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简介：Anewbionicapproachispresentedtofindtheoptimaltopologiesofastructurewithtension-onlyorcompression-onlymaterialbasedonboneremodellingtheory.Bytraditionalmethods,thecomputationalcostoftopologyoptimizationofthestructureishighduetomaterialnonlinearity.Toimprovetheefficiencyofoptimization,thereference-intervalwithmaterial-replacementmethodispresented.Inthemethod,firstly,theoptimizationprocessofastructureisconsideredasboneremodellingprocessunderthesameloadingconditions.AreferenceintervalofStrainEnergyDensity(SED),correspondingtothedeadzoneorlazyzoneinbonemechanics,isadoptedtocontroltheupdateofthedesignvariables.Secondly,amaterial-replacementschemeisusedtosimplifytheFiniteElementAnalysis(FEA)ofstructureinoptimization.Intheoperationofmaterial-replacement,theoriginaltension-onlyorcompression-onlymaterialindesigndomainisreplacedwithanewisotropicmaterialandtheEffectiveStrainEnergyDensity(ESED)ofeachelementcanbeobtained.Finally,theupdateofdesignvariablesisdeterminedbycomparingthelocalESEDandthecurrentreferenceintervalofSED,e.g.,theincrementofarelativedensityisnonzeroifthelocalESEDisoutofthecurrentreferenceinterval.Numericalresultsvalidatethemethod.

简介：OptimalformationreconfigurationcontrolofmultipleUninhabitedCombatAirVehicles(UCAVs)isacomplicatedglobaloptimumproblem.ParticleSwarmOptimization(PSO)isapopulationbasedstochasticoptimizationtechniqueinspiredbysocialbehaviourofbirdflockingorfishschooling.PSOcanachievebetterresultsinafaster,cheaperwaycomparedwithotherbio-inspiredcomputationalmethods,andtherearefewparameterstoadjustinPSO.Inthispaper,weproposeanimprovedPSOmodelforsolvingtheoptimalformationreconfigurationcontrolproblemformultipleUCAVs.Firstly,theControlParameteri-zationandTimeDiscretization(CPTD)methodisdesignedindetail.Then,themutationstrategyandaspecialmutation-escapeoperatorareadoptedintheimprovedPSOmodeltomakeparticlesexplorethesearchspacemoreefficiently.Theproposedstrategycanproducealargespeedvaluedynamicallyaccordingtothevariationofthespeed,whichmakesthealgorithmexplorethelocalandglobalminimathoroughlyatthesametime.SeriesexperimentalresultsdemonstratethefeasibilityandeffectivenessoftheproposedmethodinsolvingtheoptimalformationreconfigurationcontrolproblemformultipleUCAVs.

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简介：Underwaterrobotisanewresearchfieldwhichisemergingquicklyinrecentyears.PreviousresearchesinthisfieldfocusonRemotelyOperatedVehicles(ROVs),AutonomousUnderwaterVehicles(AUVs),underwatermanipulators,etc.Fishrobot,whichisanewtypeofunderwaterbiomimeticrobot,hasattractedgreatattentionbecauseofitssilenceinmovingandenergyefficiencycomparedtoconventionalpropeller-orientedpropulsivemechanism.However,mostofresearchesonfishrobotshavebeencarriedoutviaempiricalorexperimentalapproaches,notbasedondynamicoptimality.Inthispaper,weproposedananalyticaloptimizationapproachwhichcanguaranteethemaximumpropulsivevelocityoffishrobotinthegivenparametricconditions.First,adynamicmodelof3-joint(4links)carangiformfishrobotisderived,usingwhichtheinfluencesofparametersofinputtorquefunctions,suchasamplitude,frequencyandphasedifference,onitsvelocityareinvestigatedbysimulation.Second,themaximumvelocityofthefishrobotisoptimizedbycombiningGeneticAlgorithm(GA)andHillClimbingAlgorithm(HCA).GAisusedtogeneratetheinitialoptimalparametersoftheinputfunctionsofthesystem.Then,theparametersareoptimizedagainbyHCAtoensurethatthefinalsetofparametersisthe"near"globaloptimization.Finally,bothsimulationsandprimitiveexperimentsarecarriedouttoprovethefeasibilityoftheproposedmethod.

简介：MultipleUninhabitedAerialVehicles(multi-UAVs)coordinatedtrajectoryreplanningisoneofthemostcomplicatedglobaloptimumproblemsinmulti-UAVscoordinatedcontrol.Basedontheconstructionofthebasicmodelofmulti-UAVscoordinatedtrajectoryreplanning,whichincludesproblemdescription,threatmodeling,constraintconditions,coordinatedfunctionandcoordinationmechanism,anovelMax-MinadaptiveAntColonyOptimization(ACO)approachispresentedindetail.Inviewofthecharacteristicsofmulti-UAVscoordinatedtrajectoryreplanningindynamicanduncertainenvironments,theminimumandmaximumpheromonetrailsinACOaresettoenhancethesearchingcapability,andthepointpheromoneisadoptedtoachievethecollisionavoidancebetweenUAVsatthetrajectoryplannerlayer.Consideringthesimultaneousarrivalandtheair-spacecollisionavoidance,anEstimatedTimeofArrival(ETA)isdecidedfirst.ThenthetrajectoryandflightvelocityofeachUAVaredetermined.Simulationexperimentsareperformedunderthecomplicatedcombatingenvironmentcontainingsomestaticthreatsandpopupthreats.Theresultsdemonstratethefeasibilityandtheeffectivenessoftheproposedapproach.