CN113359812A - Unmanned aerial vehicle cluster control method and device and readable storage medium - Google Patents

Unmanned aerial vehicle cluster control method and device and readable storage medium Download PDF

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CN113359812A
CN113359812A CN202110508786.8A CN202110508786A CN113359812A CN 113359812 A CN113359812 A CN 113359812A CN 202110508786 A CN202110508786 A CN 202110508786A CN 113359812 A CN113359812 A CN 113359812A
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unmanned aerial
aerial vehicle
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CN113359812B (en
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赵彦杰
梁月乾
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Electronic Science Research Institute of CTEC
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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
    • Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T10/00—Road transport of goods or passengers
    • Y02T10/10—Internal combustion engine [ICE] based vehicles
    • Y02T10/40—Engine management systems

Abstract

The invention discloses an unmanned aerial vehicle cluster control method, an unmanned aerial vehicle cluster control device and a readable storage medium, wherein the method comprises the steps of establishing a corresponding topological structure according to a target arrangement formation and a communication relation between unmanned aerial vehicles; calculating gradient vectors corresponding to all unmanned aerial vehicles according to expected relative positions of the unmanned aerial vehicles on the nodes of the topological structure; determining the control law of the unmanned aerial vehicle according to the gradient vector; and controlling the corresponding unmanned aerial vehicle through the control law. The invention provides an unmanned aerial vehicle cluster formation control solution which has a uniform analytic form, meets the actual flight requirement and is easy to realize, and unmanned aerial vehicle clusters can be formed and flown according to an arbitrary time invariant formation.

Description

Unmanned aerial vehicle cluster control method and device and readable storage medium
Technical Field
The invention relates to the technical field of unmanned aerial vehicles, in particular to an unmanned aerial vehicle cluster control method and device and a readable storage medium.
Background
The existing unmanned aerial vehicle cluster control scheme can only carry out formation control aiming at a certain formation, and can not provide the formation control of a uniform form of a common formation.
Disclosure of Invention
The embodiment of the invention provides an unmanned aerial vehicle cluster control method, an unmanned aerial vehicle cluster control device and a readable storage medium, provides an unmanned aerial vehicle cluster formation control solution which has a uniform analytic form, meets actual flight requirements and is easy to realize, and can realize formation flight of unmanned aerial vehicle clusters according to any time invariant formation.
The embodiment of the invention provides an unmanned aerial vehicle cluster control method, which comprises the following steps:
establishing a corresponding topological structure according to the target arrangement formation and the communication relation between the unmanned aerial vehicles;
calculating gradient vectors corresponding to all unmanned aerial vehicles according to expected relative positions of the unmanned aerial vehicles on the nodes of the topological structure;
determining the control law of the unmanned aerial vehicle according to the gradient vector;
and controlling the corresponding unmanned aerial vehicle through the control law.
In an example, the establishing a corresponding topology according to the target formation and the communication relationship between the drones includes:
setting a communication relation between any two unmanned aerial vehicles with expected relative positions;
and establishing a corresponding topological structure according to the communication relation and the target formation, wherein the topological structure is a rigid topology.
In one example, the calculating a gradient vector corresponding to each drone according to the expected relative position of the drone on each node in the topology includes:
and calculating gradient vectors corresponding to the unmanned aerial vehicles according to the motion action weight value between the two unmanned aerial vehicles, the position difference and the speed difference between the unmanned aerial vehicles and the tracking target, and the position difference design parameters and the speed difference design parameters between the unmanned aerial vehicles and the tracking target.
In one example, the determining the control law of the drone from the gradient vector comprises:
calculating the pre-control law of the unmanned aerial vehicle according to the gradient vector;
and determining the control law of the unmanned aerial vehicle based on the pre-control law so that the control law meets the motion constraint of the unmanned aerial vehicle.
In one example, the determining the control law of the drone based on the pre-control law comprises:
determining a control law of the drone based on the pre-control law through a predefined saturation function.
The embodiment of the present invention further provides an unmanned aerial vehicle cluster control apparatus, including:
the topology construction module is used for establishing a corresponding topology structure according to the target arrangement formation and the communication relation between the unmanned aerial vehicles;
the data processing module is used for calculating gradient vectors corresponding to all unmanned aerial vehicles according to expected relative positions of the unmanned aerial vehicles on all nodes in the topological structure;
the controller construction module is used for determining the control law of the unmanned aerial vehicle according to the gradient vector;
and the control module is used for controlling the corresponding unmanned aerial vehicle through the control law.
The embodiment of the present invention further provides a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the steps of the unmanned aerial vehicle cluster control method are implemented.
According to the method, the corresponding gradient vectors of all unmanned aerial vehicles are calculated according to the expected relative positions of the unmanned aerial vehicles on the nodes of the topological structure, the control laws of the unmanned aerial vehicles are determined according to the gradient vectors, and the corresponding unmanned aerial vehicles are controlled through the control laws.
The foregoing description is only an overview of the technical solutions of the present invention, and the embodiments of the present invention are described below in order to make the technical means of the present invention more clearly understood and to make the above and other objects, features, and advantages of the present invention more clearly understandable.
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Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the invention. Also, like reference numerals are used to refer to like parts throughout the drawings. In the drawings:
FIG. 1 is a basic flow diagram of an embodiment of the present invention;
fig. 2 is a diagram illustrating an unmanned aerial vehicle cluster formation process according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of velocity and acceleration according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of a turn rate and a climb rate according to an embodiment of the present invention;
FIG. 5 is a schematic view of a steering angle and a climbing angle according to an embodiment of the present invention;
FIG. 6 is a diagram of the variation of the unmanned aerial vehicle control input value with time according to an embodiment of the present invention;
fig. 7 is a diagram illustrating a formation process of a cluster of unmanned aerial vehicles in case of the embodiment of the present invention;
FIG. 8 is a diagram illustrating velocity and acceleration according to an embodiment of the present invention;
FIG. 9 is a schematic diagram of a second example of a turn rate and climb rate according to the present invention;
FIG. 10 is a schematic diagram of a second steering angle and a climbing angle according to an embodiment of the present invention;
FIG. 11 is a diagram of the variation of the unmanned aerial vehicle control input value with time according to example two of the present invention;
fig. 12 is a diagram illustrating a formation process of a cluster of three unmanned aerial vehicles in an embodiment of the present invention;
FIG. 13 is a diagram illustrating three velocity and acceleration profiles according to an embodiment of the present invention;
FIG. 14 is a graph illustrating a third turn rate and a climb rate according to an embodiment of the present invention;
FIG. 15 is a schematic diagram of a third steering angle and a climbing angle according to an embodiment of the present invention;
fig. 16 is a graph of the time-dependent change in the three-robot control input values in accordance with an embodiment of the present invention.
Detailed Description
Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.
The embodiment of the invention provides an unmanned aerial vehicle cluster control method, which comprises the following specific steps as shown in figure 1:
s101, establishing a corresponding topological structure according to the target arrangement formation and the communication relation between the unmanned aerial vehicles.
In the example, each unmanned aerial vehicle in the unmanned aerial vehicle cluster is provided with a navigation module and can output position and speed information of the unmanned aerial vehicle; the execution unit is equipped to respond to the control input quickly.
The method can be applied to formation of unmanned aerial vehicle cluster formation, or the positions of partial unmanned aerial vehicles need to be changed in the flight process so as to change the unmanned aerial vehicle formation, and corresponding topological structures can be established according to the communication relation between the target formation and the unmanned aerial vehicles.
S102, calculating gradient vectors corresponding to all unmanned aerial vehicles according to expected relative positions of the unmanned aerial vehicles on the nodes of the topological structure.
In this example, the cluster is composed of N fixed-wing drones, and the three-degree-of-freedom point kinematics model with the inertia control link of the ith drone satisfies:
Figure BDA0003059425430000041
wherein p isi(t)＝[xi(t)，yi(t)，zi(t)]TFor the three-dimensional position, x, of the ith unmanned aerial vehicle in the selected rectangular coordinate system XYZ at the moment ti(t)、yi(t)、ziAnd (t) are three-dimensional coordinates of the ith unmanned aerial vehicle at the moment t respectively. Vi(t)、χi(t)∈(-π，π]、γi(t)∈[-π/2，π/2]Respectively the speed, steering angle, climbing angle and V of the ith unmanned aerial vehicle at the moment tci(t)、χci(t)、γciAnd (t) are control input values of speed, steering angle and climbing angle respectively. Tau isV、τχ、τγTime constants of the speed, the steering angle, and the climbing angle, respectively. Based on the speed vector of the ith unmanned aerial vehicle at the time tComprises the following steps:
vi(t)＝Vi(t)[cos(γi(t))cos(χi(t)),cos(γi(t))sin(χi(t)),sin(γi(t))]T
where the superscript T denotes transpose.
Let the expected relative positions of drone i and drone j be
Figure BDA0003059425430000051
In this example, the following variables were selected as control variables:
ui(t)＝[Vci(t),χci(t),γci(t)]T
in one example, the calculating a gradient vector corresponding to each drone according to the expected relative position of the drone on each node in the topology includes:
for each drone in the cluster, a gradient vector is calculated
Figure BDA0003059425430000052
Wherein the content of the first and second substances,
Figure BDA0003059425430000053
respectively representing the gradient value of the ith unmanned aerial vehicle on the three-dimensional coordinate at the moment t.
S103, determining the control law of the unmanned aerial vehicle according to the gradient vector.
According to gradient vector
Figure BDA0003059425430000054
Firstly, determining the pre-control law of the ith unmanned aerial vehicle, and further determining the final control law of the ith unmanned aerial vehicle.
And S104, controlling the corresponding unmanned aerial vehicle through the control law.
And finally, controlling the corresponding unmanned aerial vehicle through the control law of the ith unmanned aerial vehicle. Therefore, the control law of any unmanned aerial vehicle in the cluster can be obtained, and the unmanned aerial vehicle cluster is controlled.
In conclusion, the method provides a simple and feasible scheme for determining the formation control law of the unmanned aerial vehicle cluster, and the unmanned aerial vehicle cluster can fly in formation according to an arbitrary time-invariant formation.
In an example, the establishing a corresponding topology according to the target formation and the communication relationship between the drones includes:
setting a communication relation between any two unmanned aerial vehicles with expected relative positions;
and establishing a corresponding topological structure according to the communication relation and the target formation, wherein the topological structure is a rigid topology.
Specifically, a communication relationship exists between any two unmanned aerial vehicles with expected relative positions, and the communication relationship referred to in this example means that command communication or data communication exists between every two unmanned aerial vehicles with expected relative positions. The target topology in this example is a communication topology graph containing vertices and edges established from clustered drones. In order to form a stable formation of the clusters in this example, the topology is set to be a rigid topology.
In an example, the calculating the gradient vector corresponding to each drone includes:
and calculating gradient vectors corresponding to the unmanned aerial vehicles according to the motion action weight value between the two unmanned aerial vehicles, the position difference and the speed difference between the unmanned aerial vehicles and the tracking target, and the position difference design parameters and the speed difference design parameters between the unmanned aerial vehicles and the tracking target.
In this example, the gradient vector is calculated to satisfy:
Figure BDA0003059425430000061
wherein n isijSight line vector representing unmanned aerial vehicle i to unmanned aerial vehicle j
Figure BDA0003059425430000062
aijRepresenting the communication relationship between unmanned aerial vehicle i and unmanned aerial vehicle j
Figure BDA0003059425430000063
ρhThe communication relation between the unmanned aerial vehicle i and the unmanned aerial vehicle j is strong and weak, sigma represents a norm type, and r is the communication distance between the unmanned aerial vehicles.
Figure BDA0003059425430000064
Figure BDA0003059425430000071
Figure BDA0003059425430000072
Figure BDA0003059425430000073
Figure BDA0003059425430000074
The unmanned aerial vehicle cluster sets a tracking target while forming a team, the tracking target can be a real target or a virtual target, and the position and the speed of the tracking target at the moment t are p respectivelyt(t) and vt(t)。
In the above formula, cα1> 0 and cα2More than 0 are the weight of the inter-machine attraction/separation action and the velocity coincidence action, respectively, cγ1> 0 and cγ2> 0, respectively correspond to the position difference (p)t-pi) Sum velocity difference (v)t-vi) The design parameters of (1). Epsilon is more than 0 and less than 1, a is more than 0 and less than or equal to b,
Figure BDA0003059425430000075
Niis the set of all drones that have communication with the ith drone. d is the desired distance between the two machines, z is a general argument, | z |σRepresenting the sigma-norm of the generic argument z.
In one example, the determining the control law of the drone from the gradient vector comprises:
calculating the pre-control law of the unmanned aerial vehicle according to the gradient vector;
and determining the control law of the unmanned aerial vehicle based on the pre-control law so that the control law meets the motion constraint of the unmanned aerial vehicle.
In this example, the pre-control law of the drone is calculated according to the aforementioned gradient vectors, satisfying:
Figure BDA0003059425430000081
wherein
Figure BDA0003059425430000082
The pre-control laws of the speed, the steering angle and the climbing angle of the ith unmanned aerial vehicle are respectively.
In the present example, the speed v (t), the acceleration a (t), the steering rate ω, and the acceleration a (t) of each drone at each instant t1(t) climbing rate ω2(t) and the climbing angle γ (t) satisfy the following constraints, respectively:
Vmin≤V(t)≤Vmax
amin≤a(t)≤amax
ω1min≤ω1(t)≤ω1max
ω2min≤ω2(t)≤ω2max
γmin≤γ(t)≤γmax
wherein Vmin、amin、ω1min、ω2min、γminRespectively the minimum value V of the speed, the acceleration, the steering rate, the climbing rate and the climbing angle of the unmanned aerial vehiclemax、amax、ω1max、ω2max、γmaxThe maximum values of the speed, the acceleration, the steering rate, the climbing rate and the climbing angle of the unmanned aerial vehicle are respectively.
The control law of the unmanned aerial vehicle is determined based on the pre-control law in the present example, and the motion constraint of the unmanned aerial vehicle is met.
In one example, the determining the control law of the drone based on the pre-control law comprises:
determining a control law of the drone based on the pre-control law through a predefined saturation function.
According to the pre-control law and the motion constraint, in this example, the control law of the drone is further determined by a predefined saturation function, and the following conditions are satisfied:
Figure BDA0003059425430000083
Figure BDA0003059425430000091
Figure BDA0003059425430000092
wherein, Vci(t)、χci(t)、γciAnd (t) are respectively the control laws of the speed, the steering angle and the climbing angle of the ith unmanned aerial vehicle, namely control input values. σ t > 0 denotes the sampling time interval, max (z)1,z2) Function representation is taken as z1And z2Maximum value of (c), min (z)1,z2) Function representation is taken as z1And z2Sat () represents a defined saturation function satisfying:
Figure BDA0003059425430000093
finally through the control law, i.e. Vci(t)、χci(t)、γciAnd (t) controlling the corresponding unmanned aerial vehicle as a control input value.
In summary, the embodiments of the present invention consider a cluster composed of fixed-wing drones, and given expected relative positions between some drones, or given expected relative positions between some drones according to an expected formation of the cluster, and accordingly, control input values of speed, steering angle, and climbing angle are designed for each drone in the cluster by the method of the present embodiment, so that the cluster flies according to the expected relative positions between the drones or the expected formation of the cluster, so as to complete corresponding tasks. Therefore, the embodiment of the invention provides an unmanned aerial vehicle cluster formation control solution which has a uniform analytic form, meets the actual flight requirement and is easy to realize for the problem that the cluster performs formation flight according to a general formation, and the solution can enable the cluster to perform formation flight according to an arbitrary time invariant formation and meet the motion performance constraint of the actual fixed wing unmanned aerial vehicle.
The embodiment of the invention also provides an implementation case of the unmanned aerial vehicle cluster control method, and the unmanned aerial vehicle cluster in the implementation case is composed of 20 fixed-wing unmanned aerial vehicles. The motion constraints of the drone are shown in table 1.
Table 1 unmanned aerial vehicle motion constraints
Figure BDA0003059425430000094
Figure BDA0003059425430000101
Case one
In this case, it is desirable that clusters of drones form and maintain a horizontal formation. The formation process of the formation is shown in fig. 2-6, and it can be seen that the clusters finally form the desired formation. The change situation of the motion amount of each unmanned aerial vehicle along with time in the formation process is shown in fig. 3-5, and it can be seen that the motion constraints of the unmanned aerial vehicles are all satisfied; the change of the control input values of the speed, the steering angle and the climbing angle of each unmanned aerial vehicle along with the time of the unmanned aerial vehicle control law determined by the method of the invention is shown in figure 6.
Case two
In this case, it is desirable that clusters of drones form and maintain dart-type formation. The formation process of the formation is shown in fig. 7-11, and it can be seen that the clusters finally form the desired formation; the change situation of the motion amount of each unmanned aerial vehicle along with time in the formation process is shown in fig. 8-10, and it can be seen that the motion constraints of the unmanned aerial vehicles are all satisfied; the change over time of the speed, steering angle, and climb angle control input values (i.e., the control laws determined by the method of the present invention) of each drone is shown in fig. 11.
Case three
In this case, it is desirable for the drone clusters to form and maintain diamond formation. The formation process of the formation is shown in fig. 12-16, and it can be seen that the clusters finally form the desired formation; the change situation of the motion amount of each unmanned aerial vehicle along with time in the formation process is shown in fig. 13-15, and it can be seen that the motion constraints of the unmanned aerial vehicles are all satisfied; the change over time of the speed, steering angle, and climb angle control input values (i.e., the control laws determined by the method of the present invention) for each drone is shown in fig. 16.
In conclusion, the method is suitable for cluster formation control of time-invariant formation in any shape. Aiming at multiple motion constraints existing in the actual flight of the fixed-wing unmanned aerial vehicle, the method can simultaneously process a plurality of constraints. The invention provides an analytical expression of control input values of speed, steering angle and climbing angle. Because the control input value is an analytic expression, the control is easy to realize and the control cost is low.
The embodiment of the present invention further provides an unmanned aerial vehicle cluster control apparatus, including:
the topology construction module is used for establishing a corresponding topology structure according to the target arrangement formation and the communication relation between the unmanned aerial vehicles;
the data processing module is used for calculating gradient vectors corresponding to all unmanned aerial vehicles according to expected relative positions of the unmanned aerial vehicles on all nodes in the topological structure;
the controller construction module is used for determining the control law of the unmanned aerial vehicle according to the gradient vector;
and the control module is used for controlling the corresponding unmanned aerial vehicle through the control law.
The embodiment of the present invention further provides a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the steps of the unmanned aerial vehicle cluster control method are implemented.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solutions of the present invention may be embodied in the form of a software product, which is stored in a storage medium (such as ROM/RAM, magnetic disk, optical disk) and includes instructions for enabling a terminal (such as a mobile phone, a computer, a server, an air conditioner, or a network device) to execute the method according to the embodiments of the present invention.
While the present invention has been described with reference to the embodiments shown in the drawings, the present invention is not limited to the embodiments, which are illustrative and not restrictive, and it will be apparent to those skilled in the art that various changes and modifications can be made therein without departing from the spirit and scope of the invention as defined in the appended claims.

Claims (7)

1. An unmanned aerial vehicle cluster control method is characterized by comprising the following steps:
establishing a corresponding topological structure according to the target arrangement formation and the communication relation between the unmanned aerial vehicles;
calculating gradient vectors corresponding to all unmanned aerial vehicles according to expected relative positions of the unmanned aerial vehicles on the nodes of the topological structure;
determining the control law of the unmanned aerial vehicle according to the gradient vector;
and controlling the corresponding unmanned aerial vehicle through the control law.
2. The method of claim 1, wherein the establishing a corresponding topology according to the target formation and the communication relationship between the drones comprises:
setting a communication relation between any two unmanned aerial vehicles with expected relative positions;
and establishing a corresponding topological structure according to the communication relation and the target formation, wherein the topological structure is a rigid topology.
3. The method of cluster control of drones as recited in claim 2, wherein said calculating a gradient vector for each drone according to the expected relative position of the drone on the nodes of the topology comprises:
and calculating the gradient vector of each unmanned aerial vehicle according to the motion action weight value between the two unmanned aerial vehicles, the position difference and the speed difference between the unmanned aerial vehicle and the tracking target, and the position difference design parameter and the speed difference design parameter between the unmanned aerial vehicle and the tracking target.
4. A drone cluster control method according to any one of claims 1-3, characterized in that the determining of the control law of drones according to the gradient vectors comprises:
calculating the pre-control law of the unmanned aerial vehicle according to the gradient vector;
and determining the control law of the unmanned aerial vehicle based on the pre-control law so that the control law meets the motion constraint of the unmanned aerial vehicle.
5. The drone cluster control method of claim 4, wherein the determining the control law of the drone based on the pre-control law comprises:
determining a control law of the drone based on the pre-control law through a predefined saturation function.
6. An unmanned aerial vehicle cluster control device, its characterized in that includes:
the topology construction module is used for establishing a corresponding topology structure according to the target arrangement formation and the communication relation between the unmanned aerial vehicles;
the data processing module is used for calculating gradient vectors corresponding to all unmanned aerial vehicles according to expected relative positions of the unmanned aerial vehicles on all nodes in the topological structure;
the controller construction module is used for determining the control law of the unmanned aerial vehicle according to the gradient vector;
and the control module is used for controlling the corresponding unmanned aerial vehicle through the control law.
7. A computer-readable storage medium, characterized in that the computer-readable storage medium has stored thereon a computer program which, when being executed by a processor, carries out the steps of the drone cluster control method according to any one of claims 1 to 5.
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