CN103777640B - A kind of distributed control unmanned aerial vehicle group is concentrated sub-clustering formation method - Google Patents

A kind of distributed control unmanned aerial vehicle group is concentrated sub-clustering formation method Download PDF

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CN103777640B
CN103777640B CN201410017265.2A CN201410017265A CN103777640B CN 103777640 B CN103777640 B CN 103777640B CN 201410017265 A CN201410017265 A CN 201410017265A CN 103777640 B CN103777640 B CN 103777640B
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formation
task
bunch
aerial vehicle
unmanned aerial
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CN103777640A (en
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王磊
颜嵩林
王艳风
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北京航空航天大学
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Abstract

The invention provides a kind of distributed control unmanned aerial vehicle group and concentrate sub-clustering formation method, comprise the following steps: 1, determine in task chain each task unmanned aerial vehicle group task character and determine feasible unmanned plane formation form according to flight environment of vehicle; 2, from feasible formation form, unmanned aerial vehicle group is created to the preferential collection of the optimization of forming into columns modeling, determine that according to different task objects the static state of each task or dynamic optimization preferentially collect; 3, from the formation mode of static optimization collection or dynamic optimization collection, select the OPTIMAL TASK formation or the suboptimum task formation that meet performance indications according to the optimization index of task. By method of the invention process can be efficiently, intelligence, convert and select flexibly the cooperation formation of unmanned aerial vehicle group, there is safety, stable, advantage reliably.

Description

A kind of distributed control unmanned aerial vehicle group is concentrated sub-clustering formation method

Technical field

The present invention relates to formation is bunch centralized multitask unmanned aerial vehicle group evolution and a control field, outstandingIt relates to a kind of distributed control unmanned aerial vehicle group and concentrates sub-clustering formation method.

Background technology

Unmanned plane is operational weapon important in modern war, can replace within the specific limits and have man-machine holdingRow Various Complex and dangerous task, but in future war, only depend on the autonomous operation of single frame unmanned plane cannotAdapt to complicated battlefield surroundings. Form into columns to complete and appoint and possess effectively collaborative tactful unmanned planeBusiness. Because the unmanned aerial vehicle group that multiple UAVs forms can reduce overall flight resistance, unmanned aerial vehicle group is existedPneumatic efficiency, strike effect, success rate, reconnaissance range and evade probability and all have lifting. From but unmannedA group of planes can and have relative large scope of activities in execution complex task, multitask, appoint under complex environmentBe engaged in probability and protection. But when carrying out various different task, unmanned aerial vehicle group can exist formation to selectWith task index optimization problem. First,, when unmanned aerial vehicle group is carried out different task, different formations are selected not onlyCan affect the implementation effect of this task, and can produce extra effect to next task in task chain.Particularly, in the time that the same area is carried out different tasks, evolution can make group of planes security carry timelyHeight, can also promote the execution efficiency of task. Secondly, become for some bursts, extra event formationChanging is necessary, important sometimes. But existence and each task optimization that the formation of each task is optimizedOptimization relation with task entirety; The formation control of forming into columns for distributed control, fixed structure is along with appointingWhether the execution of business exists can carry out constantly dynamically adjusting is optimized that to form the preferential collection of dynamic optimization be also currentKey issue. Therefore unmanned aerial vehicle group formation becomes the key of can not ignore on the impact of various different tasksOne of problem.

The control of task to unmanned plane flight pattern is only simply considered in early stage more research, main workGenerally that under the each task condition of supposition a group of planes is taking every unmanned plane as a node, or with lead aircraft, officialMachine form is carried out formation control, but planning in advance to known task target, thereby unmanned aerial vehicle group is existedIn task, keep some index optimization, for example voyage maximizes etc. Unmanned aerial vehicle group formation control at present,Evolution mainly concentrates on the research direction that unit is considered separately, is cluster point side from single frame unmanned planeFace considers the division of task character to be fixed or the routeing of semifixed formation; On the other hand onlyNeed to finish the work and carry out the co-ordination of formation for length, wing plane double-click structure, and unmanned aerial vehicle group is dividingEvery bunch of cloth control, concentrates the feasibility realizing under this united state of forming into columns less with optimization research in bunch.

Summary of the invention

The present invention one of is intended to solve the problems of the technologies described above at least to a certain extent or at least provides onePlant useful building mode. For this reason, the present invention proposes one and there is security, reliability and operabilityGood distributed control unmanned aerial vehicle group is concentrated sub-clustering formation method, makes the unmanned aerial vehicle group under the method can beExcellent or suboptimum is finished the work. Its technical scheme is as described below:

A kind of distributed control unmanned aerial vehicle group is concentrated sub-clustering formation method, comprises the following steps:

1) initial parameter of setting unmanned aerial vehicle group, as group of planes quantity, unmanned plane performance etc.; Determine unmannedThe task character of each subtask in the task chain of a group of planes, and determine that according to flight environment of vehicle unmanned aerial vehicle group is at each sonPermission formation form in task, tentatively forms static optimization and preferentially collects;

2) to described unmanned aerial vehicle group, the permission formation form in each subtask is carried out modeling, determines eachPlant the corresponding network topology structure of formation form, draw in described task chain every under the environment of each subtaskPreplanned mission configuration and the topological model of bunch unmanned plane, and therefrom set up formation conversion mathematical form, every bunchDifferent can the having a significant impact selection mode and the conversion regimes of forming into columns of task character, then from entirety toOptimum or suboptimum formation control strategy are taked to the formation form of unmanned aerial vehicle group in part;

3), in the time that emergency case appears in certain subtask, the preferential collection of static optimization is reconstructed, is expandedOr shrink, and select other effective formation forms, preferentially collect thereby form dynamic optimization.

In step 1), the preferential collection of described static optimization comprises that project has: the unmanned plane that task character is definiteBunch point of group, the concrete function of every bunch and mobility, rapidity, a group of planes, connect topology, topology becomesChange strategy.

Further, every bunch of unmanned aerial vehicle group is the mixed of submanifold that task character is single or many character compositionCluster, wherein the concrete function of every bunch comprises: I, target detecting; II, fire cover; III, motor-driven standbyWith; IV, interference and counter-measure; V, formation coordination and control; VI, bunch point shift; VII, taskThe emergent distribution of formation of middle emergency case.

The formation control of described unmanned aerial vehicle group is coordinated to control by every bunch, the wherein communication of control signal, formationStrategy can be subject to the restriction of formation topological sum formation sequence; For the emergent plan of adjusting of the formation that has emergency caseSlightly, each bunch of non-central unmanned plane also can participate in controlling and coordinating, and the concrete formation of every bunch can be subject to static preferentialThe disaggregation restriction of level; When structure dynamic optimization preferentially collects, directly informational linkage of nothing between some node, because ofThis can only comprise that forming static state preferentially concentrates some formations, and the preferential collection of dynamic optimization is generally that static optimization is excellentThe first subset of collection; In every bunch bunch, adopt centralized formation method, bunch center bunch in shift by bunch in each nothingThe man-machine specific tasks according to distribution participate in coordinating to determine jointly.

The formation control coodination modes of described unmanned aerial vehicle group comprises: I, same task function are coordinated; II, machineMoving coordination for subsequent use; Between III, different task, function conversion is coordinated;

For every bunch of formation mode that comprises multiple-task character, first by bunch in unmanned plane divide by functionLayer is: I, center key-course; II, goal task enforcement bunch, as target striking type task can be chosen orderMark strike bunch is the second layer; III, fire cover bunch; IV, interference and counter-measure bunch; V, target detecting;VI, motor-driven for subsequent use; Secondly, center key-course preferentially bunch in carry out task coordinate and process static optimizationThe formation of preferential collection is distributed; Again, center key-course can call from low to high with the unmanned plane of high preferential layerMotor-driven for subsequent use until center key-course, thus process fast the dynamic preferential collection of optimizing, reach function withThe reliable conversion of formation; Finally except center key-course emergency processing emergency case, the function of not bypassing the immediate leadershipShift at conversion and control He Cu center;

Every bunch only comprises the formation mode of single task role character, according to task character by each bunch of coordination after by toolBody task is distributed to every bunch, and the center machine in every bunch bunch can be specified flexibly, and adopts multi-zone supervision, alsoCan adopt parallel coordination mode process bunch in each unmanned plane task object;

Task character is single each bunch, bunch between coordinate preferentially in same nature each bunch carry out; TaskMatter blend together bunch bunch between Task Switching coordinated to control by formation and each bunch and determine.

The method that forms the preferential collection of dynamic optimization in step 3) is as described below: when the each subtask of task chain energyWhen enough independent, optimize and carry out according to each subtask, only task is carried out to static optimization; In the time existingBetween require or formation require time, according to the predistribution mode planning dynamic priority collection of every bunch; To urgent feelingsThe formation processing of condition need to have each Cu Hegecu center joint coordination of direct correlation, becomes according to formation topologyChanging minimum is similarity degree maximum before and after formation changes, the shortest, each bunch of congeniality task of each bunch of displacementBetween preferentially convert, have direct link bunch point to change order carry out.

According to method shown in the present, can make unmanned aerial vehicle group under the method to reach with corresponding formationTo concrete optimization index or answer suboptimum form to finish the work.

Part of the present invention is optimized form can guarantee that some task index of task obviously improves, from thisIn bright concrete example or practice thus, can confirm mutually.

Brief description of the drawings

Fig. 1 is the flow chart that distributed control unmanned aerial vehicle group of the present invention concentrates sub-clustering formation to build;

Fig. 2 is task chain formation control flow chart of the present invention;

Fig. 3 is that the group of planes that in the present invention, unmanned aerial vehicle group sub-clustering is formed into columns preferentially collects structure flow chart;

Fig. 4 is unmanned aerial vehicle group evolution flow chart in the present invention;

Fig. 5 a is the topological structure conversion embodiment 1 of evolution in the present invention;

Fig. 5 b is the topological structure conversion embodiment 2 of evolution in the present invention.

Detailed description of the invention

Describe concrete illustrated embodiment of the present invention below in detail, respective flow chart and structure are all aobvious in the accompanying drawingsShow. Wherein identical or similar label represents identical or similar part or has from start to finishThe assembly of identical or similar functions. Below by describing the example of accompanying drawing representative, as just the partyThe referential of method for example, only for explaining the present invention, and can not be interpreted as limitation of the present invention.

Below openly provide a kind of specific concrete example to be described method of the present invention, Jin JinshiFor more in detail significantly, to of the present invention open, but this kind of concrete example of simplifying be as just example,Can not be limited to this example. The disclosed method of the present invention can provide many different examples and example to be used for realityThe existing corresponding structure of the present invention, model, assembly wherein and description is set; And corresponding popularizationObject does not lie in restriction the present invention. In addition, the example in the present invention can be extended to all the other different examplesIn corresponding numeral or alphabetical, this kind taking optional network specific digit or letter representation only for simplification with know order, can or itself not indicate the relation between discussed example essence or setting as restriction.Various special processes in example involved in the present invention and material be that those of ordinary skill in the art commonly use,Common technological means.

In description of the invention, except special annotation, its term is broad understanding, as: network topologyIn connection and instruction information interaction, can be various possible contacts or connected mode, can be straightConnect letter or by means communications such as ground, satellites, understand the tool of above-mentioned term in example depending on concrete conditionBody implication.

Can more clear and intuitive understanding concrete example of the present invention with explanation with reference to accompanying drawing and following descriptionCorresponding aspect. In concrete example, only use that some are concrete, specific embodiment shows this inventionPrinciple and feasibility, but these should not serve as limitation of the present invention, on the contrary, of the present inventionly specifically showDerivative in example, comprise all conversion within the scope of spirit and the intension that falls into additional claims,Amendment and equivalent.

The distributed control that detailed below with reference to accompanying drawings description shows according to the specific embodiment of the inventionUnmanned aerial vehicle group is concentrated sub-clustering formation modeling and construction method.

The distributed control unmanned aerial vehicle group of one as shown in Figure 1 concentrate sub-clustering formation construction method comprise asLower step:

Step e 101, judges that according to task character and unmanned aerial vehicle group flight environment of vehicle the permission of unmanned aerial vehicle group is compiledFormation formula.

In other document examples, the Collaborative Control that unmanned aerial vehicle group is formed into columns is only considered the same area notCarry out disposable formation control with task, and be confined to the path planning aspect of target detecting, example whereinHandset group's unmanned plane negligible amounts, target strike behavior is independent action, as document: based on multitaskThe research of unmanned plane formation control; Or only according to the same task of zones of different, be generally target hit orThe path plannings such as target detecting, the highest path optimization of middle index security etc. cruises. But to unmannedGroup of planes sub-clustering is formed into columns in every bunch containing the formation conversion of multiple UAVs, particularly has appointing of formation sequence restrictionBusiness formation study on the transformation is less. In this paper example, formation is collaborative includes but not limited to unmanned with conversion projectIn the centralized sub-clustering pattern of a group of planes, every bunch is single task role character, also can every bunch the nothing that is multiple task charactersMan-machine hybrid system, can independently also can be associated between task; Or in these two kinds of structures conversion orPerson's local transitions is carried out the different task, the pop-up mission etc. that are associated. Here mainly to unmanned aerial vehicle group sub-clusteringFormation mode is studied and is built. Comprise the function setting of task to every cluster, form into columns at task chainFeasibility in each task, a group of planes corresponding topological structure of forming into columns. Further concrete bunch of formation shape of unmanned aerial vehicle groupFormula mainly contains: fixing and free formation mode; Control structure adopts fixing formation and layering in the present inventionFormula structure. Bunch function setting comprises: Task Assigned Policy, adjust strategy, function switching strategy, formationTransduction pathway selection strategy, formation optimisation strategy etc. Collaborative Control part is that entirety is controlled formation adjustment sideFace, preferentially collects mainly for static formation optimization; Specifically comprise: unmanned aerial vehicle group task landform formation limitSystem, group of planes formation topological structure build and task overall arrangement.

Step e 102 is listed all feasible formation forms according to optimizing collection from the each subtask of task chain,And thus unmanned aerial vehicle group is formed into columns and carried out modeling, determine the network topology knot that each formation mode is correspondingStructure, thus can show that the preplanned mission of every bunch of unmanned plane under described task environment configures and topological model,And therefrom set up formation and change mathematical form. (research of routeing key technology, base in other documentsIn the Path Planning for Unmanned Aircraft Vehicle of space decomposition network, the tight flight pattern of unmanned plane forms to be controlled, unmanned planeInvestigation routeing, Path Planning for Unmanned Aircraft Vehicle, Path Planning for Unmanned Aircraft Vehicle problem Primary Study), manyUnmanned plane formation form is mainly to single task role, and as the shortest in voyage is the path planning of index; Only document " baseIn the unmanned plane formation control research of multitask " mention multitask, but its example is only for reconnaissance phaseFormation is optimized, and the formation of single frame unmanned plane composition is only discussed, and attack part be subsequently each unmannedMachine is independently executed the task. First the model that the present invention builds is to be based upon on sub-clustering formation mode, whereinIgnore concrete control system, in multitask, each task is all carried out formation control, and it is overall to carry out task chainWith local optimum.

Step e 103, sets up corresponding formation optimisation strategy according to every bunch of unmanned plane of task setting, andAccording to limiting factors such as formation sequences between task chain, formation optimization collection is screened, thereby further can comply withFrom entirety to part, take optimum or suboptimum formation control plan according to preplanned mission variant in task chainSlightly. A group of planes specifically can take the control of overall distribution formula, bunch in centralized Control (main You Cu center realize)Be subject to the evolution control model of formation sequence restriction overall formation is coordinated to control. For notSame task chain can adopt different reasonable control modes from entirety to part, as single task roles such as detectingsThe overall tasks of matter, in its task chain, each subtask is all detecting character, therefore optimization aim can be from entiretyBe set as voyage and minimize lower routeing, now application distribution control just can finish the work require teamShape configuration. But different for task character, as contained many character tasks such as detecting, early warning, strike, supportTime, need entire and part, centralized and distributed dual control flight pattern is optimized, distributedControlling function is the optimization of unmanned aerial vehicle group task chain, the formation that when task character is complicated, task entirety limitsWith adjustment mode; Centralized control functions is that each bunch of task character set adjustment; The restriction of formation sequence is in officeWhen the each task evolution of business chain, provide, alternative condition can limit formation and adjust strategy.

With reference to Fig. 2, a kind of distributed control unmanned aerial vehicle group concentrates sub-clustering formation control structure to comprise:

Task chain and formation sequence limiting module, for unmanned aerial vehicle group overall task planning and formation restriction because ofElement judgement;

Task chain integrated planning is optional formation under set task, as worked as region, the each subtask of task chain phaseApart from far away, even if there is other local task optimization formations, but for ensureing at certain bullet-loading capacity or fuel oilUnder prerequisite, can only preferentially select fuel-saving type formation; The restriction planning of formation sequence comprise when in task chain certain twoIndividual or multiple tasks, have communication delay or the transmission limiting factor such as interference and cannot normally carry out formationAdjust, need that target is in advance carried out to feasible formation mode and add formation sequence restriction planning.

Space planning and task character module, for the feasible formation judgement of unmanned aerial vehicle group. Task character can be pre-First set or provide in advance, as with detecting, detect+cruise, detect+when the mission modes such as firepower attack toDetermine every bunch of task of a group of planes and feasible formation. Space planning comprises the environmental limitations in tasks carrying region, isNoly have high mountain or execute the task in valley etc., these all limit to some extent to the selection of formation. Work as taskThat carry out detection task or Strike task in valley time, loose rank formation must be can notThe formation mode of realizing, also there is impact to forming into columns in task character and space boundary therefore.

Control section, preferentially collects for forming formation from feasible formation, thus the entirety of selection or localThe formation mode of optimum, suboptimum.

Wherein, static preferential collection is used for forming into columns and sets up preferential collection, and it comprises space planning and task character ruleDraw, finally form static state corresponding to each subtask and preferentially collect chain, and initial setting task cluster is distributed and teamConversion between when fractal transform bunch, formation sequence limiting module is for task formation restrictive condition incision between task chainChange the emergency processing of planning and emergency case, and feed back actual formation to static preferential collection, thereby filter outThe front-to-back effect of each formation in task chain, finally forms dynamic priority collection.

First by task object in advance, task chain is carried out to preliminary planning and arrangement, can be from known informationDraw geography and the weather condition in the each tasks carrying of task chain area with other data. Can draw like this ringFeasibility formation under the restriction of border; Secondly, according to each task character, as detection task, strike task dispatchingThe task setting that each task is carried out bunch, two are carried out formation static programming thus, form one staticOptimize preferential collection.

The concrete function of every bunch comprises: I, target detecting; II, fire cover; III, motor-driven for subsequent use; IV,Disturb and counter-measure; V, formation coordination and control; VI, bunch point shift; Emergency case in VII, taskEmergent distribution of formation.

The group of planes unmanned plane quantity that appointment is executed the task, provides preferential topological structure, the boat of concentrating each formationJourney, maximum are taken the time of implementation of the unmanned plane technical parameter indexs such as bullet amount, the maximum angle of climb and some task.Task for the fixing time of implementation also should be included static programming part in. Now task module is through space planningWith task character module, can provide a static optimization by each bunch of coordination of distributed control model preferentialCollection.

The formation control of described unmanned aerial vehicle group is coordinated to control by every bunch, and the concrete formation of every bunch is subject to static optimizationThe disaggregation restriction of priority, adopts centralized formation method in every bunch bunch, bunch center bunch in shift by bunchInterior each unmanned plane participates in coordinating to determine according to the specific tasks of distributing jointly.

Due to dynamically formation variation and pop-up mission, task chain node task character variation, static preferentialCollection has direct relation. Therefore need to contact directly each bunch of Dian Yucunei center unmanned plane excellent to static state constantlyChanging collection carries out order adjustment and upgrades. Select or front and back task for last task formation in time seriesIt is that empty this class situation can be concentrated and select optimization formation in dynamic priority that static preferential collection formation is occured simultaneously, then sentencesWhether disconnected this formation before and after also meeting static preferential collection or formation sequence restriction demand; And for burst feelingsCondition generally can only be concentrated and adopt suboptimum formation in dynamic priority, because now optimum formation is difficult to meet burstSituation mission requirements.

In an embodiment of the present invention, as the method for building up of the preferential collection of Fig. 3 unmanned aerial vehicle group comprises following stepRapid:

A1) determine task environment and task character;

A2) set up unmanned plane state, comprise that bullet-loading capacity, the maximum angle of climb, ultimate run, minimum flyIn line height, minimum flying distance, maximum angle of turn, flight environment of vehicle task object enemy threaten etc.;

A3) set static formation optimization collection by task character, space environment and unmanned plane state;

A4) arrange static optimization collection by each task index;

A5) add formation sequence to limit expansion, adjustment or the selection to static optimization collection;

A6) carrying out the each subtask of task global optimization or task chain optimizes;

A7) flight formation is carried out to corresponding formation control and reach correct formation form.

Wherein, steps A 5) in formation sequence limiting factor add static preferential collection, it is converted intoDynamic priority collection. The objective optimization of the final formation of unmanned aerial vehicle group just from dynamic priority concentrate select optimum orSuboptimum formation. Some technical indicators that objective optimization is generally task starts front appointment, as the shortest in air route,Unmanned plane minimum number in a group of planes, bullet-loading capacity is minimum or safety coefficient is the most high, therefore optimizes collection uniqueAnd bounded.

As shown in Figure 4, steps A 5) can also turn in detail following flow process:

A51) start containing the overall task of formation sequence limiting factor;

A52) judge between the task chain of overall task and affected by formation sequence; If so, enterEnter described steps A 53); If not, enter steps A 6);

A53) judge that limiting factor preferentially collects impact to static state; If had, enter described steps A 54),If not, enter steps A 6);

A54) judge that dynamic priority integrates whether as empty set; If so, keep former formation, described in enteringSteps A 7); If not, enter steps A 6);

Various limiting factors described in the present invention can not make the dynamic priority of all tasks integrate as empty set.

Modeling part is for the concrete model determining objective optimization collection.

This segment set has suffered the optional modeling process of formation conversion, comprises the static preferential collection model and moving of optimizingState optimization collection model. The collaborative formation model of concrete unmanned plane can be selected according to actual conditions. Below will be in detailCarefully discuss the static path planning model taking optimal-fuel as target and have dynamically appointing of formation sequence restrictionMentality of designing and the modelling application example of business apportion model.

Static path planning modeling and algorithm are selected:

Consider 5 node topologies as shown in Figure 5 a, each node represents one bunch. Depending on every cluster conductA set, establishes its motor pattern and is: ri, wherein r i = x i y i z i Represent the position of i bunch, establish coordinateInitial point is the center bunch (No. 3 nodes) of forming into columns, and v is every bunch of unmanned plane speed, θ,For every bunchCenter course heading relatively, θ is course angle,For the angle of pitch. SoIf flyMachine is formed into columns as in same plane inner conversion formation, constructs static preferential collection path planning. Can be excellent in static stateChange and concentrate each bunch of unmanned plane while finding out evolution to change the shortest path L of distancemin,Wherein lijFor the distance of bunch exchange, s is the topological node that needs conversion. If cost J, task are optimized in air routeThe topological matrix that the each task of chain is possible is κn={Sij, i, j=1,2 ..., 5; For there being m subtask,The minimum of a value of cost is optimized in its air routeωnThe evolution of expression task is feasibleProperty; Work as ωn, represent that the each subtask of n does not exist the formation that can convert at=0 o'clock; Work as ωnWithin=1 o'clock, representThis kind of formation is the optimum disposable formation in the each subtask of n.

Fly to from the outset first task object and generally can adopt any formation, but consider combustion in-flightOil is economized and first task most, should select to meetAndInitial teamShape.

If the task of cruising that first subtask is GENERAL TYPE, economizes according to fuel oil most, start a group of planes and can adopt VFont formation; In topology, represent 0 ° and 90 ° of adjacent cluster with " ± 1 ", as each in column bunch is 90 °, " ±2 " ± 30 ° of expressions are adjacent, and " ± 3 " represent ± 45 °, and " ± 4 " represent ± 60 °, and " ± 5 " representAll the other are not more than 90 ° of angles; ?

κ 0 = 0 - 2 0 0 0 - 2 0 - 2 1 0 0 - 2 0 2 0 0 1 2 0 2 0 0 0 2 0 , First task adopts line of wedge κ 1 = 0 1 - 2 0 0 1 0 2 2 0 - 2 2 0 0 0 0 2 0 0 2 0 0 0 2 0 ,

In the time that second task is detecting, search, I: adopt rank without landform restriction on a large scale; II: haveLandform restriction adopts column; If limit without landform in this example, due toCan adopt rank,? κ 2 = 0 0 - 5 0 0 0 0 - 5 5 0 - 5 - 5 0 0 0 0 5 0 0 5 0 0 0 0 0 .

When the 3rd task is the offensive task of target, I: general attack adopts trapezoidal formation; II: rightGround attacks and adopts wedge shape or column; III: point, line target adopt diamond formation; If enter in example of the present inventionThe task of attacking is generality while attacking over the ground, can from I, II, select, and considersWith the team of making a return voyageShape, thus line of wedge should be adopted, κ 3 = 0 1 - 2 0 0 1 0 2 2 0 - 2 2 0 0 0 0 2 0 0 2 0 0 0 0 0 , ω in above-mentioned taskn=1,n=1,...,3,Thereby cost function J min = min { Σ n = 1 3 κ n · ω n } .

The conventional algorithm of present stage path planning is divided into traditional classical algorithm and modern algorithm, mainly contains derivativeCorrelation method, method in optimal control, optimizing search, genetic algorithm, artificial neural network etc., all visual conditionsUse. Here can adopt based on Voronoi graph search method, task chain tasks carrying region planePath planning is divided in region.

5 node topologies shown in Fig. 5 b are discussed, because under this condition there is the restriction of formation sequence in task, because ofThisNot necessarily there is bunch the shortest evolution of displacement, cost function in taskωnThere will be ωn=0 situation, as: task, landform restriction can be to rank, circle in mountain valley etc.Shape formation produces restriction, or formation conversion has requirement to convert just formation restriction of column to rank. At thisIn topology, establish between second and third task and have formation sequence conversion restriction, the 3rd task is for there being landform restrictionTask, task two is detection task, task three is ground task of bombing, does not now exist task chainExcellent formation is changed, and considers the suboptimum formation of the task of taking into account two, three, still adopts V font while taking offForm into columns, κ 0 = 0 - 2 0 0 0 - 2 0 - 2 1 0 0 - 2 0 2 0 0 1 2 0 2 0 0 0 2 0 , While carrying out first task, adopt line of wedge κ 1 = 0 1 - 2 0 0 1 0 2 2 0 - 2 2 0 0 0 0 2 0 0 2 0 0 0 2 0 , Then be the reaching of guarantee task, consider two, three task characters withRestrictive condition, adopts column can adapt to multiple-task form and comprises in ground attack, detecting and cloud and returningDeng, κ 2,3 = 0 - 1 - 1 0 0 - 1 0 0 - 1 0 - 1 0 0 0 0 0 - 1 0 0 - 1 0 0 0 - 1 0 , While making a return voyage, still continue to use line of wedge. Cost corresponding to model thusFunctionIt is the suboptimal solution under condition restriction.

Algorithm is the same with upper example still can be used based on Voronoi graph search method, but the region in figure is dividedNeed to meet restrictive condition.

According to the method for the embodiment of the present invention, can preferentially improve the security of unmanned aerial vehicle group, and can be excellentChange task index, has efficient, stable and reliable advantage.

Should be appreciated that each several part of the present invention can realize with hardware, software or their combination. ThisThe those of ordinary skill of technical field is appreciated that realizes all or part of that above-described embodiment method carriesStep is can carry out the hardware that instruction is relevant by program to complete, and described program can be stored in a kind of meterIn calculation machine readable storage medium storing program for executing, this program, in the time carrying out, comprises one of step of embodiment of the method or its groupClose. Storage medium can be read-only storage, disk or CD etc.

Although illustrated and described embodiments of the invention, for those of ordinary skill in the art andSpeech, is appreciated that without departing from the principles and spirit of the present invention and can carries out these embodimentMultiple variation, amendment, replacement and modification, scope of the present invention is by claims and be equal to and limit.

Claims (5)

1. distributed control unmanned aerial vehicle group is concentrated a sub-clustering formation method, comprises the following steps:
1) set the initial parameter of unmanned aerial vehicle group, determine appointing of each subtask in the task chain of unmanned aerial vehicle groupBusiness character, and determine the permission formation form of unmanned aerial vehicle group in each subtask according to flight environment of vehicle, preliminaryForming static optimization preferentially collects;
2) to described unmanned aerial vehicle group, the permission formation form in each subtask is carried out modeling, determines eachPlant the corresponding network topology structure of formation form, draw in described task chain every under the environment of each subtaskPreplanned mission configuration and the topological model of bunch unmanned plane, and therefrom set up formation conversion mathematical form, thenFrom entirety to part, the formation form of unmanned aerial vehicle group is taked to optimum or suboptimum formation control strategy;
The formation control of described unmanned aerial vehicle group is coordinated to control by every bunch, and the concrete formation of every bunch is subject to static optimizationThe disaggregation restriction of priority, adopts centralized formation method in every bunch bunch, bunch center bunch in shift by bunchInterior each unmanned plane participates in coordinating to determine according to the specific tasks of distributing jointly;
3), in the time that emergency case appears in certain subtask, the preferential collection of static optimization is reconstructed, is expandedOr shrink, and select other effective formation forms, preferentially collect thereby form dynamic optimization.
2. distributed control unmanned aerial vehicle group according to claim 1 is concentrated sub-clustering formation method, itsBe characterised in that: step 1) in, the preferential collection of described static optimization comprises that project has: task character is determinedBunch point of unmanned aerial vehicle group, the concrete function of every bunch and mobility, rapidity, a group of planes, connect topology,Topological transformation strategy.
3. distributed control unmanned aerial vehicle group according to claim 2 is concentrated sub-clustering formation method, itsBe characterised in that: every bunch of blending together for the single submanifold of task character or many character composition of unmanned aerial vehicle groupBunch, wherein the concrete function of every bunch comprises: I, target detecting; II, fire cover; III, motor-driven for subsequent use;IV, interference and counter-measure; V, formation coordination and control; VI, bunch point shift; Prominent in VII, taskThe emergent distribution of formation of the condition of oestrusing.
4. distributed control unmanned aerial vehicle group according to claim 1 is concentrated sub-clustering formation method, itsBe characterised in that: the formation control coodination modes of described unmanned aerial vehicle group comprises: I, same task function are coordinated;II, motor-driven coordination for subsequent use; Between III, different task, function conversion is coordinated;
For every bunch of formation mode that comprises multiple-task character, first by bunch in unmanned plane divide by functionLayer is: I, center key-course; II, goal task enforcement bunch, as target striking type task can be chosen orderMark strike bunch is the second layer; III, fire cover bunch; IV, interference and counter-measure bunch; V, target detecting;VI, motor-driven for subsequent use; Secondly, center key-course preferentially bunch in carry out task coordinate and process static optimizationThe formation of preferential collection is distributed; Again, center key-course can call from low to high with the unmanned plane of high preferential layerMotor-driven for subsequent use until center key-course, thus process fast the dynamic preferential collection of optimizing, reach function withThe reliable conversion of formation; Finally except center key-course emergency processing emergency case, the function of not bypassing the immediate leadershipShift at conversion and control He Cu center;
Every bunch only comprises the formation mode of single task role character, according to task character by each bunch of coordination after by toolBody task is distributed to every bunch, and the center machine in every bunch bunch can be specified flexibly, and adopts multi-zone supervision, alsoCan adopt parallel coordination mode process bunch in each unmanned plane task object;
Task character is single each bunch, bunch between coordinate preferentially in same nature each bunch carry out; TaskMatter blend together bunch bunch between Task Switching coordinated to control by formation and each bunch and determine.
5. distributed control unmanned aerial vehicle group according to claim 1 is concentrated sub-clustering formation method, itsBe characterised in that: step 3) in to form the method for the preferential collection of dynamic optimization as described below: when the each son of task chainWhen task can be independent, optimize and carry out according to each subtask, only task is carried out to static optimization; WhenWhen life period requires or formation requires, according to the predistribution mode planning dynamic priority collection of every bunch; RightThe formation processing of emergency need to have each Cu Hegecu center joint coordination of direct correlation, according to formationChange in topology minimum is similarity degree maximum before and after formation changes, each bunch of the shortest, the each bunch same sex of displacementThe order that preferentially converts, has direct link bunch point to change between matter task is carried out.
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