Distributed cooperative control : emerging applications

239 Pages·2017·12.589 MB·English

by  Guo, Yi

DistributedCooperativeControl
Distributed Cooperative Control
EmergingApplications
YiGuo
Thiseditionfirstpublished2017
©2017JohnWiley&Sons,Inc.
Allrightsreserved.Nopartofthispublicationmaybereproduced,storedinaretrievalsystem,or
transmitted,inanyformorbyanymeans,electronic,mechanical,photocopying,recordingor
otherwise,exceptaspermittedbylaw.Adviceonhowtoobtainpermissiontoreusematerialfrom
thistitleisavailableathttp://www.wiley.com/go/permissions.
TherightofYiGuotobeidentifiedastheauthorofthisworkhasbeenassertedinaccordance
withlaw.
RegisteredOffice
JohnWiley&Sons,Inc.,111RiverStreet,Hoboken,NJ07030,USA
EditorialOffice
111RiverStreet,Hoboken,NJ07030,USA
Fordetailsofourglobaleditorialoffices,customerservices,andmoreinformationaboutWiley
productsvisitusatwww.wiley.com.
Wileyalsopublishesitsbooksinavarietyofelectronicformatsandbyprint-on-demand.Some
contentthatappearsinstandardprintversionsofthisbookmaynotbeavailableinotherformats.
LimitofLiability/DisclaimerofWarranty
Thepublisherandtheauthorsmakenorepresentationsorwarrantieswithrespecttotheaccuracy
orcompletenessofthecontentsofthisworkandspecificallydisclaimallwarranties;including
withoutlimitationanyimpliedwarrantiesoffitnessforaparticularpurpose.Thisworkissold
withtheunderstandingthatthepublisherisnotengagedinrenderingprofessionalservices.The
adviceandstrategiescontainedhereinmaynotbesuitableforeverysituation.Inviewofon-going
research,equipmentmodifications,changesingovernmentalregulations,andtheconstantflow
ofinformationrelatingtotheuseofexperimentalreagents,equipment,anddevices,thereaderis
urgedtoreviewandevaluatetheinformationprovidedinthepackageinsertorinstructionsfor
eachchemical,pieceofequipment,reagent,ordevicefor,amongotherthings,anychangesinthe
instructionsorindicationofusageandforaddedwarningsandprecautions.Thefactthatan
organizationorwebsiteisreferredtointhisworkasacitationand/orpotentialsourceoffurther
informationdoesnotmeanthattheauthororthepublisherendorsestheinformationthe
organizationorwebsitemayprovideorrecommendationsitmaymake.Further,readersshould
beawarethatwebsiteslistedinthisworkmayhavechangedordisappearedbetweenwhenthis
workswaswrittenandwhenitisread.Nowarrantymaybecreatedorextendedbyany
promotionalstatementsforthiswork.Neitherthepublishernortheauthorshallbeliableforany
damagesarisingherefrom.
LibraryofCongressCataloging-in-PublicationData
Names:Guo,Yi,1971–author.
Title:Distributedcooperativecontrol:emergingapplications/YiGuo.
Description:Hoboken,NJ,USA:JohnWiley&SonsInc.,2017.|Includesbibliographical
referencesandindex.
Identifiers:LCCN2016041891|ISBN9781119216094(cloth)|ISBN9781119216124(ePub)|
ISBN9781119216100(AdobePDF)
Subjects:LCSH:Automaticcontrol.|Distributedparametersystems.
Classification:LCCTJ215.G862017|DDC629.8/9–dc23
LCrecordavailableathttps://lccn.loc.gov/2016041891
Coverimage:MinaDeLaO/Gettyimages
Setin10/12ptWarnockbySPiGlobal,Pondicherry,India
PrintedintheUnitedStatesofAmerica
10 9 8 7 6 5 4 3 2 1
ToMyParents
KuishengGuoandZhenfuLiu
vii
Contents
Preface xii
AbouttheCompanionWebsite xiv
1 Introduction 1
1.1 MotivationandChallenges 1
1.1.1 FromCollectiveBehaviorstoCooperativeControl 1
1.1.2 Challenges 2
1.2 BackgroundandRelatedWork 4
1.2.1 NetworkedCommunicationSystems 4
1.2.2 CooperatingAutonomousMobileRobots 5
1.2.3 NanoscaleSystemsandLaserSynchronization 7
1.3 OverviewoftheBook 9
References 12
2 DistributedConsensusandConsensusFilters 19
2.1 IntroductionandLiteratureReview 19
2.2 PreliminariesonGraphTheory 22
2.3 DistributedConsensus 26
2.3.1 TheContinuous-TimeConsensusProtocol 26
2.3.2 TheDiscrete-TimeConsensusProtocol 28
2.4 DistributedConsensusFilter 29
2.4.1 PIAverageConsensusFilter:Continuous-Time 30
2.4.2 PIAverageConsensusFilter:Discrete-Time 30
References 31
PartI DistributedConsensusforNetworkedCommunication
Systems 37
3 AverageConsensusforQuantizedCommunication 39
3.1 Introduction 39
3.2 ProblemFormulation 41
viii Contents
3.2.1 AverageConsensusProtocolwithQuantization 41
3.2.2 ProblemStatement 42
3.3 WeightingMatrixDesignforAverageConsensuswith
Quantization 42
3.3.1 StateTransformation 43
3.3.2 DesignforFixedandDirectedGraphs 44
3.3.3 DesignforSwitchingandDirectedGraphs 52
3.4 SimulationsandPerformanceEvaluation 54
3.4.1 FixedandDirectedGraphs 54
3.4.2 SwitchingandDirectedGraphs 55
3.4.3 FixedandDirectedGraphs 56
3.4.4 PerformanceComparison 57
3.5 Conclusion 61
Notes 61
References 62
4 WeightedAverageConsensusforCooperativeSpectrum
Sensing 64
4.1 Introduction 64
4.2 ProblemStatement 67
4.3 CooperativeSpectrumSensingUsingWeightedAverage
Consensus 71
4.3.1 WeightedAverageConsensusAlgorithm 71
4.3.2 FusionConvergencePerformanceinTermsofDetection
Probability 72
4.3.3 OptimalWeightDesignunderAWGNMeasurement
Channels 73
4.3.4 HeuristicWeightDesignunderRayleighFadingChannels 75
4.4 ConvergenceAnalysis 76
4.4.1 FixedCommunicationChannels 76
4.4.2 DynamicCommunicationChannels 79
4.4.3 ConvergenceRatewithRandomLinkFailures 83
4.5 SimulationsandPerformanceEvaluation 87
4.5.1 SUNetworkSetup 87
4.5.2 ConvergenceofWeightedAverageConsensus 88
4.5.3 MetricsandMethodologies 90
4.5.4 PerformanceEvaluation 91
4.6 Conclusion 97
Notes 97
References 97
5 DistributedConsensusFilterforRadioEnvironmentMapping 101
5.1 Introduction 101
5.2 ProblemFormulation 103
Contents ix
5.2.1 SystemConfigurationandDistributedSensorPlacement 103
5.2.2 TheModelandProblemStatement 105
5.3 DistributedREMTracking 106
5.3.1 SystemMatrixEstimation 107
5.3.2 Kalman–EMFilter 108
5.3.3 PIConsensusFilterforDistributedEstimationand
Tracking 109
5.4 CommunicationandComputationComplexity 110
5.4.1 CommunicationComplexity 112
5.4.2 ComputationComplexity 112
5.5 SimulationsandPerformanceEvaluation 113
5.5.1 DynamicRadioTransmitter 113
5.5.2 StationaryRadioTransmitter 116
5.5.3 ComparisonwithExistingCentralizedMethods 116
5.6 Conclusion 118
Notes 119
References 119
PartII DistributedCooperativeControlforMultirobotic
Systems 123
6 DistributedSourceSeekingbyCooperativeRobots 125
6.1 Introduction 125
6.2 ProblemFormulation 126
6.3 SourceSeekingwithAll-to-AllCommunications 127
6.3.1 CooperativeEstimationofGradients 127
6.3.2 ControlLawDesign 128
6.4 DistributedSourceSeekingwithLimitedCommunications 133
6.5 Simulations 135
6.6 ExperimentalValidation 138
6.6.1 TheRobot 138
6.6.2 TheExperimentSetup 140
6.6.3 ExperimentalResults 141
6.7 Conclusion 144
Notes 144
References 144
7 DistributedPlumeFrontTrackingbyCooperativeRobots 146
7.1 Introduction 146
7.2 ProblemStatement 148
7.3 PlumeFrontEstimationandTrackingbySingleRobot 150
7.3.1 StateEquationofthePlumeFrontDynamics 151
7.3.2 MeasurementEquationandObserverDesign 152
x Contents
7.3.3 Estimation-BasedTrackingControl 153
7.3.4 ConvergenceAnalysis 155
7.4 MultirobotCooperativeTrackingofPlumeFront 156
7.4.1 BoundaryRobots 157
7.4.2 FollowerRobots 157
7.4.3 ConvergenceAnalysis 158
7.5 Simulations 160
7.5.1 SimulationEnvironment 160
7.5.2 Single-RobotPlumeFrontTracking 161
7.5.3 MultirobotCooperativePlumeFrontTracking 161
7.6 Conclusion 164
Notes 165
References 165
PartIII DistributedCooperativeControlforMultiagentPhysics
Systems 167
8 FrictionControlofNano-particleArray 169
8.1 Introduction 169
8.2 TheFrenkel–KontorovaModel 170
8.3 Open-LoopStabilityAnalysis 172
8.3.1 LinearParticleInteractions 172
8.3.2 NonlinearParticleInteractions 176
8.4 ControlProblemFormulation 177
8.5 TrackingControlDesign 178
8.5.1 TrackingControloftheAverageSystem 178
8.5.2 StabilityofSingleParticlesintheClosed-LoopSystem 181
8.6 SimulationResults 186
8.7 Conclusion 191
Notes 194
References 195
9 SynchronizingCoupledSemiconductorLasers 197
9.1 Introduction 197
9.2 TheModelofCoupledSemiconductorLasers 198
9.3 StabilityPropertiesofDecoupledSemiconductorLaser 200
9.4 SynchronizationofCoupledSemiconductorLasers 203
9.5 SimulationExamples 207
9.6 Conclusion 209
Notes 209
References 210
Contents xi
AppendixANotationandSymbols 212
AppendixBKroneckerProductandProperties 213
AppendixCQuantizationSchemes 214
AppendixDFiniteL Gain 215
2
AppendixERadioSignalPropagationModel 216
Index 218
xii
Preface
Networkedsystemsaremostfamiliarintheformofdatanetworksconnecting
computers (e.g., Internet) or networks for voice communications. However,
in the broader sense, networks provide the infrastructure for spatially dis-
tributedcomponentsofasystem,ordistributedsystems,tointercommunicate,
enabling powerful capabilities for cooperative and collective behaviors for
the overall system. Such collective behaviors are seen in man-made systems
(e.g.,largepowersystemsandtransportationnetworks)aswellasinnaturally
occurring systems (e.g., flocks of birds, clusters of biological organisms, and
gene networks). The remarkable advances in networking technologies (both
wiredandwirelessnetworks)areenablingawiderangeofnew,man-madesys-
temsbasedonsophisticatedandlowcostdistributedcomponentscooperating
across low cost and high-speed data networks. Also, the availability of new
toolsandthedevelopmentofnewtechniquesinhandlingmulti-scalesystems
(frommicroaerialvehiclestonanoparticles)giveunprecedentedopportunity
forbreakthroughsincontrollingrealworldnetworkedsystems.
Cooperative control of multi-agent systems has experienced rapid devel-
opment during the past few decades. Distributed consensus algorithms
received much research attention, and cooperative control of multi-vehicle
systems have been extensively studied extending information consensus to
coordinated motions of autonomous vehicles. Due to domain specifications
and system constraints, applications found in realworld systems pose new
challenges to cooperative control. The richness of realworld problems and
diverse application domains revitalize the field and stimulate new research
directions.
This book presents applications of distributed cooperative control to real-
worldengineeringandphysicssystemsaddressingemergingneedsforhigheffi-
ciencydistributedcontrolsystems.Afterintroducingbackgroundsandreview-
ing fundamental distributed consensus algorithms, technical contents of the
bookaredividedintothreeparts.Thefirstpartdealswithnetworkedcommu-
nicationsystems,andconsistsofthreechapters,whichpresentdistributedcon-
sensus for quantized communication, cooperative spectrum sensing and dis-
tributedradioenvironmentmappingforcognitiveradionetworks.Thesecond