A virtual drone that is not a real-existing drone but is set according to some algorithm; in order to make UAViKnown UAV0Including UAV0Position p of0Velocity v0And a control input u0) And each unmanned aerial vehicle adopts the same algorithm.
Step S2, estimating state quantity during no communication
Obtaining the state quantity x by estimationi(t) estimated value
Figure BDA0002778575230000024
Wherein
Figure BDA0002778575230000025
Figure BDA0002778575230000026
Is a UAViThe k-th trigger time of (c),
Figure BDA0002778575230000027
representing a UAViThe (k + 1) th trigger time of (c),
Figure BDA0002778575230000028
step S3, event trigger function calculation
Figure BDA0002778575230000029
In the formula, ei(t) is UAViThe error of the state measurement of (2),
Figure BDA00027785752300000210
is a UAViThe error of (a) is detected,
Figure BDA00027785752300000211
is an estimate of the error that is,
Figure BDA00027785752300000212
aijis a UAVjTo the UAViA coefficient of adjacency ofi0Is a UAV0To the UAViThe adjacency coefficient of (a); gain matrix K ═ BTP, and P is represented by the Riccati inequality ATP+PA-2αPBBTP+αI2n< 0 to obtain, wherein
Figure BDA00027785752300000213
ρ1And ρ satisfy the following condition: rho is more than 01< p, and
Figure BDA00027785752300000214
and λNIs the maximum eigenvalue of H, λ1Is the minimum eigenvalue of H, H ═ L + diag { a10,a20,…,aN0L is a Laplacian matrix;
step S4, judging whether the trigger condition is reached
Judging whether the triggering condition is satisfied
Figure BDA00027785752300000215
Wherein tau isiIn order to minimize the time-to-trigger interval,
Figure BDA00027785752300000216
for the time interval determined by the trigger function,
Figure BDA0002778575230000031
if the trigger condition is satisfied, go to step S5; if the trigger condition is not satisfied, go to step S2;
step S5, communication and status update
UAViSending the current state information to the adjacent unmanned aerial vehicle, and updating the state information x of the adjacent unmanned aerial vehiclei(t)。
Preferably, the specific method for estimating the state quantity in step S2 is as follows:
Figure BDA0002778575230000032
with respect to the document "YE Y, SU H, SUN Y. event-triggered consensus tracking for fractional-order multi-agent systems with general linear modules [ J]Neuroomputing, 2018,315:292-]Control and decision 2016,31(05):835 and 841 "using a zero order keeper as a state estimator, the estimation method of the present invention can obtain a more accurate estimation.
Preferably, τ in step S4iThe specific value taking method comprises the following steps:
0＜τi≤τ
wherein the content of the first and second substances,
Figure BDA0002778575230000033
ρ2satisfies the following conditions: rho is more than 02＜ρ，ρ1+ρ2≤ρ。
The communication control method in the event-triggered cooperative control of the multiple unmanned aerial vehicles provides a brand-new designed event triggering function used in the communication control, avoids continuous communication among the unmanned aerial vehicles, and greatly reduces the waste of communication resources; and adopts a brand new method to the state x during the period of no communicationi(t) estimating to obtain a more accurate estimated value, and laying a foundation for judging an event triggering condition; and a minimum trigger time interval tau is proposediThe possible "Zeno action" is avoided. In a word, the communication control method in event-triggered cooperative control of multiple unmanned aerial vehicles solves the problem that information among unmanned aerial vehicles is frequently updated in the process of formation cooperative control of multiple unmanned aerial vehicles, and an event trigger function is designed only by utilizing state estimation information, so that the problem of communication and control updating among unmanned aerial vehicles is converted into the value taking problem of a judgment trigger function, the complexity of an event trigger function algorithm is simplified, the working process of a trigger mechanism is more visual, and the method has higher actual engineering value.
Drawings
Fig. 1 is a flowchart of a communication control method in event-triggered cooperative control of multiple unmanned aerial vehicles;
FIG. 2 is a communication topology;
fig. 3 is a track of a multi-machine formation tracking target when ω is 0;
fig. 4 is a formation position error curve of a multi-machine formation tracking target when ω is 0;
fig. 5 is a formation speed error curve of a multi-machine formation tracking target when ω is 0;
fig. 6 is an event trigger distribution diagram of a multi-machine formation tracking target when ω is 0;
fig. 7 is a comparison of state estimation values of multi-machine formation tracking targets when ω is 0;
FIG. 8 is a track of a multi-machine formation tracking target when ω ≠ 0;
FIG. 9 is a formation position error curve of a multi-machine formation tracking target when ω ≠ 0;
FIG. 10 is a formation speed error curve of a multi-machine formation tracking target when ω ≠ 0;
FIG. 11 is an event trigger distribution diagram of a multi-machine formation tracking target when ω ≠ 0;
FIG. 12 is a comparison of the event trigger distribution of the present invention versus the literature method when ω is 0;
FIG. 13 is a comparison of event triggered profiles for the present invention and the comparative literature method when ω ≠ 0.
Detailed Description
The following describes an embodiment of the present invention with reference to fig. 1 to 13.
As shown in fig. 1, the communication control method in event-triggered cooperative control of multiple drones according to the present invention mainly includes 5 steps: parameter initialization, state quantity estimation during no communication, event trigger function calculation, judgment of whether a trigger condition is reached, communication and state updating.
The method comprises the following specific steps:
step S1, initializing parameters
Describing formation of multiple drones as
Figure BDA0002778575230000041
Wherein
Figure BDA0002778575230000042
pi、viAnd uiRespectively representing UAVsiThe position, speed and control inputs of the vehicle,
Figure BDA0002778575230000043
i belongs to {1,2, …, N }, N is the number of unmanned frames, UAV0Being virtual unmanned aerial vehicles, UAVsiCan obtainKnown UAV0The information of (a);
step S2, estimating state quantity during no communication
The state quantity x is obtained by estimationi(t) estimated value
Figure BDA0002778575230000044
Wherein
Figure BDA0002778575230000045
Figure BDA0002778575230000046
Is a UAViThe k-th trigger time of (c),
Figure BDA0002778575230000047
representing a UAViAt the (k + 1) th trigger time
Figure BDA0002778575230000048
The specific method for estimating the state quantity comprises the following steps:
Figure BDA0002778575230000049
step S3, event trigger function calculation
Figure BDA00027785752300000410
In the formula, ei(t) is UAViThe error of the state measurement of (2),
Figure BDA00027785752300000411
is a UAViThe error of (a) is detected,
Figure BDA00027785752300000412
is an estimate of the error that is,
Figure BDA00027785752300000413
aijis a UAVjTo UAViA coefficient of adjacency ofi0Is a UAV0To UAViThe adjacency coefficient of (a); gain matrix K ═ BTP, and P is represented by the Riccati inequality ATP+PA-2αPBBTP+αI2n< 0 to obtain, wherein
Figure BDA00027785752300000414
Where ρ is1And ρ satisfies: rho is more than 01< p, and
Figure BDA00027785752300000415
and λNIs the maximum eigenvalue of H, λ1Is the minimum eigenvalue of H, H ═ L + diag { a10,a20,…,aN0L is a Laplacian matrix;
the document "XU W, HO D W, LI L, et al. event-triggered schemes on lead-following sensing systems under differential policies [ J ]. IEEE transactions on cybernetics,2015,47(1): 212) and 223" requires continuous contiguous UAV information to satisfy the discrimination of event conditions. The event trigger function provided by the invention only needs to utilize the estimated value of the state of the UAV and the adjacent UAV, namely, the event trigger function only uses the state value of the trigger time.
To better illustrate the effectiveness of the event trigger function proposed by the present invention, it is demonstrated below.
Let ρ be present for the purpose of subsequent proof1,ρ2Rho, satisfies 0 < rho1,ρ2< rho and rho1+ρ2Rho is not more than. Consider a UAViThe event trigger time interval of
Figure BDA0002778575230000051
In the formula: tau isiIs the minimum trigger time interval as a constant to be designed;
Figure BDA0002778575230000052
a time interval determined for an event trigger function.
According to
Figure BDA0002778575230000053
It is known that the event trigger time ultimately depends on τiAnd
Figure BDA0002778575230000054
therefore, define the set of most recent event-triggered UAVs as M, respectively1(t) and M2(t) wherein M1(t) is composed of
Figure BDA0002778575230000055
The determined event triggers the UAV set, and M2(t) is fromiThe determined event triggers the UAV set, and both satisfy M1(t)∪M2(t)＝{1,2,…,N}，
Figure BDA00027785752300000517
Choosing a Lyapunov function as:
Figure BDA0002778575230000056
due to the fact that
Figure BDA0002778575230000057
Then the derivation of v (t) can result:
Figure BDA0002778575230000058
by
Figure BDA0002778575230000059
The following can be obtained:
Figure BDA00027785752300000510
according to the Young inequality:
Figure BDA00027785752300000511
thus, it is possible to obtain:
Figure BDA00027785752300000512
let inequality
Figure BDA00027785752300000513
In the formula:
Figure BDA00027785752300000514
the formula (2) can be transformed into:
Figure BDA00027785752300000515
then:
Figure BDA00027785752300000516
if equation (2) holds, then combine the Riccati inequality:
ATP+PA-2αPBBTP+αI2n＜0
taking into account coefficients
Figure BDA0002778575230000061
Namely, it is
Figure BDA0002778575230000062
Then equation (1) can be transformed into:
Figure BDA0002778575230000063
it is apparent that the following requirement proves that the formula (2) is established.
Figure BDA0002778575230000064
From the above formula, M1(t) one sufficient condition with respect to the formula (2) is:
Figure BDA0002778575230000065
when in use
Figure BDA0002778575230000066
When f is presenti(t) is less than or equal to 0. Then only need to ensure
Figure BDA0002778575230000067
It is ensured that the above equation is true, i.e. it is confirmed that equation (3) is true,
Figure BDA0002778575230000068
this is true. And (5) finishing the certification.
The above-described proof process proves when the event trigger function is
Figure BDA0002778575230000069
Stability of the system, i.e. at time intervals of
Figure BDA00027785752300000610
System stability in time.
Step S4, judging whether the trigger condition is reached
Judging whether the triggering condition is satisfied
Figure BDA00027785752300000611
Wherein τ isiFor a minimum trigger time interval, τiThe specific value taking method comprises the following steps: 0 < tauiTau is less than or equal to tau, in the formula,
Figure BDA00027785752300000612
Figure BDA00027785752300000613
and rho2Satisfies the following conditions: rho is more than 02＜ρ，ρ1+ρ2≤ρ；
Figure BDA00027785752300000614
For the time interval determined by the trigger function,
Figure BDA00027785752300000615
if the trigger condition is satisfied, go to step S5; if the trigger condition is not satisfied, go to step S2;
it is demonstrated below that the time interval is tauiThe system stability in time and the maximum settable trigger time interval τ to be solved. In addition, the above formula
Figure BDA00027785752300000616
The trigger function shown solves the problem of the document "XU W, HO D W, LI L, et al]IEEE transactions on cybernetics 2015,47(1):212-]Automatica,2016,69:242-249 ", the waste of information resources due to the non-use of contiguous UAV information.
To prove that the event trigger function of the present invention does not have "Zeno behavior", only the minimum trigger time interval τ needs to be provediWith a lower bound greater than 0.
Similarly to the above-mentioned proof, it is also necessary to prove that expression (2) is true, i.e. that expression (4) is true, but unlike the above-mentioned proof, here is for M2(t) for discussion.
To obtain τ, one sufficient condition for selecting equation (2), like equation (5), is:
Figure BDA0002778575230000071
for M2(t) in the case of (t),
Figure BDA0002778575230000072
since this is true, it is only necessary to prove that expression (6) is true.
For M2(t), one sufficient condition to give formula (6) is:
Figure BDA0002778575230000073
namely:
Figure BDA0002778575230000074
then, the interval of the event trigger time τiCan be described as being composed of
Figure BDA0002778575230000075
Increase from 0 to
Figure BDA0002778575230000076
Is determined.
Therefore, the following is sought
Figure BDA0002778575230000077
The lower time bound of (c), the derivation of which can be found:
Figure BDA0002778575230000078
by
Figure BDA0002778575230000079
The following can be obtained:
Figure BDA00027785752300000710
order to
Figure BDA00027785752300000711
Equation (8) can be described as:
Figure BDA00027785752300000712
for the formula (9), it satisfies ψ (t) ≦ φ (t, φ)0) Where phi (t, phi)0) Is the solution of the equation.
Figure BDA0002778575230000081
Solved to obtain
Figure BDA0002778575230000082
Then is composed of
Figure BDA0002778575230000083
Can be solved to obtain
Figure BDA0002778575230000084
Then for M2(t) when selecting the trigger time interval τiThe establishment of the formula (7) is ensured when τ is less than or equal to τ, that is, the establishment of the formulas (2) and (4) is ensured. From equation (10), τ > 0, i.e. the UAV is absent "Zeno behavior" at any initial value.
The above proof confirms that the trigger interval is
Figure BDA0002778575230000085
And τiSystem stability of the time, both of which ensure that the trigger interval is chosen to be
Figure BDA0002778575230000086
System stability in time.
Step S5, communication and status update
UAViSending the current state information to the adjacent unmanned aerial vehicle, and updating the state information x of the adjacent unmanned aerial vehiclei(t)。
In order to prove the feasibility and the superiority of the communication control method in event-triggered multi-drone collaborative control proposed by the present invention, the following is verified by tracking a target with 4 UAVs (i.e., N-4).
UAV was chosen in the following examplelAnd UAVbAs UAVs0，UAVlAnd UAVbThe method of determining and tracking the target of (2) adopts the method of CN111290440A and CN111414007A, and the communication topological relation between UAVs is shown in fig. 2.
Selecting 4 UAV initial positions (-500,0)Tm、(0,600)Tm、(100,-500)Tm and (500,200)Tm; initial speed of (0, -15)Tm/s、(-15,0)Tm/s、(10,-10)Tm/s and (15, -10)Tm/s；UAVlRespectively, are (0,0)TAnd (0,20)Tm/s；UAVbIs thetab(0) Is equal to 0, i.e. pb(0)＝(1,0)T，vb(0)＝(0,0)T，ub(0)＝(0,0)T(ii) a The scaling factor r is (100,100,100,100); rotation factor RiTheta in (1)iRespectively (pi, pi/2, 3 pi/2, 0); setting the target to do uniform linear motion with the initial position as (0,150)Tm, speed (-7,7)Tm/s。
Selecting rho as 0.24, rho1＝5/48，ρ 21/16, then ki0.0111, b is 0.0017, tau is 0.0455, and k is [0.01,0.01,0.01,0.01]，τ＝[0.04,0.04,0.04,0.04]And if alpha is 0.25, then solve the Riccati inequality ATP+PA-2αPBBTP+αI2n< 0 available:
Figure BDA0002778575230000091
further it can be calculated that:
Figure BDA0002778575230000092
the method provided by the invention is verified by whether the UAV formation does circling motion after tracking the upper target (i.e. whether omega is 0) or not, and the simulation time is set to be 30 s.
Example 1:
the UAV formation target tracking is performed when ω is 0, and simulation graphs of the multimachine formation target tracking are shown in fig. 3 to 7 when ω is 0.
FIG. 3 is a trajectory diagram of a tracking target for a UAV formation, in which UAVs can be observedlThe UAV can track the upper target, and meanwhile, the UAV can form a set formation and realize the tracking of the target, which shows the feasibility of the communication control method in the event-triggered cooperative control of the multiple UAVs, provided by the invention; fig. 4 and 5 are error curves of formation position and speed, respectively, which are about 10s or so, and the error curves both tend to 0, indicating that each unmanned aerial vehicle is at the UAV about 10s or solForm a preset formation around and follow the UAVlContinuing to track the target; fig. 6 shows an event trigger distribution diagram in the process of tracking a formation target in 0-4 s and 10-14 s, it is obvious that the influence of the existence of an event trigger mechanism on the number of times of communication between the unmanned aerial vehicles can be intuitively observed from the diagram, and in order to more intuitively explain the advantage of the communication control method of the present invention on the reduction of the number of times of communication between the unmanned aerial vehicles, the following comparison is made on the average trigger time interval with or without the trigger mechanism, as shown in table 1, it can be found that when the onboard information processing frequency of the unmanned aerial vehicle is 1000Hz, the number of times of communication between the unmanned aerial vehicles with the event trigger mechanism is far less than the case without the event trigger; fig. 7 is a comparison of the state estimate used herein and the state estimate generated using a zero-order keeper, and it is apparent that the state estimate used herein is more accurate than a zero-order keeper.
TABLE 1 time comparison of omega-0 with and without trigger mechanism
Figure BDA0002778575230000093
Note:
Figure BDA0002778575230000094
the decided number represents a number of times of triggering decided by the trigger function; tau isiThe number of times represents the number of triggers determined by the minimum trigger time interval.
Example 2:
UAV formation target tracking when omega is not equal to 0, and selecting the value of omega as omega1＝0.3rad/s，ω2The simulation results are shown in fig. 8 to 11 and table 2, respectively, at 0.8 rad/s.
As can be observed from the trajectory diagram of fig. 8, when ω ≠ 0, the communication control method in the event-triggered cooperative control of multiple drones, which is proposed by the present invention, is also feasible, and it can be found that the UAV starts hovering after forming a desired formation and continues to keep hovering around the target after tracking the upper target; in fig. 9 and 10, the error curves of the formation position and the speed tend to 0 in the vicinity of 10s, and at 13.5s, the curves both have small amplitude oscillation due to the speed adjustment after the formation tracks the target, but then tend to 0 again soon; the effect of the event trigger mechanism on reducing the number of communications can be observed in the trigger profile of fig. 11, and table 2 further demonstrates the significant effect of the event trigger mechanism on reducing the number of communications compared to reducing the number of communications.
TABLE 2 time comparison with and without trigger mechanism when ω ≠ 0
Figure BDA0002778575230000101
Comparing the simulation results in the two cases, it can be found that, under the same initial value, the time for the UAV formation to track the upper target is independent of whether to perform the circling motion, but depends on the UAVlThe time of the upper target is tracked. In addition, comparing table 1 and table 2, it can be seen that, in two cases, the decision item of the dominant event trigger is changed, the triggering times in embodiment 1 are determined by the trigger function, while embodiment 2 is determined by the designed minimum triggering time interval, and the difference between the two cases reflects the present inventionCompared with the method of fixed time triggering, the method of the invention meets the actual requirement better.
To further illustrate the superiority of the proposed method of the present invention, the following simulation comparisons were performed under the simulation conditions of examples 1 and 2 using the trigger functions in the documents "YANG D, REN W, LIU X, et al. The simulation results are shown in fig. 12, fig. 13, and table 3.
TABLE 3 temporal comparison of the trigger function using the above document
Figure BDA0002778575230000102
As can be seen from fig. 12, fig. 13 and table 3, compared to the method of the present invention, the average time interval of event triggers of the document "YANG D, REN W, LIU X, et al, decentralized event-triggered sensors for linear multi-agent systems under general direct graphs [ J ]. automation, 2016,69:242-249 ], is significantly shortened, especially when ω ≠ 0, it can be visually observed from fig. 13 that the frequency of event triggers at later stages is increased, which is mainly due to the fact that the minimum trigger time interval is not designed in the document.
The simulation result shows that the communication control method in the event-triggered cooperative control of the multiple unmanned aerial vehicles can effectively reduce the communication times among the UAVs, realize discontinuous communication and realize the tracking of the target.
Finally, it should be noted that the above-mentioned embodiments are only preferred embodiments of the present invention, and are not intended to limit the present invention, and although the present invention has been described in detail with reference to the foregoing embodiments, it will be apparent to those skilled in the art that modifications and equivalents can be made in the technical solutions described in the foregoing embodiments, or some technical features thereof can be replaced. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims (1)

1. A communication control method in multi-unmanned aerial vehicle cooperative control based on event triggering is characterized by comprising the following steps:
step S1, parameter initialization
Describing formation of multiple drones as
Figure FDA0003542017800000011
Wherein
Figure FDA0003542017800000012
pi、viAnd uiRespectively representing UAVsiThe position, speed and control inputs of the vehicle,
Figure FDA0003542017800000013
n is Unmanned Aerial Vehicle (UAV)0Being virtual unmanned aerial vehicles, UAVsiKnowing UAV0The information of (a);
step S2, estimating state quantity during no communication
Obtaining the state quantity x by estimationi(t) estimated value
Figure FDA0003542017800000014
Wherein
Figure FDA0003542017800000015
Figure FDA0003542017800000016
Is a UAViThe k-th trigger time of (c) is,
Figure FDA0003542017800000017
representing a UAViThe (k + 1) th trigger time of (c),
Figure FDA0003542017800000018
step S3, event trigger function calculation
Figure FDA0003542017800000019
In the formula, ei(t) is UAViThe error of the state measurement of (2),
Figure FDA00035420178000000110
is a UAViThe error of (a) is detected,
Figure FDA00035420178000000111
is an estimate of the error that is,
Figure FDA00035420178000000112
aijis a UAVjTo UAViA coefficient of adjacency ofi0Is a UAV0To the UAViThe adjacency coefficient of (a); gain matrix K ═ BTP, and P is represented by the Riccati inequality ATP+PA-2αPBBTP+αI2n< 0 to obtain, wherein
Figure FDA00035420178000000113
Where ρ is1And ρ satisfies: rho is more than 01< p, and
Figure FDA00035420178000000114
and λNIs the maximum eigenvalue of H, λ1Is the minimum eigenvalue of H, H ═ L + diag { a10,a20,…,aN0L is a Laplacian matrix;
step S4, judging whether the trigger condition is reached
Judging whether the triggering condition is satisfied
Figure FDA00035420178000000115
Wherein tau isiTo a minimumThe time interval of the triggering is such that,
Figure FDA00035420178000000116
for the time interval determined by the trigger function,
Figure FDA00035420178000000117
if the trigger condition is satisfied, go to step S5; if the trigger condition is not satisfied, go to step S2;
wherein τ isiThe specific value taking method comprises the following steps:
0＜τi≤τ
wherein the content of the first and second substances,
Figure FDA00035420178000000118
ρ2satisfies the following conditions: rho is more than 02＜ρ，ρ1+ρ2≤ρ；
Step S5, communication and status update
UAViSending the current state information to the adjacent unmanned aerial vehicle, and updating the state information x of the adjacent unmanned aerial vehiclei(t)。
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