CN114020042A - Heterogeneous unmanned cluster formation enclosure tracking control method and system - Google Patents

Heterogeneous unmanned cluster formation enclosure tracking control method and system Download PDF

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CN114020042A
CN114020042A CN202111530445.7A CN202111530445A CN114020042A CN 114020042 A CN114020042 A CN 114020042A CN 202111530445 A CN202111530445 A CN 202111530445A CN 114020042 A CN114020042 A CN 114020042A
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formation
leader
tracking
motion model
varying
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化永朝
董希旺
苏飘逸
于江龙
任章
吕金虎
翁哲鸣
张洪坤
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Beihang University
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Abstract

The invention relates to a heterogeneous unmanned cluster formation enclosure tracking control method and system. According to the method, a motion model of a tracking-leader is determined according to the macro motion state and bounded control input of a heterogeneous unmanned cluster system; constructing a distributed time-varying formation tracking controller according to the motion model of the tracking-leader, the state of the formation-leader, the communication topological relation and the time-varying output formation vector; constructing a distributed surround-tracking controller according to the state of the formation-leader and the state of the follower; constructing a formation-leader motion model according to the distributed time-varying formation tracking controller and the motion model of the tracking-leader; constructing a follower motion model according to the formation-leader motion model and the distributed surround-tracking controller; the invention realizes formation-enclosure tracking control of a heterogeneous unmanned cluster system with switching communication topology and unknown input of a leader.

Description

Heterogeneous unmanned cluster formation enclosure tracking control method and system
Technical Field
The invention relates to the field of cluster system cooperative control, in particular to a heterogeneous unmanned cluster formation surround tracking control method and system.
Background
The unmanned cluster cooperative control is widely concerned and emphasized at home and abroad in recent years, the task execution efficiency can be remarkably improved through cooperative complementation between heterogeneous unmanned platforms, and the unmanned cluster cooperative control has a wide application prospect in a plurality of task applications such as large-scale cooperative area search, cluster optimization scheduling and the like. In recent years, a large number of application tests are carried out in the aerospace field, such as unmanned plane swarm attack, multi-missile cooperative defense, multi-satellite cooperative detection and the like. However, the task type, the coordination mode and the coordination strategy of the existing unmanned cluster system are relatively simple, and an autonomous coordination control technology under a complex environment condition needs to be researched urgently.
Currently, the field of cluster system cooperative control has generated a plurality of closely related and focused research branches, including consistency control, formation control, enclosure control, and the like. In traditional closed control studies, it is generally assumed that there is no interaction or collaboration between multiple leaders. However, in practical application scenarios, the leader often needs to collaborate to maintain a specific time-varying formation and be able to track a reference track or a specific target to move in order to better meet the task requirements. For example, when a high-low-matching multi-missile system is cooperatively attacked, highly configured missiles are required to form a desired relative position relationship through cooperation, and meanwhile, the lowly configured missiles need to be capable of accurately falling into an attack area under the guidance of the highly configured missiles. In the scene, a more complex formation-enclosure tracking control problem occurs, different cooperative control targets in layers and cooperative coupling among layers exist in a cluster system, on one hand, multiple leaders are required to form a specific formation and track a reference track or target motion, and on the other hand, followers are required to enter the formation formed by the leaders. Therefore, the research on formation-enclosure tracking control of the unmanned cluster system not only has theoretical significance, but also has more practical engineering significance.
Existing cooperative control methods generally assume that the cluster system is homogeneous, i.e., all individuals in the cluster are required to have the same kinetic and kinematic models. However, the isomorphic cluster has the limitations of single intelligent emerging mode, weak cooperative capability and the like. The advantages of different unmanned systems such as unmanned aerial vehicles, unmanned vehicles and unmanned boats can be fully exerted by the cross-domain cooperation of heterogeneous clusters, and the multiplication of cluster intelligence is realized in a structural coupling and function complementation mode. However, at present, the research on formation control and enclosure control of the heterogeneous cluster system is still in a starting stage, and related research results are few. Meanwhile, under the influence of switching topology, the existing method is difficult to make the control error of the closed-loop system converge, so that the unmanned cluster system formation-enclosure control technology directly applied to switching topology needs to be broken through.
Disclosure of Invention
The invention aims to provide a heterogeneous unmanned cluster formation and enclosure tracking control method and system, which are used for realizing formation-enclosure tracking control of a heterogeneous unmanned cluster system with switching communication topology and unknown leader input.
In order to achieve the purpose, the invention provides the following scheme:
a heterogeneous unmanned cluster formation surround tracking control method comprises the following steps:
determining a tracking-leader, a formation-leader, and a follower from the heterogeneous unmanned cluster system; the tracking-leader generates a target signal tracked by the entire heterogeneous unmanned cluster system; the formation-leader and the follower are different types of agents in the heterogeneous unmanned cluster system respectively;
determining a motion model of a tracking-leader according to the macro motion state of the heterogeneous unmanned cluster system and bounded control input; the motion model of the tracking-leader is used for generating a reference track of the overall motion of the heterogeneous unmanned cluster system;
acquiring a communication topological relation of a heterogeneous unmanned cluster system; the union of the neighbor sets of all followers in the communication topological relation of the heterogeneous unmanned cluster system comprises all formation-leaders, and the action topologies of the followers are communicated; the action topology among the leaders is a spanning tree with a tracking-leader as a root node, and the action topology among the formation-leaders is undirected;
constructing a distributed time-varying formation tracking controller according to the motion model of the tracking-leader, the state of the formation-leader, the communication topological relation and the time-varying output formation vector; constructing a distributed surround-tracking controller according to the state of the formation-leader and the state of the follower;
constructing a formation-leader motion model according to the distributed time-varying formation tracking controller and the motion model of the tracking-leader; constructing a follower motion model according to the formation-leader motion model and the distributed surround-tracking controller;
tracking a reference trajectory of the tracking-leader using a formation-leader motion model time-varying formation;
the follower's output is converged into the convex hull of the formation-leader formation using a follower motion model.
Optionally, determining a motion model of the tracking-leader according to a macro motion state of the heterogeneous unmanned cluster system and a bounded control input, specifically including:
using formulas
Figure BDA0003410538520000031
Determining a motion model of the tracking-leader;
wherein,
Figure BDA0003410538520000032
the status of the track-leader is represented,
Figure BDA0003410538520000033
a control input representing a track-leader,
Figure BDA0003410538520000034
the output of the track-leader is represented,
Figure BDA0003410538520000035
is a matrix of constants, v0(t) is bounded, and r0(t)||Eta is less than or equal to eta, and eta is a constant.
Optionally, the constructing a distributed time-varying formation tracking controller according to the motion model of the tracking-leader, the state of the formation-leader, the communication topological relation, and the time-varying output formation vector specifically includes:
using the formula hyi(t)=Yihi(t) determining a time-varying output queuing vector;
using formulas
Figure BDA0003410538520000036
Determining a distributed time-varying formation tracking controller;
wherein,
Figure BDA0003410538520000037
denotes a formation parameter, i is 1,2, …, N denotes the number of formation-leaders,
Figure BDA0003410538520000038
representing the formation output matrix, hyi(t) is a time-varying output queuing vector,
Figure BDA0003410538520000039
representing the state of the formation-leader,
Figure BDA00034105385200000310
represents a pair v0Is determined by the distributed estimation of the time domain,
Figure BDA00034105385200000311
represents the adaptive control gain; tau isiRepresenting a time-varying convoy tracking compensation input,
Figure BDA00034105385200000312
μ denotes the normal number, K1i、Khi、K2i、ΥiAnd ΓiA matrix of gains is represented by a matrix of gains,
Figure BDA00034105385200000313
a non-negative weight is represented by a non-negative weight,
Figure BDA00034105385200000314
representing neighbor formation-leader j pairs v0Is calculated.
Optionally, the constructing a distributed time-varying formation tracking controller according to the motion model of the tracking-leader, the state of the formation-leader, the communication topology relationship, and the time-varying output formation vector further includes:
judging whether the time-varying output formation vector has compensation input or not;
if so, determining whether the compensation input satisfies a formula
Figure BDA00034105385200000315
If so, constructing a distributed time-varying formation tracking controller; if not, re-determining the time-varying output formation vector;
wherein,
Figure BDA0003410538520000041
representing a constant matrix, τi(t) represents the compensation input and,
Figure BDA0003410538520000042
a matrix of constants is represented by a matrix of constants,
Figure BDA0003410538520000043
denotes an external input, XhiRepresenting a constant matrix that satisfies the local regulator equation.
Optionally, said constructing a formation-leader motion model from a distributed time-varying formation tracking controller and a motion model of a tracking-leader; constructing a follower motion model according to a formation-leader motion model and a distributed surround-tracking controller, and specifically comprising the following steps of:
using formulas
Figure BDA0003410538520000044
Determining a formation-leader motion model and a follower motion model;
wherein,
Figure BDA0003410538520000045
and
Figure BDA0003410538520000046
respectively, the status, control inputs and outputs of the formation-leader i or follower i, i being 1,2, …, N + M, M being the number of followers,
Figure BDA0003410538520000047
Figure BDA0003410538520000048
is a matrix of constants.
Optionally, said constructing a formation-leader motion model from a distributed time-varying formation tracking controller and a motion model of a tracking-leader; constructing a follower motion model according to the formation-leader motion model and the distributed surround-tracking controller, and specifically further comprising:
using formulas
Figure BDA0003410538520000049
Determining that a formation-leader achieves a desired time-varying output formation tracking condition;
using formulas
Figure BDA00034105385200000410
Determining that the formation-leader and follower achieve a desired output bounding condition;
wherein, yi(t) is the output of the formation-leader i, i ═ 1,2, …, N, yk(t) output of follower k, ρk,jA non-negative constant of the number of the first,
Figure BDA00034105385200000411
k∈{N+1,N+2,…,N+M},j=1,2,…,N。
a heterogeneous unmanned cluster formation surround-track control system comprises:
the intelligent agent dividing module is used for determining a tracking-leader, a formation-leader and a follower according to the heterogeneous unmanned cluster system; the tracking-leader generates a target signal tracked by the entire heterogeneous unmanned cluster system; the formation-leader and the follower are different types of agents in the heterogeneous unmanned cluster system respectively;
the motion model determination module of the tracking-leader is used for determining the motion model of the tracking-leader according to the macro motion state of the heterogeneous unmanned cluster system and bounded control input; the motion model of the tracking-leader is used for generating a reference track of the overall motion of the heterogeneous unmanned cluster system;
the communication topological relation acquisition module is used for acquiring the communication topological relation of the heterogeneous unmanned cluster system; the union of the neighbor sets of all followers in the communication topological relation of the heterogeneous unmanned cluster system comprises all formation-leaders, and the action topologies of the followers are communicated; the action topology among the leaders is a spanning tree with a tracking-leader as a root node, and the action topology among the formation-leaders is undirected;
the controller construction module is used for constructing a distributed time-varying formation tracking controller according to the motion model of the tracking-leader, the state of the formation-leader, the communication topological relation and the time-varying output formation vector; constructing a distributed surround-tracking controller according to the state of the formation-leader and the state of the follower;
the motion model building module is used for building a formation-leader motion model according to the distributed time-varying formation tracking controller and the motion model of the tracking-leader; constructing a follower motion model according to the formation-leader motion model and the distributed surround-tracking controller;
a time-varying formation tracking module for tracking a reference trajectory of the tracking-leader by a time-varying formation using a formation-leader motion model;
and the enclosure control module is used for converging the output of the follower to a convex hull of the formation formed by the formation-leader by utilizing the follower motion model.
Optionally, the motion model construction module of the tracking-leader specifically includes:
a tracking-leader motion model determination unit for utilizing a formula
Figure BDA0003410538520000051
Determining a motion model of the tracking-leader;
wherein,
Figure BDA0003410538520000052
the status of the track-leader is represented,
Figure BDA0003410538520000053
a control input representing a track-leader,
Figure BDA0003410538520000054
the output of the track-leader is represented,
Figure BDA0003410538520000055
is a matrix of constants, v0(t) is bounded, and r0(t)||Eta is less than or equal to eta, and eta is a constant.
According to the specific embodiment provided by the invention, the invention discloses the following technical effects:
the invention provides a heterogeneous unmanned cluster formation encircling tracking control method and system, which are characterized in that each agent is divided into three types of tracking-leader, formation-leader and follower, the tracking-leader with time-varying input is adopted to generate an integral reference track of a cluster system or represent a non-cooperative target to be tracked, edge-based distributed observers are respectively designed for the formation-leader and the follower based on an adaptive control and sliding mode variable structure control theory, and finally a predefined encircling control strategy is utilized to ensure that the convergence target value of the follower does not depend on communication topology, thereby realizing formation-encircling tracking control of the heterogeneous unmanned cluster system with switching communication topology and unknown input of the leader.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without inventive exercise.
Fig. 1 is a schematic flow chart of a heterogeneous unmanned cluster formation surround tracking control method provided by the present invention;
FIG. 2 is a possible action topology;
fig. 3 is a screenshot of the position trajectory of the drone-drone vehicle system at t-30 s and at a given time t-0, 15,25,30 s;
FIG. 4 is a queue-leader output queue tracking error curve;
FIG. 5 is a follower output encircled error curve;
fig. 6 is a schematic structural diagram of a heterogeneous unmanned cluster formation surround tracking control system provided by the present invention.
The numbers in the figures illustrate the following:
five-pointed star: tracking-leader drone i ═ 0; rhombus, upper triangle, circle and right triangle: formation-leader drone i ═ 1,2,. 4; square: a follower unmanned vehicle i ═ 5, 6.. 10;
Figure BDA0003410538520000061
output of formation-leader Euclidean norm of formation tracking error
Figure BDA0003410538520000062
Euclidean norm of the follower's output bounding error
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The invention aims to provide a heterogeneous unmanned cluster formation and enclosure tracking control method and system, which are used for realizing formation-enclosure tracking control of a heterogeneous unmanned cluster system with switching communication topology and unknown leader input.
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in further detail below.
Fig. 1 is a schematic flow chart of a heterogeneous unmanned cluster formation encircling tracking control method provided by the present invention, and as shown in fig. 1, the heterogeneous unmanned cluster formation encircling tracking control method provided by the present invention includes:
s101, determining a tracking-leader, a formation-leader and a follower according to a heterogeneous unmanned cluster system; the tracking-leader generates a target signal tracked by the entire heterogeneous unmanned cluster system; the formation-leader and the follower are different types of agents in the heterogeneous unmanned cluster system respectively; tracking-the leader has no neighbors, the formation-leader's neighbors only include the leader, and the followers' neighbors are formation-leaders or other followers. Consider a higher-order heterogeneous unmanned cluster system consisting of N + M +1 agents, where i-0 represents a trail-leader, i-1, 2, …, N represents a formation-leader, i-N +1, N +2, …, and N + M represents a follower.
S102, determining a motion model of a tracking-leader according to the macro motion state and bounded control input of the heterogeneous unmanned cluster system; the motion model of the tracking-leader is used for generating a reference track of the overall motion of the heterogeneous unmanned cluster system;
s102 specifically comprises the following steps:
using formulas
Figure BDA0003410538520000071
Determining a motion model of the tracking-leader;
wherein,
Figure BDA0003410538520000072
the status of the track-leader is represented,
Figure BDA0003410538520000073
a control input representing a track-leader,
Figure BDA0003410538520000074
the output of the track-leader is represented,
Figure BDA0003410538520000075
is a matrix of constants, v0(t) is bounded, and r0(t)||Eta is less than or equal to eta, and eta is a constant.
S103, acquiring a communication topological relation of the heterogeneous unmanned cluster system; the union of the neighbor sets of all followers in the communication topological relation of the heterogeneous unmanned cluster system comprises all formation-leaders, and the action topologies of the followers are communicated; the action topology among the leaders is a spanning tree with a tracking-leader as a root node, and the action topology among the formation-leaders is undirected;
s103 specifically comprises the following steps:
communication topology availability map for heterogeneous unmanned clusters
Figure BDA0003410538520000081
It is shown that,
Figure BDA0003410538520000082
a set of nodes is represented that is,
Figure BDA0003410538520000083
a set of edges is represented that is,
Figure BDA0003410538520000084
representing having non-negative weight wijOf the adjacent matrix. Let epsilonij=(vi,vj) Representation diagram
Figure BDA0003410538520000085
In the slave node viTo node vjOne edge of (2). Weight wijIf > 0 and only if εjiE epsilon, otherwise w ij0. By using
Figure BDA0003410538520000086
Representing a node viIs selected. Drawing(s)
Figure BDA0003410538520000087
Is defined as
Figure BDA0003410538520000088
Wherein,
Figure BDA0003410538520000089
(i-1, 2, …, N) represents node viThe degree of entry of (c). Definition map
Figure BDA00034105385200000810
Is the Laplace matrix of
Figure BDA00034105385200000811
Considering the scenario that the cluster system has switching topology, subscripts of all possible action topologies are set as
Figure BDA00034105385200000812
Let [ t)l,tl+1) (l-0, 1,2 …) represents an infinite sequence of consistent bounded non-overlapping time intervals, where t isl+1-tl≥τdIs greater than 0. Action topology at time tl+1A handover occurs. Let σ (t) [ [0, ∞) → {1,2, …, z } denote a switching signal, which takes the value of the number in the current diagram. At time t, the action graph and the corresponding Laplace matrix are respectively recorded as
Figure BDA00034105385200000813
And
Figure BDA00034105385200000814
to ensure that each formation-leader can function in the enclosure control, the union of each follower neighbor set is required to contain all the formation-leaders. Assuming topology for any possible actions
Figure BDA00034105385200000815
Role topology between leaders
Figure BDA00034105385200000816
The method comprises the steps that a spanning tree with a tracking-leader as a root node is provided, and the acting topology between formation and leader is undirected; action topology between followers
Figure BDA00034105385200000817
Are connected. Will correspond to the figure
Figure BDA00034105385200000818
And
Figure BDA00034105385200000819
the Laplace matrices are respectively denoted as
Figure BDA00034105385200000820
And
Figure BDA00034105385200000821
can be divided into
Figure BDA00034105385200000822
At this time, it can be known
Figure BDA00034105385200000823
Is a positive definite matrix.
S104, according to the motion model of the tracking leader, the state of the formation leader, the communication topological relation and the time-varying output formation directionMeasuring, constructing a distributed time-varying formation tracking controller; constructing a distributed surround-tracking controller according to the state of the formation-leader and the state of the follower; that is, for the formation-leader (i ═ 1,2, …, N), a time-varying vector is used
Figure BDA00034105385200000824
Characterize its expected time-varying output formation, wherein hyi(t) (i ═ 1,2, …, N) is piecewise continuously conductible
For a formation-leader i (i ═ 1,2,. N), the desired time-varying output formation vector hyi(t) is generated by the following off-site system:
Figure BDA0003410538520000091
in the formula:
Figure BDA0003410538520000092
a parameter indicative of the formation parameter is,
Figure BDA0003410538520000093
which represents an external input, is presented,
Figure BDA0003410538520000094
a matrix of the formation status is represented,
Figure BDA0003410538520000095
a matrix of constants is represented by a matrix of constants,
Figure BDA0003410538520000096
represents a time-varying output queuing vector,
Figure BDA0003410538520000097
representing a formation output matrix. By bounded external input ri(t) to produce a more general type of time-varying formation, h is requiredi(t) is bounded.
Using formulas
Figure BDA0003410538520000098
Determining a distributed time-varying formation tracking controller;
wherein,
Figure BDA0003410538520000099
denotes a formation parameter, i is 1,2, …, N denotes the number of formation-leaders,
Figure BDA00034105385200000910
representing the formation output matrix, hyi(t) is a time-varying output queuing vector,
Figure BDA00034105385200000911
representing the state of the formation-leader,
Figure BDA00034105385200000912
represents a pair v0Is determined by the distributed estimation of the time domain,
Figure BDA00034105385200000913
represents the adaptive control gain; tau isiRepresenting a time-varying convoy tracking compensation input,
Figure BDA00034105385200000914
μ denotes the normal number, K1i、Khi、K2i、ΥiAnd ΓiA matrix of gains is represented by a matrix of gains,
Figure BDA00034105385200000915
a non-negative weight is represented by a non-negative weight,
Figure BDA00034105385200000916
representing neighbor formation-leader j pairs v0Is calculated.
Using formulas
Figure BDA00034105385200000917
Determining a distributed surround-track controller;
wherein,
Figure BDA00034105385200000918
Figure BDA00034105385200000919
Figure BDA00034105385200000920
representing the ith follower pair xj(j ∈ {1,2, …, N }) of distributed estimates,
Figure BDA00034105385200000921
(j ∈ {1,2, …, N }) and
Figure BDA00034105385200000922
(k ∈ { N +1, N +2, …, N + M }) represents an adaptive gain;
Figure BDA00034105385200000923
satisfy the requirement of
Figure BDA00034105385200000924
Non-negative constant ρ ofi,jRepresenting predefined weight values for determining a desired convex combination of multi-formation-leader outputs, K representing a normal number, K3i
Figure BDA0003410538520000101
Υi,jAnd Qi,jA gain matrix is represented.
S104 specifically further includes:
judging whether the time-varying output formation vector has compensation input or not;
if so, determining whether the compensation input satisfies a formula
Figure BDA0003410538520000102
If so, constructing a distributed time-varying formation tracking controller; if not, re-determining the time-varying output formation vector;
that is, if satisfied, adaptive parameters in a distributed time-varying convoy tracking controller
Figure BDA0003410538520000103
The update law of (j ∈ {0,1, …, N }) is:
Figure BDA0003410538520000104
in the formula: initial value
Figure BDA0003410538520000105
And is provided with
Figure BDA0003410538520000106
k is 1,2, …, N. Selecting mu with sufficient size to make mu larger than or equal to eta. Designing a gain matrix K1iSo that A isi+BiK1iIs Hurwitz, order Khi=Uhi-K1iXhi,K2i=Ui-K1iXiSelection upsiloniSo that BiΥi-XiE is 0. Let F bei=ΦiBiΥi,ΦiFor positive definite matrices, the following Lyapunov equation is satisfied: phii(Ai+BiK1i)+(Ai+BiK1i)TΦi=-Ini
The gain in the distributed surround-tracking controller for the follower i (i ═ N +1, …, N + M) is then adaptively designed. Adaptive parameters
Figure BDA0003410538520000107
(j ∈ {1,2, …, N }) and
Figure BDA0003410538520000108
the update law of (k ∈ { N +1, …, N + M }) is as follows:
Figure BDA0003410538520000109
in the formula: initial value of adaptive parameter
Figure BDA00034105385200001010
Is selected fullyLarge normality number κ satisfies
Figure BDA00034105385200001011
Wherein, thetaj(j ∈ {1,2, …, N }) represents the upper bound of the formation-leader j control input, i.e., | | | uj||≤θj. Similarly, the gain matrix K is designed3iSo that A isi+BiK3iIs Hurwitz, order
Figure BDA00034105385200001012
(j e {1,2, …, N }), selecting yi,j(j ∈ {1,2, …, N }) such that B isiΥi,j-Xi,jBjAnd 0 holds. Let Qi,j=PiBiΥi,j,PiRepresents a positive definite matrix satisfying the following Lyapunov equation:
Figure BDA00034105385200001013
wherein,
Figure BDA00034105385200001014
representing a constant matrix, τi(t) represents the compensation input and,
Figure BDA00034105385200001015
a matrix of constants is represented by a matrix of constants,
Figure BDA00034105385200001016
denotes an external input, XhiRepresenting a constant matrix that satisfies the local regulator equation.
S105, constructing a formation-leader motion model according to the distributed time-varying formation tracking controller and the motion model of the tracking-leader; constructing a follower motion model according to the formation-leader motion model and the distributed surround-tracking controller;
s105 specifically comprises the following steps:
using formulas
Figure BDA0003410538520000111
Determining a formation-leader motion model and a follower motion model;
wherein,
Figure BDA0003410538520000112
and
Figure BDA0003410538520000113
respectively, the status, control inputs and outputs of the formation-leader i or follower i, i being 1,2, …, N + M, M being the number of followers,
Figure BDA0003410538520000114
Figure BDA0003410538520000115
is a matrix of constants.
Wherein a constant matrix (X) is selectedi,Ui) (i ═ 1,2, …, N), such that the regulator equation
Figure BDA0003410538520000116
If true;
selecting a constant matrix (X)hi,Uhi) (i ═ 1,2, …, N), such that the regulator equation
Figure BDA0003410538520000117
This is true.
Selecting a constant matrix (X)i,j,Ui,j) (i N +1, …, N + M, j 1,2, …, N) such that the regulator equation
Figure BDA0003410538520000118
This is true.
S105 specifically further includes:
using formulas
Figure BDA0003410538520000119
Determining that a formation-leader achieves a desired time-varying output formation tracking condition;
using formulas
Figure BDA00034105385200001110
Determining that the formation-leader and follower achieve a desired output bounding condition;
wherein, yi(t) is the output of the formation-leader i, i ═ 1,2, …, N, yk(t) output of follower k, ρk,jA non-negative constant of the number of the first,
Figure BDA00034105385200001111
k∈{N+1,N+2,…,N+M},j=1,2,…,N。
if the time-varying output formation tracking and output enclosure control conditions are simultaneously met for any formation leader i (i belongs to {1,2, …, N }) and follower k (k belongs to { N +1, N +2, …, N + M }), the high-order heterogeneous cluster system is called to realize the expected output formation-enclosure tracking.
S106, tracking the reference track of the tracking-leader by utilizing a time-varying formation of a formation-leader motion model;
and S107, converging the output of the follower into a convex hull of the formation formed by the formation-leader by utilizing a follower motion model.
The formation-enclosure tracking control method is applied to an air-ground cooperative patrol application scene of a multi-unmanned aerial vehicle-unmanned vehicle heterogeneous system, a heterogeneous unmanned cluster system consisting of 4 unmanned aerial vehicles and 6 unmanned vehicles is considered, a tracking-leader i is 0 and represents an overall reference track of the heterogeneous multi-robot system, a formation-leader i is 1,2,3 and 4 represents a four-rotor unmanned aerial vehicle, and followers i are 5,6, … and 10 represent Mecanum wheel unmanned vehicles. The multiple unmanned aerial vehicles form expected formation tracking in the air, meanwhile, the multiple unmanned vehicles can converge into the projection of a convex hull formed by the multiple unmanned aerial vehicles on the ground, and the multi-robot system executes a cooperative patrol task in a formation-enclosure tracking mode. Since the height direction of a quad-rotor drone can be controlled individually, only the motion in the two-dimensional plane (X-Y plane) is considered in the following. Assuming that there is a switch in the active topology of the multi-robot system, all possible topologies are as shown in FIG. 2, with the active topology being
Figure BDA0003410538520000121
And
Figure BDA0003410538520000122
is switched once every 5s and has an initial active topology of
Figure BDA0003410538520000123
Consider the following tracking-leader model:
Figure BDA0003410538520000124
let its unknown control input be
r0(t)=[0.1cos(0.1t),0.1sin(0.1t)]T
Based on the inner and outer ring control architecture, the kinematics model of the quad-rotor drone in the outer loop (position-velocity loop) can be approximated, where
Figure BDA0003410538520000125
(i is 1,2,3,4), each
Figure BDA0003410538520000126
Using feedback linearization techniques, the kinematics model of a Mecanum wheel drone vehicle may also be approximated by (2), where Ai=02×2,Bi=I2,Ci=I2(i ═ 5,6, …, 10). The state variable of each unmanned aerial vehicle consists of position and speed, and the output is position; the status and output of each unmanned vehicle is indicative of position.
Four unmanned aerial vehicles are used as formation-leaders to carry out fixed-height flight at a specified height, namely, the unmanned aerial vehicles are controlled independently in the Z-axis direction. The drones are required to form a square formation in the X-Y plane, the expected output formation vector being represented as
Figure BDA0003410538520000127
Wherein h isy1=[-1,1]T,hy2=[1,1]T,hy3=[1,-1]T,hy4=[-1,-1]T. To generate hyThe matrix in the readily known local system can be selected as Hi=02×2,Ri=02×2,Yi=I2(i ═ 1,2,3, 4). Six unmanned vehicles need to converge into the projection of a convex hull formed by multiple unmanned vehicles on the ground, and weight vectors rho are defined for depicting expected convergence values of the unmanned vehiclesi=[ρi,1i,2i,3i,4](i ═ 5,6, …,10), and is selected
Figure BDA0003410538520000131
Figure BDA0003410538520000132
Figure BDA0003410538520000133
The formation-enclosure tracking controller is designed. Firstly, respectively selecting X1=X2=I4
Figure BDA0003410538520000134
X3=X4=I4
Figure BDA0003410538520000135
Figure BDA0003410538520000136
(i-5, 6, …,10, j-1, 2,3,4), it can be verified that the regulator equation holds. Then, the controller of the formation-leader drone i (i ═ 1,2,3,4) is designed. Due to Ri=02×2Let the compensation input τi=02×1It can be seen that the feasibility condition (11) holds for each convoy-leader. Selecting adaptive parameters
Figure BDA0003410538520000137
Has an initial value of
Figure BDA0003410538520000138
(i-1, 2,3,4, j-0, 1, …, 4). Let u be 1, the sum of the values of,
Figure BDA0003410538520000139
Υi=I2(i=1,2,3,4)。
finally, the controller of the follower unmanned vehicle i (i ═ 5,6, …,10) was designed. Let adaptive parameters
Figure BDA00034105385200001310
And
Figure BDA00034105385200001311
has an initial value of
Figure BDA00034105385200001312
Selecting K3i=-I2And upsiloni,j=02×2(j ═ 1,2,3, 4). Tracking-leader initial State v0(0)=[-20,0,0,-1]TThe initial state of the formation-leader and follower is generated by a random number.
The simulation results are shown in fig. 3-5. Fig. 3 shows the location trajectory of the drone-drone heterogeneous cluster system within t-30 s and location screenshots at different times (t-0, 15,25,30s), where the five-pointed star indicates that the tracking-leader i-0; the rhombus, the upper triangle, the circle and the right triangle respectively represent formation-leader unmanned aerial vehicles i ═ 1,2,3 and 4; the squares represent follower unmanned vehicles i-5, 6, …, 10. Fig. 4 and 5 show output formation tracking error of the formation-leader and output encircling error curve of the follower, respectively. As can be seen from fig. 3-5, four drones form a desired square formation, and can track the tracking-leader motion trajectory, while six follower drones can converge into the projection of the convex hull formed by multiple drones on the ground. Therefore, the multi-UAV heterogeneous cluster system realizes the expected output formation-surrounding tracking.
Fig. 6 is a schematic structural diagram of a heterogeneous unmanned cluster formation encircling tracking control system provided by the present invention, and as shown in fig. 6, the heterogeneous unmanned cluster formation encircling tracking control system provided by the present invention is characterized by comprising:
the agent partitioning module 601 is used for determining a tracking-leader, a formation-leader and a follower according to the heterogeneous unmanned cluster system; the tracking-leader generates a target signal tracked by the entire heterogeneous unmanned cluster system; the formation-leader and the follower are different types of agents in the heterogeneous unmanned cluster system respectively;
a tracking-leader motion model determination module 602, configured to determine a tracking-leader motion model based on the state of macro motion of the heterogeneous unmanned cluster system and bounded control input; the motion model of the tracking-leader is used for generating a reference track of the overall motion of the heterogeneous unmanned cluster system;
a communication topological relation obtaining module 603, configured to obtain a communication topological relation of the heterogeneous unmanned cluster system; the union of the neighbor sets of all followers in the communication topological relation of the heterogeneous unmanned cluster system comprises all formation-leaders, and the action topologies of the followers are communicated; the action topology among the leaders is a spanning tree with a tracking-leader as a root node, and the action topology among the formation-leaders is undirected;
a controller construction module 604, configured to construct a distributed time-varying formation tracking controller according to the motion model of the tracking-leader, the state of the formation-leader, the communication topology relationship, and the time-varying output formation vector; constructing a distributed surround-tracking controller according to the state of the formation-leader and the state of the follower;
a motion model construction module 605 for constructing a formation-leader motion model according to the distributed time-varying formation tracking controller and the motion model of the tracking-leader; constructing a follower motion model according to the formation-leader motion model and the distributed surround-tracking controller;
a time-varying formation tracking module 606 for time-varying formation tracking the reference trajectory of the tracking-leader using a formation-leader motion model;
a bounding control module 607 for converging the output of the follower into the convex hull of the formation formed by the formation-leader using a follower motion model.
The motion model building module 602 specifically includes:
a tracking-leader motion model determination unit for utilizing a formula
Figure BDA0003410538520000141
Determining a motion model of the tracking-leader;
wherein,
Figure BDA0003410538520000142
the status of the track-leader is represented,
Figure BDA0003410538520000143
a control input representing a track-leader,
Figure BDA0003410538520000144
the output of the track-leader is represented,
Figure BDA0003410538520000145
is a matrix of constants, v0(t) is bounded, and r0(t)||Eta is less than or equal to eta, and eta is a constant.
The embodiments in the present description are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. For the system disclosed by the embodiment, the description is relatively simple because the system corresponds to the method disclosed by the embodiment, and the relevant points can be referred to the method part for description.
The principles and embodiments of the present invention have been described herein using specific examples, which are provided only to help understand the method and the core concept of the present invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, the specific embodiments and the application range may be changed. In view of the above, the present disclosure should not be construed as limiting the invention.

Claims (8)

1. A heterogeneous unmanned cluster formation surround tracking control method is characterized by comprising the following steps:
determining a tracking-leader, a formation-leader, and a follower from the heterogeneous unmanned cluster system; the tracking-leader generates a target signal tracked by the entire heterogeneous unmanned cluster system; the formation-leader and the follower are different types of agents in the heterogeneous unmanned cluster system respectively;
determining a motion model of a tracking-leader according to the macro motion state of the heterogeneous unmanned cluster system and bounded control input; the motion model of the tracking-leader is used for generating a reference track of the overall motion of the heterogeneous unmanned cluster system;
acquiring a communication topological relation of a heterogeneous unmanned cluster system; the union of the neighbor sets of all followers in the communication topological relation of the heterogeneous unmanned cluster system comprises all formation-leaders, and the action topologies of the followers are communicated; the action topology among the leaders is a spanning tree with a tracking-leader as a root node, and the action topology among the formation-leaders is undirected;
constructing a distributed time-varying formation tracking controller according to the motion model of the tracking-leader, the state of the formation-leader, the communication topological relation and the time-varying output formation vector; constructing a distributed surround-tracking controller according to the state of the formation-leader and the state of the follower;
constructing a formation-leader motion model according to the distributed time-varying formation tracking controller and the motion model of the tracking-leader; constructing a follower motion model according to the formation-leader motion model and the distributed surround-tracking controller;
tracking a reference trajectory of the tracking-leader using a formation-leader motion model time-varying formation;
the follower's output is converged into the convex hull of the formation-leader formation using a follower motion model.
2. The heterogeneous unmanned cluster formation surround tracking control method according to claim 1, wherein the determining a motion model of a tracking-leader according to a macro motion state of the heterogeneous unmanned cluster system and a bounded control input specifically comprises:
using formulas
Figure FDA0003410538510000011
Determining a motion model of the tracking-leader;
wherein,
Figure FDA0003410538510000012
the status of the track-leader is represented,
Figure FDA0003410538510000013
a control input representing a track-leader,
Figure FDA0003410538510000014
the output of the track-leader is represented,
Figure FDA0003410538510000015
is a matrix of constants, v0(t) is bounded, and r0(t)||Eta is less than or equal to eta, and eta is a constant.
3. The heterogeneous unmanned cluster formation surround tracking control method according to claim 2, wherein the constructing a distributed time-varying formation tracking controller according to a tracking-leader motion model, a formation-leader state, the communication topological relation and a time-varying output formation vector specifically comprises:
using the formula hyi(t)=Yihi(t) determining a time-varying output queuing vector;
using formulas
Figure FDA0003410538510000021
Determining a distributed time-varying formation tracking controller;
wherein,
Figure FDA0003410538510000022
denotes a formation parameter, i is 1,2, …, N denotes the number of formation-leaders,
Figure FDA0003410538510000023
representing the formation output matrix, hyi(t) is a time-varying output queuing vector,
Figure FDA0003410538510000024
representing the state of the formation-leader,
Figure FDA0003410538510000025
represents a pair v0Is determined by the distributed estimation of the time domain,
Figure FDA0003410538510000026
Figure FDA0003410538510000027
represents the adaptive control gain; tau isiRepresenting a time-varying convoy tracking compensation input,
Figure FDA0003410538510000028
μ denotes the normal number, K1i、Khi、K2i、ΥiAnd ΓiA matrix of gains is represented by a matrix of gains,
Figure FDA0003410538510000029
a non-negative weight is represented by a non-negative weight,
Figure FDA00034105385100000210
representing neighbor formation-leader j pairs v0Is calculated.
4. The heterogeneous unmanned cluster formation surround tracking control method according to claim 3, wherein the distributed time-varying formation tracking controller is constructed according to a tracking-leader motion model, a formation-leader state, the communication topological relation and a time-varying output formation vector, and specifically further comprises:
judging whether the time-varying output formation vector has compensation input or not;
if so, determining whether the compensation input satisfies a formula
Figure FDA00034105385100000211
If so, constructing a distributed time-varying formation tracking controller; if not, re-determining the time-varying output formation vector;
wherein,
Figure FDA00034105385100000212
representing a constant matrix, τi(t) represents the compensation input and,
Figure FDA00034105385100000213
a matrix of constants is represented by a matrix of constants,
Figure FDA00034105385100000214
denotes an external input, XhiRepresenting a constant matrix that satisfies the local regulator equation.
5. The heterogeneous unmanned cluster formation surround tracking control method according to claim 4, wherein the formation-leader motion model is constructed according to a distributed time-varying formation tracking controller and a motion model of a tracking-leader; constructing a follower motion model according to a formation-leader motion model and a distributed surround-tracking controller, and specifically comprising the following steps of:
using formulas
Figure FDA0003410538510000031
Determining formation-leader fortuneA moving model and a follower motion model;
wherein,
Figure FDA0003410538510000032
and
Figure FDA0003410538510000033
respectively, the status, control inputs and outputs of the formation-leader i or follower i, i being 1,2, …, N + M, M being the number of followers,
Figure FDA0003410538510000034
Figure FDA0003410538510000035
is a matrix of constants.
6. The heterogeneous unmanned cluster formation surround tracking control method according to claim 5, wherein the formation-leader motion model is constructed according to a distributed time-varying formation tracking controller and a motion model of a tracking-leader; constructing a follower motion model according to the formation-leader motion model and the distributed surround-tracking controller, and specifically further comprising:
using formulas
Figure FDA0003410538510000036
Determining that a formation-leader achieves a desired time-varying output formation tracking condition;
using formulas
Figure FDA0003410538510000037
Determining a formation-leader-follower to achieve a desired output confounding condition
Wherein, yi(t) is the output of the formation-leader i, i ═ 1,2, …, N, yk(t) output of follower k, ρk,jA non-negative constant of the number of the first,
Figure FDA0003410538510000038
7. a heterogeneous unmanned cluster formation surround tracking control system is characterized by comprising:
the intelligent agent dividing module is used for determining a tracking-leader, a formation-leader and a follower according to the heterogeneous unmanned cluster system; the tracking-leader generates a target signal tracked by the entire heterogeneous unmanned cluster system; the formation-leader and the follower are different types of agents in the heterogeneous unmanned cluster system respectively;
the motion model determination module of the tracking-leader is used for determining the motion model of the tracking-leader according to the macro motion state of the heterogeneous unmanned cluster system and bounded control input; the motion model of the tracking-leader is used for generating a reference track of the overall motion of the heterogeneous unmanned cluster system;
the communication topological relation acquisition module is used for acquiring the communication topological relation of the heterogeneous unmanned cluster system; the union of the neighbor sets of all followers in the communication topological relation of the heterogeneous unmanned cluster system comprises all formation-leaders, and the action topologies of the followers are communicated; the action topology among the leaders is a spanning tree with a tracking-leader as a root node, and the action topology among the formation-leaders is undirected;
the controller construction module is used for constructing a distributed time-varying formation tracking controller according to the motion model of the tracking-leader, the state of the formation-leader, the communication topological relation and the time-varying output formation vector; constructing a distributed surround-tracking controller according to the state of the formation-leader and the state of the follower;
the motion model building module is used for building a formation-leader motion model according to the distributed time-varying formation tracking controller and the motion model of the tracking-leader; constructing a follower motion model according to the formation-leader motion model and the distributed surround-tracking controller;
a time-varying formation tracking module for tracking a reference trajectory of the tracking-leader by a time-varying formation using a formation-leader motion model;
and the enclosure control module is used for converging the output of the follower to a convex hull of the formation formed by the formation-leader by utilizing the follower motion model.
8. The heterogeneous unmanned cluster formation surround-track control method according to claim 7, wherein the motion model construction module of the track-leader specifically comprises:
a tracking-leader motion model determination unit for utilizing a formula
Figure FDA0003410538510000041
Determining a motion model of the tracking-leader;
wherein,
Figure FDA0003410538510000042
the status of the track-leader is represented,
Figure FDA0003410538510000043
a control input representing a track-leader,
Figure FDA0003410538510000044
the output of the track-leader is represented,
Figure FDA0003410538510000045
is a matrix of constants, v0(t) is bounded, and r0(t)||Eta is less than or equal to eta, and eta is a constant.
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CN117331317A (en) * 2023-12-01 2024-01-02 东海实验室 Under-actuated underwater helicopter surrounding control method based on width learning
CN117331317B (en) * 2023-12-01 2024-02-20 东海实验室 Under-actuated underwater helicopter surrounding control method based on width learning
CN118151544A (en) * 2024-05-11 2024-06-07 北京理工大学长三角研究院(嘉兴) Self-adaptive fault-tolerant control method of multi-agent system in surrounding control

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