CN107340784B - Unmanned plane cluster control method - Google Patents

Unmanned plane cluster control method Download PDF

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Publication number
CN107340784B
CN107340784B CN201710719448.2A CN201710719448A CN107340784B CN 107340784 B CN107340784 B CN 107340784B CN 201710719448 A CN201710719448 A CN 201710719448A CN 107340784 B CN107340784 B CN 107340784B
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unmanned plane
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CN107340784A (en
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毛琼
李小民
董海瑞
马彦恒
王正军
赵月飞
杜占龙
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Army Engineering University of PLA
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Army Engineering University of PLA
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Priority to CN201810178712.0A priority patent/CN108196583B/en
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    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05DSYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
    • G05D1/10Simultaneous control of position or course in three dimensions
    • G05D1/101Simultaneous control of position or course in three dimensions specially adapted for aircraft
    • G05D1/104Simultaneous control of position or course in three dimensions specially adapted for aircraft involving a plurality of aircrafts, e.g. formation flying

Abstract

The invention discloses a kind of unmanned plane cluster control method, it is related to unmanned air vehicle technique field.Described method includes following steps:Unmanned plane cluster group's internal members' model is built by the locus of unmanned plane cluster group internal members, speed and acceleration;Build the Acceleration Control function of unmanned plane cluster group internal members;It is controlled by clustering campaign of the Acceleration Control function realization of structure to unmanned plane cluster group internal members, towards target movement and obstacle avoidance movement.The method of the invention flexibility in terms of collective motion is controlled is strong, and uniformity is good, and control is notable with avoidance effect.

Description

Unmanned plane cluster control method
Technical field
The present invention relates to unmanned air vehicle technique field, more particularly to a kind of unmanned plane cluster control method.
Background technology
Multiple UAVs (Unmanned Aerial Vehicles, UAVs) cooperate with each other completes military target strike, mesh The time of tasks carrying can be greatly reduced with tasks such as scoutings, improve the efficiency and success rate fought for mark tracking.With operation Increasingly sophisticated, the not only quantity of space unmanned plane and the density rising, but also forceful electric power magnetic environment easily causes UAV Communication of environment It is blind, and potentially burst obstacle carrys out series of challenges to the flight control of unmanned plane cluster with safety belt, it has also become one is urgently Problem to be solved.
Unmanned plane group system belongs to local sensing or the distributed architecture of communication, control method main at present Have:Controlling based on local rule, soft control, navigating follows method and Artificial Potential Field Method.Control method based on local rule is most Basis, can realize the control that emerges in large numbers of swarm intelligence, but only cluster is emerged in large numbers desired control direction by its difficulty;It is soft control be On the basis of local rule by for cluster add other individuals in the controllable individual guiding group in an outside towards it is intended that Move in direction;Navigator's control methods realize clustered control using informative individual guiding in cluster, will grasp in the prior art The individual of flight path information is directly set to leader, does not consider that whom, which how to recognize, under the actual conditions of no direct communication between individual is The problem of leader;Artificial Potential Field is moved by building global potential field function intelligent body to the direction that potential energy reduces, the party Method is simple and practical, advantageous in terms of avoidance, but there are local extremum problem.To sum up, unmanned plane collection team control of the prior art Method generally existing research conditions processed are preferable, method use cuts both ways, and there are flexibility deficiency, control are bad with avoidance effect The problems such as.
The content of the invention
The technical problems to be solved by the invention are how to provide a kind of activity by force, and uniformity is good, control and avoidance effect Significant unmanned plane collective motion control method.
In order to solve the above technical problems, the technical solution used in the present invention is:A kind of unmanned plane cluster control method, its It is characterized in that including the following steps:
Built by the locus of unmanned plane cluster group internal members, speed and acceleration inside unmanned plane cluster group Member's model;
Build the Acceleration Control function of unmanned plane cluster group internal members;
Pass through clustering campaign of the Acceleration Control function realization of structure to unmanned plane cluster group internal members, direction Target is moved and obstacle avoidance movement is controlled.
Further technical solution is, the distributed system that unmanned plane cluster is made of individual, each individual Movement can be abstracted as:
Wherein:PiRepresent the locus of unmanned plane i, viRepresent speed, aiRepresent acceleration,Represent to PiSingle order is asked to lead Number,Represent to viSeek first derivative.
Further technical solution is, there are following constraint during unmanned plane i flights:
Acceleration constrains:
Wherein, AmaxFor the peak acceleration of unmanned plane;
Constraint of velocity:
Wherein, VmaxFor the maximal rate of unmanned plane.
Further technical solution is, place is normalized to the quality of the individual i of unmanned plane cluster group internal members Its motion control amount acceleration function a after reasoniIt is expressed as:
ai1·α·fi g2·fi o3·fi j1·(1-α)·fi G (4)
γ in above formula1·α·fi gThe control component for attracting to produce for target, γ2·fi oFor the control needed for obstacle avoidance Component, γ3·fi jThe clustering active force produced for neighbours' unmanned plane j in group to unmanned plane i, γ1·(1-α)·fi GFor unmanned plane The control component that individual G leader's unmanned plane individuals i is produced;α is that unmanned plane individual i receives the mark of way point information, the table of α=1 Show that unmanned plane i can receive way point information, at this time the γ on the right side of (4) formula equal sign1·(1-α)·fi GFor 0;α=0 item represents unmanned plane I cannot receive way point information, the γ on the right side of (4) formula equal sign1·α·fi gFor 0, γ1·(1-α)·fi GIt is not 0, individual i will be from Selection unmanned plane G is followed as leader in search coverage, that is, unmanned plane G is made in the case of not receiving target destination Moved for target destination and towards it;γ1、γ2And γ3For the weight of each control component, fi gFor the work of target g and unmanned plane i With force function, fi oFor the force function between obstacle O and unmanned plane i, fi jFor the active force letter of unmanned plane j and unmanned plane i Number, fi GFor the active force between unmanned plane i and selected leader's unmanned plane G.
Further technical solution is, the clustering campaign force function fi jConstruction method it is as follows:
If unmanned plane individual i passes through position individual around visual perception and speed, detection range da;Using individual i as Center, daFor radius, the border circular areas of composition is the search coverage of unmanned plane i;NeighborhoodFall the spy in unmanned plane i for t moment Survey the unmanned plane individual collections in region;The search coverage is divided into three regions:Region of rejectionCoherence domainsDomain of attractionRegion of rejectionRnThe point set O in spacei r=P | 0 < di j≤dr,P∈Rn, coherence domains Domain of attraction Wherein, drTo repel Domain and the boundary distances of coherence domains, do are the boundary distances of coherence domains and domain of attraction, 0 < dr< do< da, RnRepresent n dimension real numbers Collection,Represent the distance between unmanned plane i and unmanned plane j;
NeighborhoodActive force f between interior unmanned plane j and unmanned plane ii jIt is expressed as:
Wherein, Fi j=-▽ Vi j
Wherein:fi jBy the position P of unmanned plane i and unmanned plane ji、PjWith speed vi、vjDetermine;The method of decision:Represent The action direction of power, is unit direction vector, Fi jFor the size of the active force, by the position P of unmanned plane i and unmanned plane ji、Pj Solved according to (7) formula;Vi jFor by the position P of unmanned plane i and unmanned plane ji、PjThe potential field of generation, to Vi jNegative gradient is asked to obtain Fi j;-▽Vi jFor to Vi jSeek negative gradient;By the speed v of unmanned plane i and unmanned plane ji、vjThe active force of generation is equal sign in formula (5) The Section 2 on right side;Repulsion strength control parameter between unmanned plane i and unmanned plane j,For apart from adjustment parameter, Gravitational control parameter between unmanned plane i and unmanned plane j,For the rate uniformity between unmanned plane i and unmanned plane j Control parameter,WithAn initial value can be first given, is then further adjusted in system experimentation.
Further technical solution is, the force function f that the unmanned plane i is moved towards targeti gConstruction method It is as follows:
1) all individuals can obtain way point information
Unmanned aerial vehicle flight path is resolved into a series of sequence location point Track={ T1,T2,...Tm, with the time by airborne or The Automatic dependent surveillance broadcast system transmitting terminal of ground control station is sent one by one, if the every frame unmanned plane of cluster internal can pass through machine Carry the destination that Automatic dependent surveillance broadcast system receiving terminal real-time reception Automatic dependent surveillance broadcast system transmitting terminal is sent Position, speed, the individual position deviation with current destination areConstruct the effect between target g and unmanned plane i Force function fi gIt is as follows:
Wherein,
Wherein:fi gFor the active force between target g and unmanned plane i, by the position P of unmanned plane i and target gi、TkAnd speed vi、vgDetermine;The method of decision is as follows:Represent the action direction of the active force, be unit direction vector, Fi gFor the active force Size, by the position of unmanned plane i and target g according to (9) formula solve, the distance between unmanned plane i and target g areThe active force produced by the speed difference of unmanned plane i and target g is the Section 2 in (8) formula on the right side of equal sign;Its Middle vgAsk method as follows:Unmanned aerial vehicle flight path is being resolved into a series of sequence location point Track={ T1,T2,...TmAfter, if often Two adjacent track points TkAnd Tk+1Between the time interval broadcast be Δ t, k=1...m-1, then target destination is in the flight path section Flying speed be Action intensity control coefrficient between unmanned plane i and target g, rτFor target g and nobody The changed boundary distances of gravitation form between machine i;
2) small part individual can obtain way point information
In the case where small part individual can obtain way point information, the individual for flight path information can be obtained, in 1) The method of description acts power fi g;Individual i for that cannot obtain way point information, then selected in neighborhood using following methods and transported The most fast individual G of dynamic velocity variations:
WhereinRepresent unmanned plane j in t moment and t- τ moment all unmanned plane i's In neighborhood, τ be individual i before and after twice to neighborhoodThe time interval that interior a body position is observed, ΔjRepresent the τ periods The location variation of interior unmanned plane j,It is unmanned plane j in the position of t moment,It is unmanned plane j in the position at t- τ moment;It is a After body i picks out fastest individual G using the method described in (10) formula from neighborhood, it is followed as target, Therebetween by being acted on minor function:
Wherein,
Wherein:fi GFor the active force between unmanned plane G and unmanned plane i, by the position P of unmanned plane i and unmanned plane Gi、PGWith Speed vi、vGDetermine;The method of decision is as follows:Represent the direction of the active force, be unit direction vector, Fi GFor the active force Size, by the position P of unmanned plane i and unmanned plane Gi、PGSolved according to (12) formula, the distance between unmanned plane i and unmanned plane GBy the speed v of unmanned plane i and unmanned plane Gi、vGThe active force of generation is second on the right side of equal sign in (11) formula ;drFor the boundary distances of gravitation and repulsion, dr+rtGravitation form between UAV targets' individual G and unmanned plane i occurs The boundary distances of change;Repulsion strength control coefficient between unmanned plane i and unmanned plane G,For apart from adjustment parameter,It is the gravitational control coefrficient between unmanned plane i and unmanned plane G,Between unmanned plane i and unmanned plane G Rate uniformity control coefrficient,WithCan first give an initial value, then in system experimentation into One step section.
Further technical solution is, if the warning distance between individual i and barrier O is γβ, wherein γβ< da, Then therebetween by being controlled with minor function:
Wherein,
Wherein:fi oFor the active force between obstacle O and unmanned plane i, by the position P of unmanned plane i and obstacle Oi、POAnd speed vi、vODetermine, the method for decision:Represent the action direction of the active force, be unit direction vector, Fi OFor the big of the active force It is small, by the position P of unmanned plane i and obstacle Oi、POSolved according to (14) formula, the distance between unmanned plane i and obstacle OSeparately by the speed v of unmanned plane i and obstacle Oi、vOThe active force of generation is second on the right side of equal sign in (13) formula ;γβWarning distance between unmanned plane i and barrier O,For apart from adjustment parameter,For unmanned plane i and obstacle O it Between repulsion intensity adjustment coefficient,Rate uniformity control coefrficient between unmanned plane i and obstacle O, And γβAn initial value can be first given, then is further adjusted in system experimentation.
It is using beneficial effect caused by above-mentioned technical proposal:The method is first by by local rule and potential field Method fusion generates a kind of new control function, and combines soft control method and control the movement of virtual target destination to successfully boot up Individual realizes aggregation and the flight of cluster control, and " detection is proposed on the basis of limited visual perception to unknown burst obstacle Evade " Robot dodge strategy;Secondly, there was only the situation that some individuals can normally receive flight path information for electromagnetic environment, use The method of neighborhood identification is that the individual selected target individual for not receiving flight path information is followed, and realizes desired cluster fortune It is dynamic.The method of the invention controls situation relatively actual conditions, flexibility that be simple, considering in terms of collective motion is controlled By force, uniformity is good, and control is notable with avoidance effect.
Brief description of the drawings
The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.
Fig. 1 is the flow chart of the method for the embodiment of the present invention;
Fig. 2 is that the effect in the method for the embodiment of the present invention between individual member is tried hard to;
Fig. 3 is that the effect in the method for the embodiment of the present invention between individual and target destination is tried hard to;
Fig. 4 is that the effect in the method for the embodiment of the present invention between individual and target individual is tried hard to;
Fig. 5 is that the effect in the method for the embodiment of the present invention between individual and obstacle is tried hard to;
Fig. 6 is that the method for the embodiment of the present invention carries out the aggregation of unmanned plane individual and the rail along track flight during emulation experiment Mark figure;
Fig. 7 is the curve map that the method for the embodiment of the present invention carries out distance between each frame unmanned plane during emulation experiment;
Fig. 8 is that the method for the embodiment of the present invention carries out Formation Center and the range deviation song of real-time destination during emulation experiment Line chart;
Fig. 9 is the scene graph that unmanned plane cluster hides obstacle when the method for the embodiment of the present invention carries out emulation experiment;
Distance Curve figure of each unmanned plane to obstacle when Figure 10 is the method for embodiment of the present invention progress emulation experiment;
Figure 11 be the method for the embodiment of the present invention carry out emulation experiment when based on neighborhood identification clustered control nobody Machine track plot;
Wherein, 1, the flight path curve of planning;2nd, each unmanned aerial vehicle flight path curve;
3rd, the distance between unmanned plane 1 and unmanned plane 2 curve;4th, the distance between unmanned plane 1 and unmanned plane 3 curve;5、 The distance between unmanned plane 1 and unmanned plane 4 curve;6th, the distance between unmanned plane 1 and unmanned plane 5 curve;7th, unmanned plane 1 and nothing Man-machine the distance between 6 curve;8th, the distance between unmanned plane 2 and unmanned plane 3 curve;9th, between unmanned plane 2 and unmanned plane 4 Distance Curve;10th, the distance between unmanned plane 2 and unmanned plane 5 curve;11st, the distance between unmanned plane 2 and unmanned plane 6 curve; 12nd, the distance between unmanned plane 3 and unmanned plane 4 curve;13rd, the distance between unmanned plane 3 and unmanned plane 5 curve;14th, unmanned plane The distance between 3 and unmanned plane 6 curve;15th, the distance between unmanned plane 4 and unmanned plane 5 curve;16th, unmanned plane 4 and unmanned plane The distance between 6 curves;17th, the distance between unmanned plane 5 and unmanned plane 6 curve;
18th, barrier one;19th, barrier two;20th, the distance between unmanned plane 1 and barrier one curve;21st, unmanned plane 1 The distance between barrier two curve;22nd, the distance between unmanned plane 2 and barrier one curve;23rd, unmanned plane 2 and obstacle The distance between thing two curve;24th, the distance between unmanned plane 3 and barrier one curve;25th, unmanned plane 3 and barrier two it Between distance Curve;26th, the distance between unmanned plane 4 and barrier one curve;27th, between unmanned plane 4 and barrier two away from From curve;28th, the distance between unmanned plane 5 and barrier one curve;29th, the distance between unmanned plane 5 and barrier two curve; 30th, the distance between unmanned plane 6 and barrier one curve;31st, the distance between unmanned plane 6 and barrier two curve;32nd, the 3rd The unmanned aerial vehicle flight path curve of way point information can be received in the case of kind.
Embodiment
With reference to the attached drawing in the embodiment of the present invention, the technical solution in the embodiment of the present invention is carried out clear, complete Ground describes, it is clear that described embodiment is only the part of the embodiment of the present invention, instead of all the embodiments.It is based on Embodiment in the present invention, those of ordinary skill in the art are obtained every other without making creative work Embodiment, belongs to the scope of protection of the invention.
Many details are elaborated in the following description to facilitate a thorough understanding of the present invention, still the present invention can be with Implemented using other different from other manner described here, those skilled in the art can be without prejudice to intension of the present invention In the case of do similar popularization, therefore the present invention is from the limitation of following public specific embodiment.
Overall, as shown in Figure 1, the embodiment of the invention discloses a kind of unmanned plane cluster control method, including following step Suddenly:
S101:Unmanned plane cluster is built by the locus of unmanned plane cluster group internal members, speed and acceleration Group's internal members' model;
S102:Build the Acceleration Control function of unmanned plane cluster group internal members;
S103:The clustering campaign to unmanned plane cluster group internal members is realized by the Acceleration Control function of structure (mainly solve cluster internal collision prevention, keep speed uniformity and group globality), towards target move and evade The movement of (outside cluster) obstacle is controlled.
The method is carried out specifically in terms of modeling, stability analysis and emulation experiment verify three below It is bright:
1st, the acceleration function of unmanned plane cluster group internal members is built
1.1 groups of internal members' models
The distributed system that unmanned plane cluster is made of individual, the movement of each individual can use 6DOF The equation of motion represents, following form can be abstracted as by model abbreviation and mass normalisation processing:
Wherein PiRepresent the locus of unmanned plane i, viRepresent speed, aiRepresent acceleration,Represent to PiSingle order is asked to lead Number,Represent to viSeek first derivative.By in guidance system ring layout acceleration aiUnmanned plane be can control along predefined paths Flight, it is other to transfer to automatic pilot to complete.In addition, during unmanned plane i flights, there are following constraint:
Acceleration constrains:
Wherein, AmaxFor the peak acceleration of unmanned plane.
Constraint of velocity:
Wherein, VmaxFor the maximal rate of unmanned plane.
The motion control rule of 1.2 individuals
The mass motion of unmanned plane cluster of the present invention is individual by unmanned plane individual movement rule control in cluster Between Local Interaction produce a kind of emerging behavior., can be by the fortune of cluster internal individual according to the difference of individual behavior interactive object It is dynamic to be decomposed into three sub-goals:Keep clustering, march on towards target and obstacle avoidance, therefore it is by neighbouring individual group cohesion, target The comprehensive function of the repulsive force three of attraction and obstacle, its motion control amount accelerates after Individual Quality is normalized Spend function aiIt is represented by:
ai1·α·fi g2·fi o3·fi j1·(1-α)·fi G (4)
γ in above formula1·α·fi gThe control component for attracting to produce for target, γ2·fi oFor the control needed for obstacle avoidance Component, γ3·fi jThe clustering active force produced for neighbours' unmanned plane j in group to unmanned plane i;γ1·(1-α)·fi GFor unmanned plane The control component that individual G leader's unmanned plane individuals i is produced;α is that unmanned plane individual i receives the mark of way point information, the table of α=1 Show that unmanned plane i can receive way point information, at this time the γ on the right side of (4) formula equal sign1·(1-α)·fi kFor 0;α=0 item represents unmanned plane I cannot receive way point information, the γ on the right side of (4) formula equal sign1·α·fi gFor 0 and γ1·(1-α)·fi GIt is not 0, individual i will be from Selection unmanned plane G is as leader in search coverage, that is, does not receive and unmanned plane G is considered as leader in the case of target destination And it is followed to move;γ1、γ2And γ3For the weight of each control component, fi gFor the force function of target g and unmanned plane i, fi oFor the force function between obstacle O and unmanned plane i, fi jFor the force function of unmanned plane j and unmanned plane i, fi GFor nobody Active force between machine i and selected leader's unmanned plane G.
1.2.1 the control of clustering campaign
If unmanned plane individual i passes through position individual around visual perception and speed, detection range da;Using individual i as Center, daFor radius, the border circular areas of composition is the search coverage of unmanned plane i;NeighborhoodFall the spy in unmanned plane i for t moment The unmanned plane individual collections in region are surveyed (not including unmanned plane i);The search coverage is divided into three regions:Region of rejectionOne Cause domainDomain of attractionRegion of rejectionRnThe point set in spaceCoherence domains Domain of attraction Wherein, drFor region of rejection With the boundary distances of coherence domains, doFor the boundary distances of coherence domains and domain of attraction, 0 < dr< do< da, RnRepresent n dimension sets of real numbers,Represent the distance between unmanned plane i and unmanned plane j.
NeighborhoodActive force f between interior unmanned plane j and unmanned plane ii jIt is expressed as:
Fi j=-▽ Vi j,-▽ Vi jFor to Vi jSeek negative gradient.
Wherein:fi jBy the position P of unmanned plane i and unmanned plane ji、PjWith speed vi、vjDetermine;The method of decision:Represent The action direction of power, is unit direction vector, Fi jFor the size of the active force, by the position P of unmanned plane i and unmanned plane ji、Pj Solved according to (7) formula;Vi jFor by the position P of unmanned plane i and unmanned plane ji、PjThe potential field of generation, to Vi jNegative gradient is asked to obtain Fi j;-▽Vi jFor to Vi jSeek negative gradient;By the speed v of unmanned plane i and unmanned plane ji、vjThe active force of generation is equal sign in formula (5) The Section 2 on right side;Repulsion strength control parameter between unmanned plane i and unmanned plane j,For apart from adjustment parameter,Gravitational control parameter between unmanned plane i and unmanned plane j,Speed one between unmanned plane i and unmanned plane j Cause property control parameter,WithAn initial value can be first given, is then further adjusted in system experimentation.It is a Active force between body member is as shown in Figure 2.
1.2.2 target-bound motion control
Unmanned plane cluster reaches target area and performs task in order to control, navigates first using unmanned plane cluster as an entirety Mark is planned, to reduce the complexity of path planning;Secondly unmanned aerial vehicle flight path is resolved into a series of sequence location point Track= {T1,T2,...Tm, sent out one by one by airborne (or ground control station) Automatic dependent surveillance broadcast system transmitting terminal with the time Send, if the every frame unmanned plane of cluster internal can be by airborne Automatic dependent surveillance broadcast system receiving terminal real-time reception broadcast type certainly The waypoint location of dynamic dependent surveillance system transmitting terminal transmission, velocity information, pass through the fortune of the renewal control targe Dummy of destination Dynamic position guiding cluster reaches the desired theater of war.The information distribution system can be disposed at cluster internal any one frame nobody Machine, is also disposed at ground control station, at this time flexibly changing destination, improves mobility and the flexibility of clustered control.According to Can airborne broadcast terminal normally receive way point information, can be divided into following two situations:
(1) all individuals can obtain way point information
If the every frame unmanned plane of cluster internal can receive the real time position of destination, speed by airborne data terminal, individual with The position deviation of destination isTo realize the target-bound movement of cluster, the present invention devises following active force letter Number:
Wherein,
fi gFor the active force between target g and unmanned plane i, by the position P of unmanned plane i and target gi、TkWith speed vi、vg Determine.The method of decision:Represent the action direction of the active force, be unit direction vector, Fi gFor the size of the active force, Specifically solved by the position of unmanned plane i and target g according to (9) formula, the distance between unmanned plane i and target g The active force separately produced by the speed difference of unmanned plane i and target g is the Section 2 (note in (8) formula on the right side of equal sign:vgSeek method: Unmanned aerial vehicle flight path is being resolved into a series of sequence location point Track={ T1,T2,...TmAfter, if the adjacent track points of each two TkAnd Tk+1(k=1...m-1) time interval broadcast between is Δ t, then flying speed v of the target destination in the flight path sectiongFor);Action intensity adjustment factor between unmanned plane i and target g, rτFor the work between target g and unmanned plane i The firmly changed boundary distances of form;Active force between target and individual is as shown in Figure 3.
(2) small part individual can obtain way point information
Strong electromagnetic easily prevents the communication disruption of unmanned plane cause it from obtaining target way point information, at this time the prior art In directly by obtain way point information unmanned plane individual be set to leader, by local communication leader do not obtain way point information The movement of body, makes unmanned plane member aggregating and forms clustering campaign.But as the ratio for grasping way point information individual declines, cluster The smoothness of Personal flight path significantly declines, and when ratio drops to less than 1/3, individual, which often produces, departs from collection The phenomenon of group, control and safety to cluster bring very big difficulty;And the office under strong electromagnetic interference environment between unmanned plane Portion's communication can be affected, and the unmanned plane for not obtaining flight path information can not be carried out just between the unmanned plane of acquisition flight path information Normal open is believed, so as to can not learn that who is leader.The method that the neighborhood of view-based access control model is perceived and recognized is proposed to this present invention, Assuming that unmanned plane individual i cannot receive target way point information, therefore can not be with the individual communications of way point information, but energy can be received The position of neighbours' unmanned plane individual and speed in visual range are perceived by airborne visual sensing system:
WhereinRepresent unmanned plane j in t moment and t- τ moment all in unmanned plane i Neighborhood in, τ be individual i before and after twice to neighborhoodThe time interval that interior a body position is observed, ΔjRepresent the τ times The location variation of unmanned plane j in section,It is unmanned plane j in the position of t moment,It is unmanned plane j in the position at t- τ moment; After individual i picks out fastest individual G using the method described in (10) formula from neighborhood, it is chased after as leader With therebetween by being acted on minor function:
Wherein:fi GFor the active force between unmanned plane G and unmanned plane i, by the position P of unmanned plane i and unmanned plane Gi、PGWith Speed vi、vGDetermine.The method of decision:Represent the action direction of the power, be unit direction vector, Fi GFor the big of the active force It is small, specifically solved by the position of unmanned plane i and unmanned plane G according to (12) formula, the distance between unmanned plane i and unmanned plane GThe active force separately produced by the speed difference of unmanned plane i and unmanned plane G is second on the right side of equal sign in (11) formula .drBoundary distances between region of rejection and coherence domains, dr+rtFor the gravitation between UAV targets' individual G and unmanned plane i The changed boundary distances of form;Repulsion strength control coefficient between unmanned plane i and unmanned plane G,For distance Adjustment parameter,It is the gravitational control coefrficient between unmanned plane i and unmanned plane G,For unmanned plane i and nothing Rate uniformity control coefrficient between man-machine G,WithAn initial value can be first given, then is being Further adjusted during system experiment.Active force between individual and target individual is as shown in Figure 4.
1.2.3 the motion control of obstacle avoidance
Cluster is flown to along preset flight path during destination, can run into the threat of some obstacles.Individual is to ensure certainly The flight safety of body is, it is necessary to evade barrier.According to threaten in advance whether it is known be divided into known threat and with it is unknown Threaten.For known threat, preliminary treatment can be carried out in the trajectory planning stage, individual is actively evaded in flight course;It is right When the action of unknown threat, the then detectivity dependent on airborne sensor, computer information processing speed and executing agency Between.The present invention is directed to unknown threat, in order to be consistent with actual conditions, if the detection range of unmanned plane individual i is γβ, airborne letter Breath processing and perform the time of response and be τ '=0.25s, it is individual at the time of obstacle is detected τ ' seconds laggard professional etiquette keep away (detection is evaded), then it is designed by following force function therebetween:
Wherein,
Wherein, fi oFor the active force between obstacle O and unmanned plane i, by the position P of unmanned plane i and obstacle Oi、POAnd speed vi、vODetermine, the method for decision:Represent the action direction of the active force, be unit direction vector, Fi OFor the big of the active force It is small, solved by the position of unmanned plane i and obstacle O according to (14) formula, the distance between unmanned plane i and obstacle O The active force separately produced by the speed difference of unmanned plane i and obstacle O is the Section 2 in (13) formula on the right side of equal sign;γβFor unmanned plane i Warning distance between barrier O,For apart from adjustment parameter,Repulsion intensity tune between unmanned plane i and obstacle O Save coefficient,Rate uniformity control coefrficient between unmanned plane i and obstacle O,And γβOne can first be given Initial value, then further adjusted in system experimentation.Active force between individual and obstacle is as shown in Figure 5.
2nd, stability analysis
For cluster, illustrate that it has well if the distance between cluster internal individual and neighbours remain unchanged Stability and robustness.To simplify stability analysis process, consider that cluster internal only has two frame unmanned plane i's and j first herein Situation, they are within mutual detection range.According to (1) formula, ifWithRespectively nobody Two machines are considered as a system by the relative position and relative velocity (two state variables of system) of machine i and j, i.e., stability with fi jIt is related.
If liapunov function:
Then
Two machine speed gradually reach unanimity, i.e., the distance between two machines also tend to certain value, and system reaches stable state!
Next consider that cluster internal there are 3 frame unmanned planes, numbering is respectively 1,2,3, and each mutual detection range of leisure It is interior.Stability analysis is carried out by taking individual 2 as an example, its neighbour is 1 and 3, is set as stated aboveThen:
If liapunov function:
Conclusion is same as above, and so on, if cluster internal has N frame unmanned planes, unmanned plane i has M neighbours, usesRepresent It is gathered, and is simplified pr oof process, M neighbours are separately represented with numbering l=1,2...M.
OrderThen
If liapunov function:Then:
According to Liapunov stability method of discrimination, judgement system is stablized!
3rd, emulation experiment is verified
For convenience of interpretation of result is carried out, the unmanned plane cluster flight to three dimensions below carries out emulation with obstacle avoidance and tests Card.Way point information can be received by individual, emulation experiment is mainly unfolded from following several respects:
Situation one:Unmanned plane cluster internal individual can obtain real-time flight path information, and flight space is accessible sets cluster Internal unmanned plane number of individuals is 6, and individual can receive real-time flight path information (α=1) by broadcast terminal.According to (4) formula, the feelings The motion control acceleration function a of unmanned plane individual under conditioni1·fi g2·fi o3·fi jAnd fi o=0.Unmanned plane into The initial velocity of member is 0, and initial position is random, is flown after way point information is received initially towards it, airborne sensor detection Distance is 60m, maximal rate 40m/s, peak acceleration 0.5m/s2, fuselage long 2m, γ1=1, γ2=3, γ3=0.5,rτ=20m,dr=20m, do= 30m, da=60m.Individual is finally assembled and along target to the flight path direction of motion under the control input effect that above-mentioned parameter determines Track flight, flight path is as shown in fig. 6, the distance between each machine is as shown in Figure 7.If withRepresent cluster Center, E (t)=Tk-PgroupRepresent cluster centers and current destination TkThe distance between deviation, its change procedure it is as shown in Figure 8.
Fig. 6 shows flight path direction fortune of the unmanned function of each frame from arbitrary initial state to planning under the control method Move, move closer to, assemble and formed the movement of an entirety;The apparent distances shown between any two machine of each moment of Fig. 7, Its curve trend shows that the distance carves maximum at the beginning, gradually converges to a stationary value, and the minimum between any two machine later Distance is 7.8 meters (being more than 2 meters of fuselage length), ensure that collisionless generation;Fig. 9 shows that deviation is gradual over time Convergence, cluster centers can press track flight substantially.
Situation two:Unmanned plane individual can obtain real-time flight path information in cluster, and flight space has unknown obstacle
Unmanned plane cluster internal individual is along during track flight, and when flying to obstacle, its airborne sensor detects To the position of the barrier, velocity information, the control method of situation one, but f at this time can be still usedi o≠ 0, orderγβ=25m,The locus of barrier one is (48,72,50) (m), barrier two Locus is (78,50,50) (m), and other parameters are the same as situation one.The simulated effect of three dimensions is as shown in figure 9, between each machine Distance it is as shown in Figure 10.
Sphere in Fig. 9 is the region where obstacle, and unmanned plane can be clearly visible in close barrier from unmanned aerial vehicle flight path line The lateral thrust for substantially deviating from obstacle occurs when hindering thing, as detects that obstacle evades behavior with what is produced;2 in Figure 10 are most Low ebb is the period (marking part see dotted-line ellipse) of cluster avoiding barrier one and barrier two, each machine all the time with obstacle Thing keeps more than 10 meters of distance.The same data analysing method for using situation one obtains minimum distance between each machine as 4.3m, still More than fuselage length value 2m, the collision with obstacle is avoided that.
Situation three:Cluster internal minority individual can obtain real-time way point information, and flight space is accessible
In this case, the individual for having been received by way point information continues to be controlled according to the method for situation one, destination is not received The individual of information is followed using method choice neighbours' unmanned plane individual G of neighborhood identification as leader, its control input For ai2·fi o3·fi j1·fi G, dr=20, rτ=20,τ=1, remaining parameter setting is the same, its effect is as shown in figure 11.
As can be seen from Figure 11, cluster internal has 6 frame unmanned planes, and only 1 frame can receive the flight path information (song marked as 32 Line, account for colony's number 1/6), at least there are it in the search coverage of each frame unmanned plane in other 5 frame unmanned plane under primary condition Its 1 frame unmanned plane and can be associated with by this method on the 1 frame unmanned plane that can receive flight path information, using neighborhood follow with The method of identification is not receive the individual choice leader of flight path information, a physical efficiency clustering effect, the guiding of leader and Under under Target Towing mass motion is drawn close and is formed from the aggregation of arbitrary initial state.

Claims (3)

1. a kind of unmanned plane cluster control method, it is characterised in that include the following steps:
Unmanned plane cluster group internal members are built by the locus of unmanned plane cluster group internal members, speed and acceleration Model;The distributed system that unmanned plane cluster is made of individual, the movement of each individual can be abstracted as:
<mrow> <mfenced open = "{" close = ""> <mtable> <mtr> <mtd> <mrow> <msub> <mover> <mi>P</mi> <mo>&amp;CenterDot;</mo> </mover> <mi>i</mi> </msub> <mo>=</mo> <msub> <mi>v</mi> <mi>i</mi> </msub> </mrow> </mtd> </mtr> <mtr> <mtd> <mrow> <msub> <mover> <mi>v</mi> <mo>&amp;CenterDot;</mo> </mover> <mi>i</mi> </msub> <mo>=</mo> <msub> <mi>a</mi> <mi>i</mi> </msub> </mrow> </mtd> </mtr> </mtable> </mfenced> <mo>,</mo> <mi>i</mi> <mo>=</mo> <mn>1</mn> <mo>,</mo> <mn>2</mn> <mo>,</mo> <mo>...</mo> <mi>N</mi> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>1</mn> <mo>)</mo> </mrow> </mrow>
Wherein:PiRepresent the locus of unmanned plane i, viRepresent speed, aiRepresent acceleration,Represent to PiSeek first derivative, Represent to viSeek first derivative;
There are following constraint during unmanned plane during flying:
Acceleration constrains:
<mrow> <msub> <mi>a</mi> <mi>i</mi> </msub> <mo>=</mo> <mfenced open = "{" close = ""> <mtable> <mtr> <mtd> <msub> <mi>a</mi> <mi>i</mi> </msub> </mtd> <mtd> <mrow> <mo>|</mo> <mo>|</mo> <msub> <mi>a</mi> <mi>i</mi> </msub> <mo>|</mo> <mo>|</mo> <mo>&amp;le;</mo> <msub> <mi>A</mi> <mrow> <mi>m</mi> <mi>a</mi> <mi>x</mi> </mrow> </msub> </mrow> </mtd> </mtr> <mtr> <mtd> <mrow> <msub> <mi>A</mi> <mrow> <mi>m</mi> <mi>a</mi> <mi>x</mi> </mrow> </msub> <mfrac> <msub> <mi>a</mi> <mi>i</mi> </msub> <mrow> <mo>|</mo> <mo>|</mo> <msub> <mi>a</mi> <mi>i</mi> </msub> <mo>|</mo> <mo>|</mo> </mrow> </mfrac> </mrow> </mtd> <mtd> <mrow> <mo>|</mo> <mo>|</mo> <msub> <mi>a</mi> <mi>i</mi> </msub> <mo>|</mo> <mo>|</mo> <mo>&gt;</mo> <msub> <mi>A</mi> <mrow> <mi>m</mi> <mi>a</mi> <mi>x</mi> </mrow> </msub> </mrow> </mtd> </mtr> </mtable> </mfenced> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>2</mn> <mo>)</mo> </mrow> </mrow>
Wherein, AmaxFor the peak acceleration of unmanned plane;
Constraint of velocity:
<mrow> <msub> <mi>v</mi> <mi>i</mi> </msub> <mo>=</mo> <mfenced open = "{" close = ""> <mtable> <mtr> <mtd> <msub> <mi>v</mi> <mi>i</mi> </msub> </mtd> <mtd> <mrow> <mo>|</mo> <mo>|</mo> <msub> <mi>v</mi> <mi>i</mi> </msub> <mo>|</mo> <mo>|</mo> <mo>&amp;le;</mo> <msub> <mi>V</mi> <mrow> <mi>m</mi> <mi>a</mi> <mi>x</mi> </mrow> </msub> </mrow> </mtd> </mtr> <mtr> <mtd> <mrow> <msub> <mi>V</mi> <mrow> <mi>m</mi> <mi>a</mi> <mi>x</mi> </mrow> </msub> <mfrac> <msub> <mi>v</mi> <mi>i</mi> </msub> <mrow> <mo>|</mo> <mo>|</mo> <msub> <mi>v</mi> <mi>i</mi> </msub> <mo>|</mo> <mo>|</mo> </mrow> </mfrac> </mrow> </mtd> <mtd> <mrow> <mo>|</mo> <mo>|</mo> <msub> <mi>v</mi> <mi>i</mi> </msub> <mo>|</mo> <mo>|</mo> <mo>&gt;</mo> <msub> <mi>V</mi> <mrow> <mi>m</mi> <mi>a</mi> <mi>x</mi> </mrow> </msub> </mrow> </mtd> </mtr> </mtable> </mfenced> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>3</mn> <mo>)</mo> </mrow> </mrow>
Wherein, VmaxFor the maximal rate of unmanned plane;
Build the Acceleration Control function of unmanned plane cluster group internal members;
Rear its motion control amount acceleration function a is normalized to the quality of unmanned plane cluster group's internal members' individual ii It is expressed as:
ai1·α·fi g2·fi o3·fi j1·(1-α)·fi G (4)
γ in above formula1·α·fi gThe control component for attracting to produce for target, γ2·fi oFor the control component needed for obstacle avoidance, γ3·fi jThe clustering active force produced for neighbours' unmanned plane j in group to unmanned plane i, γ1·(1-α)·fi GFor unmanned plane individual G The control component for leading unmanned plane individual i to produce;α is the mark that unmanned plane individual i receives way point information, and α=1 represents nobody Machine i can receive way point information, at this time the γ on the right side of (4) formula equal sign1·(1-α)·fi GFor 0;α=0 item represents that unmanned plane i cannot Way point information is received, the γ on the right side of (4) formula equal sign1·α·fi gFor 0, γ1·(1-α)·fi GIt is not 0, individual i will be from detecting area Select unmanned plane G to be followed as leader in domain, that is, do not receive in the case of target destination using unmanned plane G as target Destination is simultaneously moved towards it;γ1、γ2And γ3For the weight of each control component, fi gFor the active force letter of target g and unmanned plane i Number, fi oFor the force function between obstacle O and unmanned plane i, fi jFor the force function of unmanned plane j and unmanned plane i, fi GFor Active force between unmanned plane i and selected leader's unmanned plane G;
Clustering campaign to unmanned plane cluster group internal members is realized, towards target by the Acceleration Control function of structure Movement and obstacle avoidance movement are controlled, the clustering campaign force function fi jConstruction method it is as follows:
If unmanned plane individual i passes through position individual around visual perception and speed, detection range da;Centered on individual i, daFor radius, the border circular areas of composition is the search coverage of unmanned plane i;NeighborhoodFall the search coverage in unmanned plane i for t moment Interior unmanned plane individual collections;The search coverage is divided into three regions:Region of rejectionCoherence domainsAnd domain of attractionRow Denounce domainRnThe point set in spaceCoherence domains Domain of attraction Wherein, drFor the boundary distances of region of rejection and coherence domains, doFor one Cause the boundary distances of domain and domain of attraction, 0 < dr< do< da, RnRepresent n dimension sets of real numbers,Represent unmanned plane i and nothing The distance between man-machine j;
NeighborhoodActive force f between interior unmanned plane j and unmanned plane ii jIt is expressed as:
<mrow> <msubsup> <mi>f</mi> <mi>i</mi> <mi>j</mi> </msubsup> <mo>=</mo> <munder> <mo>&amp;Sigma;</mo> <mrow> <mi>j</mi> <mo>&amp;Element;</mo> <msubsup> <mi>N</mi> <mi>i</mi> <mi>t</mi> </msubsup> </mrow> </munder> <msubsup> <mi>F</mi> <mi>i</mi> <mi>j</mi> </msubsup> <msubsup> <mi>n</mi> <mi>i</mi> <mi>j</mi> </msubsup> <mo>-</mo> <munder> <mo>&amp;Sigma;</mo> <mrow> <mi>j</mi> <mo>&amp;Element;</mo> <msubsup> <mi>N</mi> <mi>i</mi> <mi>t</mi> </msubsup> </mrow> </munder> <msubsup> <mi>k</mi> <mi>i</mi> <mrow> <mi>v</mi> <mi>j</mi> </mrow> </msubsup> <mrow> <mo>(</mo> <msub> <mi>v</mi> <mi>i</mi> </msub> <mo>-</mo> <msub> <mi>v</mi> <mi>j</mi> </msub> <mo>)</mo> </mrow> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>5</mn> <mo>)</mo> </mrow> </mrow>
<mrow> <msubsup> <mi>V</mi> <mi>i</mi> <mi>j</mi> </msubsup> <mo>=</mo> <mfenced open = "{" close = ""> <mtable> <mtr> <mtd> <mrow> <mfrac> <mn>1</mn> <mn>2</mn> </mfrac> <msubsup> <mi>k</mi> <mi>i</mi> <mrow> <mi>j</mi> <mn>1</mn> </mrow> </msubsup> <msup> <mrow> <mo>(</mo> <mfrac> <mrow> <msub> <mi>d</mi> <mi>r</mi> </msub> <mo>+</mo> <msubsup> <mi>k</mi> <mi>i</mi> <mrow> <mi>j</mi> <mn>2</mn> </mrow> </msubsup> </mrow> <mrow> <msubsup> <mi>d</mi> <mi>i</mi> <mi>j</mi> </msubsup> <mo>+</mo> <msubsup> <mi>k</mi> <mi>i</mi> <mrow> <mi>j</mi> <mn>2</mn> </mrow> </msubsup> </mrow> </mfrac> <mo>-</mo> <mn>1</mn> <mo>)</mo> </mrow> <mn>2</mn> </msup> </mrow> </mtd> <mtd> <mrow> <mn>0</mn> <mo>&lt;</mo> <msubsup> <mi>d</mi> <mi>i</mi> <mi>j</mi> </msubsup> <mo>&lt;</mo> <msub> <mi>d</mi> <mi>r</mi> </msub> </mrow> </mtd> </mtr> <mtr> <mtd> <mn>0</mn> </mtd> <mtd> <mrow> <msub> <mi>d</mi> <mi>r</mi> </msub> <mo>&lt;</mo> <msubsup> <mi>d</mi> <mi>i</mi> <mi>j</mi> </msubsup> <mo>&lt;</mo> <msub> <mi>d</mi> <mi>o</mi> </msub> </mrow> </mtd> </mtr> <mtr> <mtd> <mrow> <msubsup> <mi>k</mi> <mi>i</mi> <mrow> <mi>j</mi> <mn>3</mn> </mrow> </msubsup> <msup> <mrow> <mo>(</mo> <msubsup> <mi>d</mi> <mi>i</mi> <mi>j</mi> </msubsup> <mo>-</mo> <msub> <mi>d</mi> <mi>o</mi> </msub> <mo>)</mo> </mrow> <mn>2</mn> </msup> </mrow> </mtd> <mtd> <mrow> <msub> <mi>d</mi> <mi>o</mi> </msub> <mo>&lt;</mo> <msubsup> <mi>d</mi> <mi>i</mi> <mi>j</mi> </msubsup> <mo>&lt;</mo> <msub> <mi>d</mi> <mi>a</mi> </msub> </mrow> </mtd> </mtr> </mtable> </mfenced> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>6</mn> <mo>)</mo> </mrow> </mrow>
Wherein,
<mrow> <msubsup> <mi>F</mi> <mi>i</mi> <mi>j</mi> </msubsup> <mo>=</mo> <mfenced open = "{" close = ""> <mtable> <mtr> <mtd> <mrow> <msubsup> <mi>k</mi> <mi>i</mi> <mrow> <mi>j</mi> <mn>1</mn> </mrow> </msubsup> <mrow> <mo>(</mo> <mfrac> <mrow> <msub> <mi>d</mi> <mi>r</mi> </msub> <mo>+</mo> <msubsup> <mi>k</mi> <mi>i</mi> <mrow> <mi>j</mi> <mn>2</mn> </mrow> </msubsup> </mrow> <mrow> <msubsup> <mi>d</mi> <mi>i</mi> <mi>j</mi> </msubsup> <mo>+</mo> <msubsup> <mi>k</mi> <mi>i</mi> <mrow> <mi>j</mi> <mn>2</mn> </mrow> </msubsup> </mrow> </mfrac> <mo>-</mo> <mn>1</mn> <mo>)</mo> </mrow> <mfrac> <mrow> <msub> <mi>d</mi> <mi>r</mi> </msub> <mo>+</mo> <msubsup> <mi>k</mi> <mi>i</mi> <mrow> <mi>j</mi> <mn>2</mn> </mrow> </msubsup> </mrow> <msup> <mrow> <mo>(</mo> <msubsup> <mi>d</mi> <mi>i</mi> <mi>j</mi> </msubsup> <mo>+</mo> <msubsup> <mi>k</mi> <mi>i</mi> <mrow> <mi>j</mi> <mn>2</mn> </mrow> </msubsup> <mo>)</mo> </mrow> <mn>2</mn> </msup> </mfrac> </mrow> </mtd> <mtd> <mrow> <mn>0</mn> <mo>&lt;</mo> <msubsup> <mi>d</mi> <mi>i</mi> <mi>j</mi> </msubsup> <mo>&lt;</mo> <msub> <mi>d</mi> <mi>r</mi> </msub> </mrow> </mtd> </mtr> <mtr> <mtd> <mn>0</mn> </mtd> <mtd> <mrow> <msub> <mi>d</mi> <mi>r</mi> </msub> <mo>&lt;</mo> <msubsup> <mi>d</mi> <mi>i</mi> <mi>j</mi> </msubsup> <mo>&lt;</mo> <msub> <mi>d</mi> <mi>o</mi> </msub> </mrow> </mtd> </mtr> <mtr> <mtd> <mrow> <mo>-</mo> <mn>2</mn> <msubsup> <mi>k</mi> <mi>i</mi> <mrow> <mi>j</mi> <mn>3</mn> </mrow> </msubsup> <mrow> <mo>(</mo> <msubsup> <mi>d</mi> <mi>i</mi> <mi>j</mi> </msubsup> <mo>-</mo> <msub> <mi>d</mi> <mi>o</mi> </msub> <mo>)</mo> </mrow> </mrow> </mtd> <mtd> <mrow> <msub> <mi>d</mi> <mi>o</mi> </msub> <mo>&lt;</mo> <msubsup> <mi>d</mi> <mi>i</mi> <mi>j</mi> </msubsup> <mo>&lt;</mo> <msub> <mi>d</mi> <mi>a</mi> </msub> </mrow> </mtd> </mtr> </mtable> </mfenced> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>7</mn> <mo>)</mo> </mrow> </mrow>
Wherein:fi jBy the position P of unmanned plane i and unmanned plane ji、PjWith speed vi、vjDetermine;The method of decision:Represent the work of power It is unit direction vector with direction, Fi jFor the size of the active force, by the position P of unmanned plane i and unmanned plane ji、PjAccording to (7) Formula solves;Vi jFor by the position P of unmanned plane i and unmanned plane ji、PjThe potential field of generation, to Vi jNegative gradient is asked to obtain Fi jFor To Vi jSeek negative gradient;By the speed v of unmanned plane i and unmanned plane ji、vjThe active force of generation is second on the right side of equal sign in formula (5) ;Repulsion strength control parameter between unmanned plane i and unmanned plane j,For apart from adjustment parameter,For unmanned plane i Gravitational control parameter between unmanned plane j,Rate uniformity control parameter between unmanned plane i and unmanned plane j,WithAn initial value can be first given, is then further adjusted in system experimentation.
2. unmanned plane cluster control method as claimed in claim 1, it is characterised in that:The unmanned plane i is moved towards target g Force function fi gConstruction method it is as follows:
1) all individuals can obtain way point information
Unmanned aerial vehicle flight path is resolved into a series of sequence location point Track={ T1,T2,...Tm, with the time by airborne or ground The Automatic dependent surveillance broadcast system transmitting terminal of control station is sent one by one, if the every frame unmanned plane of cluster internal can be by airborne wide Broadcast formula automatic dependent surveillance system receiving terminal real-time reception Automatic dependent surveillance broadcast system transmitting terminal transmission waypoint location, Speed, the individual position deviation with current destination areConstruct the active force letter between target g and unmanned plane i Number fi gIt is as follows:
<mrow> <msubsup> <mi>f</mi> <mi>i</mi> <mi>g</mi> </msubsup> <mo>=</mo> <msubsup> <mi>&amp;Sigma;F</mi> <mi>i</mi> <mi>g</mi> </msubsup> <msubsup> <mi>n</mi> <mi>i</mi> <mi>g</mi> </msubsup> <mo>-</mo> <msubsup> <mi>&amp;Sigma;k</mi> <mi>i</mi> <mrow> <mi>v</mi> <mi>g</mi> </mrow> </msubsup> <mrow> <mo>(</mo> <msub> <mi>v</mi> <mi>i</mi> </msub> <mo>-</mo> <msub> <mi>v</mi> <mi>g</mi> </msub> <mo>)</mo> </mrow> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>8</mn> <mo>)</mo> </mrow> </mrow>
Wherein,
<mrow> <msubsup> <mi>F</mi> <mi>i</mi> <mi>g</mi> </msubsup> <mo>=</mo> <mfenced open = "{" close = ""> <mtable> <mtr> <mtd> <mrow> <mo>-</mo> <mfrac> <msubsup> <mi>k</mi> <mi>i</mi> <mi>g</mi> </msubsup> <msup> <mi>r</mi> <mi>&amp;tau;</mi> </msup> </mfrac> <msubsup> <mi>d</mi> <mi>i</mi> <mi>g</mi> </msubsup> </mrow> </mtd> <mtd> <mrow> <msubsup> <mi>d</mi> <mi>i</mi> <mi>g</mi> </msubsup> <mo>&lt;</mo> <msup> <mi>r</mi> <mi>&amp;tau;</mi> </msup> </mrow> </mtd> </mtr> <mtr> <mtd> <mrow> <mo>-</mo> <msubsup> <mi>k</mi> <mi>i</mi> <mi>g</mi> </msubsup> </mrow> </mtd> <mtd> <mrow> <msup> <mi>r</mi> <mi>&amp;tau;</mi> </msup> <mo>&amp;le;</mo> <msubsup> <mi>d</mi> <mi>i</mi> <mi>g</mi> </msubsup> </mrow> </mtd> </mtr> </mtable> </mfenced> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>9</mn> <mo>)</mo> </mrow> </mrow>
Wherein:fi gFor the active force between target g and unmanned plane i, by the position P of unmanned plane i and target gi、TkWith speed vi、vg Determine;The method of decision is as follows:Represent the action direction of the active force, be unit direction vector, Fi gFor the big of the active force It is small, solved by the position of unmanned plane i and target g according to (9) formula, the distance between unmanned plane i and target g areThe active force produced by the speed difference of unmanned plane i and target g is the Section 2 in (8) formula on the right side of equal sign;Its Middle vgAsk method as follows:Unmanned aerial vehicle flight path is being resolved into a series of sequence location point Track={ T1,T2,...TmAfter, if often Two adjacent track points TkAnd Tk+1Between the time interval broadcast be Δ t, k=1...m-1, then target destination is in the flight path section Flying speed vgFor Action intensity control coefrficient between unmanned plane i and target g, rτFor target g and nothing The changed boundary distances of gravitation form between man-machine i;
2) small part individual can obtain way point information
In the case where small part individual can obtain way point information, the individual for flight path information can be obtained, described in 1) Method act power fi g;Individual i for that cannot obtain way point information, then selected using following methods and speed moved in neighborhood Degree changes most fast individual G:
<mrow> <mi>G</mi> <mo>=</mo> <mo>{</mo> <mi>j</mi> <mo>|</mo> <munder> <mrow> <mi>m</mi> <mi>a</mi> <mi>x</mi> </mrow> <mrow> <mi>j</mi> <mo>&amp;Element;</mo> <msubsup> <mi>N</mi> <mi>i</mi> <mi>t</mi> </msubsup> <mo>&amp;cap;</mo> <msubsup> <mi>N</mi> <mi>i</mi> <mrow> <mi>t</mi> <mo>-</mo> <mi>&amp;tau;</mi> </mrow> </msubsup> </mrow> </munder> <msub> <mi>&amp;Delta;</mi> <mi>j</mi> </msub> <mo>}</mo> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>10</mn> <mo>)</mo> </mrow> </mrow>
Wherein,Represent unmanned plane j in t moment and t- τ moment all unmanned plane i's In neighborhood, τ be individual i before and after twice to neighborhoodThe time interval that interior a body position is observed, ΔjRepresent the τ periods The location variation of interior unmanned plane j,It is unmanned plane j in the position of t moment,It is unmanned plane j in the position at t- τ moment; After individual i picks out fastest individual G using the method described in (10) formula from neighborhood, it is chased after as target With therebetween by being acted on minor function:
<mrow> <msubsup> <mi>f</mi> <mi>i</mi> <mi>G</mi> </msubsup> <mo>=</mo> <msubsup> <mi>&amp;Sigma;F</mi> <mi>i</mi> <mi>G</mi> </msubsup> <msubsup> <mi>n</mi> <mi>i</mi> <mi>G</mi> </msubsup> <mo>-</mo> <msubsup> <mi>&amp;Sigma;k</mi> <mi>i</mi> <mrow> <mi>v</mi> <mi>G</mi> </mrow> </msubsup> <mrow> <mo>(</mo> <msub> <mi>v</mi> <mi>i</mi> </msub> <mo>-</mo> <msub> <mi>v</mi> <mi>G</mi> </msub> <mo>)</mo> </mrow> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>11</mn> <mo>)</mo> </mrow> </mrow>
Wherein,
Wherein:fi GFor the active force between unmanned plane G and unmanned plane i, by the position P of unmanned plane i and unmanned plane Gi、PGAnd speed vi、vGDetermine;The method of decision is as follows:Represent the direction of the active force, be unit direction vector, Fi GFor the big of the active force It is small, by the position P of unmanned plane i and unmanned plane Gi、PGSolved according to (12) formula, the distance between unmanned plane i and unmanned plane GBy the speed v of unmanned plane i and unmanned plane Gi、vGThe active force of generation is second on the right side of equal sign in (11) formula ;drFor the boundary distances of gravitation and repulsion, dr+rτGravitation form between UAV targets' individual G and unmanned plane i occurs The boundary distances of change;Repulsion strength control coefficient between unmanned plane i and unmanned plane G,For apart from adjustment parameter,It is the gravitational control coefrficient between unmanned plane i and unmanned plane G,Between unmanned plane i and unmanned plane G Rate uniformity control coefrficient,WithCan first give an initial value, then in system experimentation into One step section.
3. unmanned plane cluster control method as claimed in claim 1, it is characterised in that:
If the warning distance between individual i and barrier O is γβ, wherein γβ< da, then therebetween by being carried out with minor function Control:
<mrow> <msubsup> <mi>f</mi> <mi>i</mi> <mi>o</mi> </msubsup> <mo>=</mo> <munder> <mo>&amp;Sigma;</mo> <mrow> <mi>j</mi> <mo>&amp;Element;</mo> <msubsup> <mi>N</mi> <mi>i</mi> <mi>&amp;beta;</mi> </msubsup> <mrow> <mo>(</mo> <mi>t</mi> <mo>)</mo> </mrow> </mrow> </munder> <msubsup> <mi>F</mi> <mi>i</mi> <mi>o</mi> </msubsup> <msubsup> <mi>n</mi> <mi>i</mi> <mi>o</mi> </msubsup> <mo>-</mo> <munder> <mo>&amp;Sigma;</mo> <mrow> <mi>j</mi> <mo>&amp;Element;</mo> <msubsup> <mi>N</mi> <mi>i</mi> <mi>&amp;beta;</mi> </msubsup> <mrow> <mo>(</mo> <mi>t</mi> <mo>)</mo> </mrow> </mrow> </munder> <msubsup> <mi>k</mi> <mi>i</mi> <mrow> <mi>v</mi> <mi>o</mi> </mrow> </msubsup> <mrow> <mo>(</mo> <msub> <mi>v</mi> <mi>o</mi> </msub> <mo>-</mo> <msub> <mi>v</mi> <mi>i</mi> </msub> <mo>)</mo> </mrow> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>13</mn> <mo>)</mo> </mrow> </mrow>
<mrow> <msubsup> <mi>F</mi> <mi>i</mi> <mi>o</mi> </msubsup> <mo>=</mo> <mfenced open = "{" close = ""> <mtable> <mtr> <mtd> <mrow> <msubsup> <mi>k</mi> <mi>i</mi> <mi>o</mi> </msubsup> <mo>&amp;CenterDot;</mo> <mrow> <mo>(</mo> <mfrac> <mrow> <msup> <mi>&amp;gamma;</mi> <mi>&amp;beta;</mi> </msup> <mo>+</mo> <msubsup> <mi>k</mi> <mi>i</mi> <mi>&amp;lambda;</mi> </msubsup> </mrow> <mrow> <msubsup> <mi>d</mi> <mi>i</mi> <mi>o</mi> </msubsup> <mo>+</mo> <msubsup> <mi>k</mi> <mi>i</mi> <mi>&amp;lambda;</mi> </msubsup> </mrow> </mfrac> <mo>-</mo> <mn>1</mn> <mo>)</mo> </mrow> <mo>&amp;CenterDot;</mo> <mfrac> <mrow> <msup> <mi>&amp;gamma;</mi> <mi>&amp;beta;</mi> </msup> <mo>+</mo> <msubsup> <mi>k</mi> <mi>i</mi> <mi>&amp;lambda;</mi> </msubsup> </mrow> <msup> <mrow> <mo>(</mo> <msubsup> <mi>d</mi> <mi>i</mi> <mi>o</mi> </msubsup> <mo>+</mo> <msubsup> <mi>k</mi> <mi>i</mi> <mi>&amp;lambda;</mi> </msubsup> <mo>)</mo> </mrow> <mn>2</mn> </msup> </mfrac> </mrow> </mtd> <mtd> <mrow> <mn>0</mn> <mo>&lt;</mo> <msubsup> <mi>d</mi> <mi>i</mi> <mi>o</mi> </msubsup> <mo>&lt;</mo> <msup> <mi>&amp;gamma;</mi> <mi>&amp;beta;</mi> </msup> </mrow> </mtd> </mtr> <mtr> <mtd> <mn>0</mn> </mtd> <mtd> <mrow></mrow> </mtd> </mtr> </mtable> </mfenced> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>14</mn> <mo>)</mo> </mrow> </mrow>
Wherein,
Wherein:fi oFor the active force between obstacle O and unmanned plane i, by the position P of unmanned plane i and obstacle Oi、POWith speed vi、vO Determine, the method for decision:Represent the action direction of the active force, be unit direction vector, Fi OFor the size of the active force, By the position P of unmanned plane i and obstacle Oi、POSolved according to (14) formula, the distance between unmanned plane i and obstacle OSeparately by the speed v of unmanned plane i and obstacle Oi、vOThe active force of generation is second on the right side of equal sign in (13) formula ;γβWarning distance between unmanned plane i and barrier O,For apart from adjustment parameter,For unmanned plane i and obstacle O it Between repulsion intensity adjustment coefficient,Rate uniformity control coefrficient between unmanned plane i and obstacle O, And γβAn initial value can be first given, then is further adjusted in system experimentation.
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Families Citing this family (37)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN107807671B (en) * 2017-11-27 2018-08-14 中国人民解放军陆军工程大学 Unmanned plane cluster danger bypassing method
CN108415425B (en) * 2018-02-08 2020-10-30 东华大学 Distributed swarm robot cooperative clustering algorithm based on improved gene regulation and control network
CN108279704B (en) * 2018-02-09 2021-05-04 沈阳航空航天大学 Cooperative control strategy for multiple unmanned aerial vehicles with increased communication links
CN108398960B (en) * 2018-03-02 2021-01-26 南京航空航天大学 Multi-unmanned aerial vehicle cooperative target tracking method for improving combination of APF and segmented Bezier
CN108388270B (en) * 2018-03-21 2021-08-31 天津大学 Security domain-oriented cluster unmanned aerial vehicle trajectory attitude cooperative control method
CN108549407B (en) * 2018-05-23 2020-11-13 哈尔滨工业大学(威海) Control algorithm for multi-unmanned aerial vehicle cooperative formation obstacle avoidance
CN108762300A (en) * 2018-05-31 2018-11-06 智飞智能装备科技东台有限公司 A kind of ground for the flight of unmanned unit controls programing system
CN109000653B (en) * 2018-06-06 2020-05-05 西南交通大学 Intelligent optimization method for multi-dimensional space multi-carrier path
CN110737212B (en) * 2018-07-18 2021-01-01 华为技术有限公司 Unmanned aerial vehicle control system and method
CN109062252B (en) * 2018-08-27 2021-05-25 中国人民解放军战略支援部队航天工程大学 Four-rotor unmanned aerial vehicle cluster control method and device based on artificial potential field method
CN108983825B (en) * 2018-09-30 2020-04-03 北京航空航天大学 Tracking method and system for time-varying formation of unmanned aerial vehicle
CN109445459B (en) * 2018-10-25 2019-10-15 中国人民解放军战略支援部队航天工程大学 Unmanned plane cluster formation control method and its device
CN109116868B (en) * 2018-10-31 2021-07-13 中国人民解放军32181部队 Distributed unmanned aerial vehicle formation cooperative control method
CN109557936B (en) * 2018-12-03 2020-07-07 北京航空航天大学 Anti-collision control method between erectable unmanned aerial vehicles based on artificial potential field method
CN111352435B (en) * 2018-12-20 2021-07-16 中国科学院沈阳自动化研究所 Unmanned aerial vehicle formation autonomous aerial refueling method
CN109460064B (en) * 2019-01-03 2019-11-15 中国人民解放军战略支援部队航天工程大学 Unmanned plane cluster regions covering method and its device based on virtual potential field function
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CN110502032B (en) * 2019-08-31 2021-10-26 华南理工大学 Unmanned aerial vehicle cluster formation flying method based on behavior control
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CN114115341B (en) * 2021-11-18 2022-11-01 中国人民解放军陆军工程大学 Intelligent agent cluster cooperative motion method and system
CN114980024B (en) * 2022-06-28 2023-10-13 安徽大学 Communication node unmanned aerial vehicle network deployment method based on discrete seed optimization algorithm
CN117608318B (en) * 2024-01-23 2024-04-09 北京航空航天大学 Unmanned aerial vehicle formation obstacle avoidance control method and system based on bird-like phototaxis

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101694587A (en) * 2009-10-13 2010-04-14 清华大学 Cluster control system applied to microminiature aircrafts
CN102393747A (en) * 2011-08-17 2012-03-28 清华大学 Collaborative interaction method for unmanned plane cluster and visual navigation system of unmanned plane
CN102707693A (en) * 2012-06-05 2012-10-03 清华大学 Method for building spatio-tempora cooperative control system of multiple unmanned aerial vehicles
CN103197684A (en) * 2013-04-25 2013-07-10 清华大学 Method and system for cooperatively tracking target by unmanned aerial vehicle cluster

Family Cites Families (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
FR2881849B1 (en) * 2005-02-04 2007-04-06 Airbus France Sas METHOD AND DEVICE FOR CONTROLLING A PLANE IN BLANK
AU2011326330B2 (en) * 2010-11-08 2014-12-18 Ezymine Pty Limited A collision avoidance system and method for human commanded systems
CN104155998B (en) * 2014-08-27 2017-08-25 电子科技大学 A kind of path planning method based on potential field method
JP5775632B2 (en) * 2014-09-16 2015-09-09 株式会社トプコン Aircraft flight control system
JP2016079918A (en) * 2014-10-17 2016-05-16 グレースマリー・ワールド株式会社 Space propulsion system and space staying [space staying over stratospheric] system and the like
CN105549617B (en) * 2016-01-13 2019-05-03 北京航空航天大学 A kind of unmanned plane formation control method of imitative swarm behavior and virtual architecture
CN105912004B (en) * 2016-06-23 2018-06-26 北京理工大学 Unmanned plane it is autonomous at a high speed warship auxiliary system and method

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101694587A (en) * 2009-10-13 2010-04-14 清华大学 Cluster control system applied to microminiature aircrafts
CN102393747A (en) * 2011-08-17 2012-03-28 清华大学 Collaborative interaction method for unmanned plane cluster and visual navigation system of unmanned plane
CN102707693A (en) * 2012-06-05 2012-10-03 清华大学 Method for building spatio-tempora cooperative control system of multiple unmanned aerial vehicles
CN103197684A (en) * 2013-04-25 2013-07-10 清华大学 Method and system for cooperatively tracking target by unmanned aerial vehicle cluster

Non-Patent Citations (5)

* Cited by examiner, † Cited by third party
Title
brief paper distributed cooperative control for deployment and task allocation of unmanned aerial vehicle networks;Hu J;《IET Control Theory & Applications》;20131231;第7卷(第11期);第1574-1582页 *
Collective memory and spatial sorting in animal groups;Couzin I D,等;《 Journal of theoretical biology》;20021231;第218卷(第1期);第1-11页 *
UAV集群自组织飞行建模与控制策略研究;孙强,等;《系统工程与电子技术》;20160731;第38卷(第7期);摘要、第1650-1653页 *
基于多agent系统的大规模无人机集群对抗;罗德林,等;《控制理论与应用》;20151130;第32卷(第11期);第1498-1504页 *
基于规则的无人机集群运动控制;景晓年,等;《计算机仿真》;20160930;第33卷(第9期);第50-54页 *

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