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StudiesinSystems,DecisionandControlVolume55SerieseditorJanuszKacprzyk,PolishAcademyofSciences,Warsaw,Polande-mail:kacprzyk@ibspan.
waw.
plAboutthisSeriesTheseries"StudiesinSystems,DecisionandControl"(SSDC)coversbothnewdevelopmentsandadvances,aswellasthestateoftheart,inthevariousareasofbroadlyperceivedsystems,decisionmakingandcontrol-quickly,uptodateandwithahighquality.
Theintentistocoverthetheory,applications,andperspectivesonthestateoftheartandfuturedevelopmentsrelevanttosystems,decisionmaking,control,complexprocessesandrelatedareas,asembeddedintheeldsofengineering,computerscience,physics,economics,socialandlifesciences,aswellastheparadigmsandmethodologiesbehindthem.
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Moreinformationaboutthisseriesathttp://www.
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com/series/13304GeorgiM.
DimirovskiEditorComplexSystemsRelationshipsbetweenControl,CommunicationsandComputing123EditorGeorgiM.
DimirovskiSchoolofElectricalEngineeringandInformationTechnologySaintsCyrilandMethodiusUniversityofSkopjeSkopjeMacedoniaISSN2198-4182ISSN2198-4190(electronic)StudiesinSystems,DecisionandControlISBN978-3-319-28858-1ISBN978-3-319-28860-4(eBook)DOI10.
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Printedonacid-freepaperThisSpringerimprintispublishedbySpringerNatureTheregisteredcompanyisSpringerInternationalPublishingAGSwitzerlandTorrentofChangesRenewsthisWorldOverandOverAgainastheUninterruptedFlowofTimeBringsYouthtotheFrontier-lessEternity.
MarcusAureliusProgressHasBeenandWillBeAchievedAlwaysWhenDaringToCrossBorders,SurpassBarriersandExceedLimits.
GeorgiM.
DimirovskiForeword:FascinatingIdeasonComplexityandComplexSystemsControlAbstractThefocusofthisForewordistoexplorethefascinatingideasoncom-plexityinconjunctionwithsystemsandcontrolsciences.
Itisbynomeansanattempttogivenalanswerstowhatthecontrolofcomplexsystemsmaycomprise.
Nonetheless,itisbelievedtohavegonefarbeyond"Complexityisintheeyeofbeholder"statedasthemessageofthesimilar2001Springermonograph.
Thisessayisanexpositionofpersonalvisionsofcomplexity,complexsystemsaswellascontrolandsupervisionofcomplexsystems,withcertaincomplexityfeaturesasanessentialsystemproperty.
Though,itremainsdedicatedtoexploretheissuesofintegratedcontrolandsupervisionwithintheirpossibleinterplayovercomplexplantsandprocesses.
Itisthushoppedthejusticationforcontinuingtheadventureofinvestigatingcomplexsystemsandcontrolsfromastandpointofphysicsandnotsolelymathematicsshallemergebyitself.
Ithasbeenfound,theexplorationroadofcomplexnetworksandsystemsaswellastheirfeasiblecontrolsstilllieswideopenbeforeinterestedresearchersfromboththeoreticalandtechnologicalpointsofdeparture.
For,complexityofdynamicnetworksandsystemisanevolvingissue.
KeywordsDynamicnetworksandsystems·Controlandsupervision·Controlledsynchronization·Collectiveversusindividualgoals·Communications·Evolutionadaptability·Evolvingcomputation·Feedback·Information·NonlineardynamicsPrologueAtrst,letusrecallherewhatthefamousHenryPoincarehademphasizedinhisowntime:'Thethoughtmustneversubmititselfnortoadogma,nortoaparty,nortoapassion,nortoapreconceivedidea,nottoanythingthatexistsifitwerenotthefactsthemselves.
For,thethoughttosubmititself,itshallbeastoceasetoexist'.
Inthesequel,withallduerespecttoavarietyofthinkingviewscompliedfromtheliterature,throughoutForewordthisoneofHenryPoincare'thoroughlyisobserved.
Inaddition,sinceWhiteheadandRussell[247]hadderivedtheentireviimathematicalscience(1927)onthegroundsofCantor'snavedenitionofasetasthefundamentalmathematicalconceptbyobservingthelawsoflogic,thediscus-sionpresentedherealsoemploysthesettheoryandthelogicofnaturalsciencestoitsfull.
LongagoLeonardodaVinciwasthersttostate:'Thereisnomuchtruthinsciencesthatdonotusemathematics'.
Furthermore,muchlaterImmanuelKantemphasized:'Ineverydepartmentofphysicalsciencethereisonlysomuchscience,properlyso-called,asthereismathematics'.
Andevenmuchmorerecently,RudolphE.
Kalmanpointedout:'Firstgetthephysicsright.
Therestismathe-matics.
'Theunderlyingscienticbackgroundherecomprisesphysics,settheoryanditsspecialbranchonadvancedgraphtheory[3,25,28,89,97,128,163,206,207,210].
For,neithercontrolnorsystemssciencesrepresentsolelyenterpriseofmathematics,butrathertheyimplywhatonemightcallakindof'generalized'physicalsciencehandlingobjectsandprocessesoperatingbelowthespeedoflight(forinstance,see[3,12,13,20,52,63,64,73,91,96,112,132,154,158,171,219,233])byvirtueofinterferingandinteractingenergy,matterandinformation.
Indeed,thereexistintheliteratureanumberofmonographswiththeambitiontogiveanswerstowhatthecontrolofcomplexnetworksandsystemsisallabout;someofthemostimportantonesarecitedhere.
Forinstance,theauthorofonesuchrecentbook,ComplexityExplained(Springer2008),PeterErdi,beginsbyarguingabouttheterms'complexity','complexsystems'andalike,andalsobycitingStephenW.
Hawking'sstatement:"Ithinkthenextcenturywillbethecenturyofcomplexity.
"Further,hepointsoutthatoneaspectofthecomplexityisrelatedtothestructureofasystem,andthenproceedstomentiontheunderlyingfactsthatallscientistsrecognizeinomnipresentnetworksandwebs.
Andyethearguesthatoneaspectofcomplexityisthestructureofasystemandfurthersuggeststhatitisthefundamentalorganizationalformofsystemsdespitewhethertheadoptedscienticapproachistheholisticorthereductionistone.
Incontrast,weherearguethatthefundamentalformpertinenttosomeentity,objectorprocess,tobeconsideredasystemisthatof(some)organizationinadditiontoapurposefunctionality(e.
g.
,see[29,30,31,35,51,57,66,96,114,128,135,155,157,160,164,180,204,208,223,224,231]).
Itisfurtherarguedherethataproperunderstandingoftheconceptofcomplexsystemsinevitablyrequiresreferringtothereality,includingthelivingsystemsandalsosocietalsystems.
Thepresentcollectiveauthoredmonographhasnoambitiontogivenalanswersbutsolelytosheddeeperlightintounderstandingcomplexsystemsinawidersetting,applicationsinclusive,henceviaobservingphysics,intherstplace.
Fromacertainviewpointoncontrolandsupervision,thepresentbookmayappearasifitwereareincarnationofthestatementbyHowardH.
Rosenbrock:'…Myownconclusionisthatengineeringisanartratherthanscience,andbysayingthisIimplyahigherstatus…',see[189],inthepresentprospectofcomplexdynamicnetworksandsystems.
WhileitmaywellbetruethisRosenbrock'sparadigmofengineeringasarts-rather-than-sciencetolieattheheartoftheconceptualdenitionknownas'Systemofsystems'givenbyAiguieretal.
in[1],dynamicnetworksandsystemspersehaveamuchdeeperscienticfoundation.
Thus,Idonotbelievesuchpuremechanisticconceptof'Systemofsystems',andtherespectiveviiiForeword:FascinatingIdeasonComplexityandComplexSystemsControlmethodologicalapproachtoo,couldgobeyondtheideasofinterconnectedandlarge-scalesystems(e.
g.
,see[5,11,16,35,39,43,48,57,65,71,76,107,109,163,167,168,192,211,227,243,260]andreferencestherein).
For,theentirehistoryofnaturalsciencesandofphysics,inparticular,givesaplethoraofevidencethatthiskindofsimplisticviewcannotbescienticallyviable.
ALookBackItseemstheideaandissuesofcomplexitywererstputforwardintheyear1948ontheeveofemergentpowerfulcomputingmachinesasitappearedinthe1964editedmulti-authoredbookbyEdwinF.
Beckenbach[24],inwhichWarrenWeaverwascitedinthePrefacetohaveauthoredthem(AmericanScientist36,1948).
ButitwasHerbertA.
Simon[213]whoin1962hasmanagedtoformulatecomplexityinscientictermsaswellastopromotecomplexityasanexclusivedirectionofimportantresearchprospect(ProceedingsofAmericanPhilosophicalSociety,106).
Acommonbeliefatthattimeacrossalleldsofsciencetypicallywas:thereexisttwomaincategoriesofcomplexity—theonesoforganizedcomplexityasso-ciatedwiththeappliedcombinatorialmathematics(alsoincludinggraphs,matrixgamesandoptimalcontrol;e.
g.
,see[2,15,26,27,47,55,67,71,72,74,94,96,101,108,121,133,153,162,177,207,214,229,233,237,246,247,249]),andtheothersofdisorganized(orunorganized)complexityassociatedwiththeuncer-tainty,probabilities,andstochasticprocesses(e.
g.
,see[6,7,14,31,37,83,95,98,Fig.
1Amacro-worldcomplexity:TelescopicsnapshothasrecordedacosmicmomentinthetumultuouslivesoflargespiralgalaxyNGC3227andsmallerellipticalNGC3226intheircloseencounter.
Spanningabout90,000light-yearsandsimilarinsizetotheMilkyWay,NGC3227isrecognizedasanactiveSeyfertgalaxywithacentralsuper-massiveblackholeForeword:FascinatingIdeasonComplexityandComplexSystemsControlix99,132,173,184,228]).
Itshouldbeappreciatedthatbothcategorieswereindeedwellconceptualizedandclearlydened.
Thisdichotomy-likethinking,itmaywellbenoticed,appearstofollowtheillustrationinFig.
1thatpresentsacontemporarytelescopesnapshotrecordofsomepartofthecosmos,whichInameconditionallyhereasthemacro-worldcom-plexity.
Itshouldbeclearlynoticed:certainelliptic-andspiral-shapedgalaxiesversusthevastbackgroundofseeminglydisorganizedones.
Furthermore,arecentinsightintothesub-sub-worldoftheboson(Fig.
6)discoverybyPeterHiggsandFranoisEnglertseemstoemphasizeoverandoverthatsimilarityandsymmetry[263]arequitenaturalpropertiesinphysicalworld[32,53];e.
g.
,seebothFigs.
2and3.
Thenwhynot(indeed,!
)accepttheuseofbothsimilarityandsymmetrywhendevelopingmathematicalrepresentationmodelsandcontrolsystemdesigns(Zhang1994[263];Dimirovski2011[51])forreal-worldobjectsandprocesses.
Indeed,considerablyearlythelogicofnaturehasyieldedtheiruseinsystemsandcontrolstudies,boththetheoreticalonesaswellastheonesinengineeringappli-cationsandtechnology[26,35,69,109,133,195,227,229,238].
Therebyitappearedthatexploitingthesimilarityandsymmetryfeatureshavealsogivenrisetoresultsandsomesortoftrendtoseeksimpliedrepresentationofendowedcontrolproblemsandthenndrelevantsolutions,aprocesssomewhatoppositetothelarge-scalesystems.
Inparticular,Prof.
Si-YingZhang[264]andhismanycollab-oratorsinduetimeshavebeenratherinstrumentalforthesedevelopmentsanddiscoveries[264];also,seeworks[44,45,47,53,95,115].
Fig.
2InthecenterofMilkyWay:ArtisticperceptionbyauthorM.
A.
Garlickofthephe-nomenologyofblackholeSgrA*,weighting4milliontimesmorethanSunandradiatingpowerfulradiowaves(NationalGeographic102(4);2014,p.
29):(1)superheatedenergydisk,(2)RO-radiationow-stream,(3)staticboundaryvirtualhorizon,(4)horizonofevents,(5)cosmicsingularity.
A.
Einstein:"IwouldliketoknowGod'sthought.
IwouldliketoknowhowGodcreatedthisworld.
"(seebrothersBogdanovIgorandGrishka[32])xForeword:FascinatingIdeasonComplexityandComplexSystemsControlItwasProf.
Zhang'sencouragementandinuencethathavematerializedinsolutionstotwodifferenttopicswithinthistrendbyJingetal.
[45,115]onforceresourcesdeploymentinbattle[44,115]andonwarfarecommandsystems[45].
Inparticular,asuitablemodicationofLanchestersquarelawwasusedinderivingforcepartitioningstrategyin[44]toobtainsimulationsresultsthatyieldedpreciselythehistoricaloutcomeoftheTrafalgarnavalbattlebetweenEnglisheet(sidex;AdmiralNelson)andFrench–Spanisheet(sidey;AdmiralVillanueva),outlinedfurtherbelow.
Itisamazingtonoticeforthiscomplex,command,controlproblemarathersimplesolutionwasfoundalbeitagame-basedanalysiswasemployed.
ThebackgroundisthefollowingsimpleLanchester-typeattritionmodel[115]:x0it=αy0i,i=1,2,,y0it=βx0i,i=1,2,,.
1Thederivedresultingtheoremstated:AssumeemployingthenonlinearlogicoftheseLanchestersquareequationofwarfareandsupposethatx0i>α+β2βy0i.
Iftheconditionsβpxsh>αpy0,i+1canbesatised,thenyTwillbecomezerobeforexT.
Thisistosay,thedefendingsidexwillgainthenalvictoryinthebattleunderthoseconditionsbyanappropriateforcepartitioningstrategyamongthefeasibleonesasshowninTable1.
FromTable1,withrespecttotheinuenceofthemaximumresidualstrengththeminimumwarfaretime,theoptimalpartitioningstrategyfortheEnglisheetis(11,16)and(7,10,16).
Themaximumresidualstrength,x0sh=16battleunits,andtheminimumwarfare,T=1.
9678timeunitshavebeenfound.
TherelationshipFig.
3ReportedoutlookofGod'sparticle—bosonofPeterHiggsandFranoisEnglert,whichexplainedhowotherparticleacquiremassandyetmaynotbethesmallestoneintheuniverse,followingCERNcolliderexperimentATLAS:FascinatingpropertiesofsymmetryandsimilaritywithrespecttoandtransversalthatmaypartitionitintotwohalvesForeword:FascinatingIdeasonComplexityandComplexSystemsControlxibetweentheresidualforcesoftheEnglisheetxandthenumberofforceparti-tioningoftheoptimizationmodelhasbeencomputedasinFig.
4.
TheestablishedrelationshipbetweenthefeasibleforcepartitioningstrategiesandtheactualnumberofforcepartitioningisdepictedinFig.
5.
Similarly,therelationshipbetweentheminimumwarfaretimeandthenumberofforcepartitioningiscomputedasinFig.
6.
ItcanbereadilyseenfromFig.
4thattheresidualforcestrengthoftheopera-tionalsidereduceswiththeincreaseinthenumberoftheforcepartitioning.
Thereexistsalimitedvalueofthenumberoftheresidualforcestrengths.
Whentheresidualstrengthislessthanthelimitedvalue,thestrategyisnotinlinewiththephysicalbackgroundofthebattle.
Forinstance,itshouldbesupposedthatα=βandthestrategyofforcepartitioningshouldbechosenas(7,20)and(2,13,18),thentheresidualstrengthonbothsidesbecomeszero.
Thisstrategywasnotusedinthatnavalbattle.
AsseenfromFig.
4,theresidualforcestrengthoftheoperationalsidexmayalsobecomezeroifthenumberoftheforcepartitioningisincreasedto11(Nelsonhadnotusedit).
ItcanbeseenfromFig.
5,thewarfaretimeshowsthegrowthtrendwiththeincreaseinthenumberoftheforcepartitioning.
Ofcourse,itiswellknownthatthewarfaretimemustbeinuencedbytheoptimalforcepartitioning.
Thereexistsalimitedvalueofthewarfaretime,whichseemstohavebeenintuitivelywellknownTable1Thepartitioningoftheforcestrengthandthewarfaretime(x01,x02)(y01,y02,y03)Warfaretimex′sh(9,18)(6,11,16)2.
038016(11,16)(7,10,16)1.
967816(12,15)(7,10,16)2.
038016(13,14)(9,8,16)2.
103916Fig.
4TherelationshipoftheresidualforceofsidexandthenumberofforcepartitioningxiiForeword:FascinatingIdeasonComplexityandComplexSystemsControltobothadmirals.
Itseemsmorethanjustinterestingtonotethatacomplexsystemdynamicsasthisnavalbattlehadhistoricallyexhibitedcouldhavebeensofairlyandeasilyreproducedviamodel-based,computingsimulationasSi-YingZhang[264]hasarguedin[265].
Furthermore,thisstudyhasemphasizedhowcrucialintherealworldarebothroleandplaceofinformationwithinthenaturallyexistinginterplayofenergyandmatterwithinformation[2,56,63,81,91,95,154].
Indeedtheinformationisthethirdfundamentalquantityhavingthesamerankandrangeasenergyandmatterdo.
AuthorPeterErdiinhis2008Springermonograph[67]providedargumentconsiderablyinfavorofimportanceaboutthesimilaritiesandsymmetriesbeingexploitedinvarioustopicsoncomplexity.
Indeed,giventhefactsfromtheworldoftheuniversals,suchasinFig.
2,andtheworldoftheinnitesimals,suchasinFig.
6,theissueofsimilarity/symmetryfeaturesaspropertiesofnaturalandFig.
5TherelationshipoftheminimumwarfaretimeofsidexandthenumberofforcepartitioningFig.
6TherelationshipofthefeasiblepartitioningstrategiesofsidexandthenumberofforcepartitioningForeword:FascinatingIdeasonComplexityandComplexSystemsControlxiiiman-madesystemscannotbeignored.
Itisthereforenotsurprisingthat,inhismonograph,PeterErdihasconceptuallyintroducedseveralkindsofcomplexities,ingeneralandinparticularstructural,functional,anddynamicalcomplexities,intherstplace.
Onlynextheplacedthealgorithmicinformationcomplexity,largelyattributedtoAndreyN.
Kolmogorov[134];thecognitivecomplexity,largelyattributedtoHeinzvonFoerester[234,235];thecomputingmachinecomplexity,largelyattributedtoAllanM.
Turing[230];theorganizationalcomplexity,largelyattributedtoLudwigvonBertalanffy[67]albeititwasAlexanderA.
Bogdanov[29]whohadrstinvented,investigated,andmadeuseofitinhistheoryoforganizationscalled'Tektology'(1925).
Furthermore,evenErdi[67]himselfhasnotedthatcertaineld-of-applicationspecicnotionsofcomplexities,namelyecologicalcomplexity;economiccomplexity;nancialcomplexity;politicalcomplexity;andsocialcomplexity.
Evenin[4]AhamdiandJungers2014exploredcomplexityofLyapunovfunctionsforswitchedlinearsystems,onlyforthelinearones.
TheoriginalKolmogorov'sdenition,whichreads"Thealgorithmic(descriptive)complexityofdatasequenceisthelengthoftheshortestbinarycomputerprogramthatprintsoutthesequenceandhalts,"isstrikinglycompatibletothefundamentaltheoremsofcomputinglanguages,grammars,andmachines[46,128,230].
Moreimportantlyinmyopinion,however,itiscompatiblewiththeunderlyingalgorithmicnatureofalldevelopmentsinsciencesandengineeringofcomputing,communicationnetworks,andcontrolsystemsalike.
For,whatalwaysanoperatingfeedbackcontrolsystemdoesafteranydisturbingactionfromtheenvironment,inasense,itissolvingoverandovertheinitialvalueproblemthroughprocessingofthecontrolerrordynamicsoftheclosed-loopsystemwithcertainnewlytriggeredinitialconditions.
Therefore,Kolmogorov'salgorithmicunderstandingofthecomplexityseemsthemostfundamentalonefromtheviewpointoftheintegratedcontrolandsupervisionofcomplexnetworksandsystems.
ThusIdobelievethatKolmogov'sconceptualizationpreciselygaverisetothecomplexitytheory.
Later,itwasembracedbyRissanen[184,185]anddevelopedtomaturedlevelbyLiandVitanyi[141].
Thesestudiesandthe1978contributionbyRissanen[185],inturn,seemtohavebeeninstrumentalforGruenwald's2007studyontheprincipleofminimumdescriptionlength(MDL)inthemodeldevelopmentforagivendataset[84].
ThelatterisalsostronglysupportedbyHaykininhis2009monograph(pp.
109–112)withinthecontextoflearningmachinesandneuralnetworks[89].
Systempropertiesofstructuralsymmetryand/orsimilarityhavebeenwellexploitedintheinvestigationofvariouskindsofinterconnectedandlarge-scalesystemrepresentations,whichhaveyieldedanoutstandingplethoraofdevelop-mentsanddiscoveries.
Forinstance,oneshouldstudytheworksbyDragoslavD.
Siljak(1970–2010)andhismanycollaborators:themonographs[207,210,260]areparticularlyimportant.
Theyhavediscoveredmostofstructuralfeaturesofdecen-tralizedcontrolofsuchcomplexsystemsinthepresenceofinformationconstraintsandstructuralperturbationsaswellasuncertainty.
Systemsandcontroltheories,inparticularthoseconcerningthelinearsystemsandlinear-quadraticoptimalcontrol(aswellastheirapplications),havehadablossomofdevelopmentsfollowingthefundamentaldiscoveriesbyRudolphE.
xivForeword:FascinatingIdeasonComplexityandComplexSystemsControlKalman[120,121,123–125]ontheoryofsystemsandcontrol.
AsimilarimpactcouldbeseenforthefundamentaldiscoveriesofVladimirA.
Yakubovich[250–252]onmatrixinequalities,S-procedure,andthecelebratedKalman–-Popov–Yakubovichlemma[33,81].
Practically,allthesedevelopmentshavebeenextendedlatertobothlarge-scalesystemsandnonlinearsystemsinvariouswaysbyanumberofauthors(e.
g.
,somearefoundinthereferencesgiven).
Yettheideasandissuesaswellasconceptsaboutcontrolofcomplexsystemscontinuetogetenrichedandtoevolveuntilnowsuchasmostrecentlywithintheparadigmofcomplexnetworksandnetworkedsystems.
Evolutionhappenedsomewhatgradu-allybeginningwithexploitingnaturalfeaturesofsimilaritiesandsymmetriesinbothoftherealworlds,thedeadandthelivingones.
Inordertoreturntotheissueofprimaryconcerninthisdiscussion,noticethatthereexistsconsiderableknowledgeaboutastrophysicsperceptionofthecosmiccomplexityandbirth,life,anddeathofcelestialobjectsandgalaxies(seenviaFigs.
2and3).
Yetthejourneyintothediscoveringtheessenceoflifeviastudyingitsmanifestedfeatures(forinstance,see[170])hasstartedprogressingnotsolongagoandwasduelargelytovariousvisionaryperceptionsofwhatcomplexityandcomplexsystemdynamicsmaybeallabout(e.
g.
,see[6,15,22,34,39,41,42,49,50,57,62,66,83,96,97,101,104,112,156,166,176,181,190,193,218,234,235]).
Ontheotherhand,ourreal-worldexperienceviahumanperceptionofnaturalonesaswellasofman-madedynamicprocessesdemonstratestheexistenceofvariationin"sheds"ofcomplexitybetweenthesecategories.
Nonetheless,itiswithinthiscontextpreciselywhereHeinzvonFoerester[233–235]withinhisthinkingaboutcyberneticsandsystemsinthewidersettingofnatureandsociety,seemstohavehighlightedconsiderabledeeperrootsinvolvingnotonlytheinter-playofenergyandmatterwithinformation[53,55,82,135,138,154]butalsothecognitionprocess[235,239].
Itappears,hisemphasisoncognitionhasemergedtobeconsiderablecrucialincontemporarydevelopmentsofsystemsengineeringdesignandautomationtechnology.
Thecognitionprocess,however,alsoimpliessomeanticipationandmaybeconsciousnesswithintheevolutiondynamicsinthenature.
Butcanitindeedbeso,thenThereisnoclear-cutanswerasyet,anditdoesnotseemonewillappearinthenearfuture.
Indeed,mostoftheconsultedsourceliteraturesuggestedforquitelongtimetherehaveexistedconsiderableendeavorstoexplorethelifeitself.
Itisastrikinglyoldideathatactuallyhasledtoadeeperunderstandingoftheissuesofcomplexityandcomplexsystems,asamatteroffact.
Thisshifthastakenplace—itmaywellbearguedso—duetothecrucialimpactofdiscoveriesingeneticresearchwithinbiologicalsystemsleadingtotheideaofsystemsbiology.
Indeed,considerablymanyaspectsofcomplexsystemsonthewaytowardscomplexdynamicnetworkshavebeenevolvedintoaninnovatedinsightsincetheworksbyDarwin[49],Bogdanov[31],Pavlov[170],Dobzhansky[58]andRadcliffe-Brown[180].
Moreover,itappearedtranscendingtheseideasintotheevolutionoflifeandthesocietaldynamicshavehadevengreaterstimulatingimpacttowardsthedevelop-mentofthescienceofcomplexdynamicnetworksandsystems(e.
g.
,see[1,16,51,66,77,84,101,127,157,165,167,168,169,190,193])andhadinducedotherForeword:FascinatingIdeasonComplexityandComplexSystemsControlxvinsightintotheissuesofcomplexityandcomplexsystemsaswellastheircontrolstrategies.
Theevidenceintheliteraturealsosuggeststhatthegeneraltrendduringthepastdecadestowardsaneverincreasinginterconnectionandcross-couplinginallsocietalandhumanactivitiescausedadeniteshifttowardsauniedcompre-hensionofcomplexdynamicsystemsandcomplexdynamicnetworksinvariousrealizationforms.
Furthermore,perhapsthisisthemostimportantparadigmofthecurrentstate-of-the-artsincomplexnetworksaswellasthewholeofsystemsscience.
Abriefscanofasmallsampleofresearchstudies,suchas[5,6,20,102,104,144,145,150,163,168,178,179,210,212,223,224,241,243,269,270],clearlydemonstratestheconcludingremark.
Inaddition,asMuscolesiandMascolo[161]noted,theunprecedentedrecentadvancesincomputernetworks,communi-cations,andinformationtechnologies[36,59,116,201,220,255]aswellastheworld-wideexpansionofmutuallyinterconnectedeconomieshaveonlyreinforcedthismajortrend.
Furthermore,thismajortrendistoexpandevenfurtherinalldomainsofsocietalandhumanactivitiesthusbecomingtheoverwhelmingone[20]nowadays.
Itseemshowever,thelifeitselfplaysamoreessentialroleinthecollectiveadaptabilityandtheevolutiondynamicsthanithasbeenadmittedinsofar[66,114,157,188,190],nonetheless.
RidingtheWave:AForward–BackwardInquiryComplexdynamicnetworks[219,243],whichcompriseasetofnodespossessinglocallycontrolledoruncontrolleddynamicsystems,andanitegraphstructureofnitecapacitycommunicationsaswellasinteractionsamongthosenodesystems,havealreadygainedagrowingattentionfromscientistsandengineersworld-wide.
Nowadays,adynamicnetworkiscommonlyunderstoodtobealarge-scalesys-temicstructureconsistingofagraphthatcontainsenumerablesetofdynamicsystemsasitsnodesandanitesetofsignal-owinterconnectionsamongthem.
Thus,intheirveryessence,Ibelievecomplexdynamicalnetworksandsystems,therootsofwhichcanbetracedbacktoAizermanandhiscollaborators[3]andtoFordandFulkerson[73],canbecompletelydescribedbythedynamicgraphsaspro-posedin[212]byDragoslavD.
Siljak.
Duringthelastcoupleofdecades,researchactivitiesinexploringsynchronousevolutionormotiondynamicshasbeensteadilygrowingandbothspontaneousandcontrolledsynchronizationhasbeenextensivelyaddressedinanumberofworks(e.
g.
,see[25,39,48,51,87,146–148,211,223,224,241,242,270,272,273],andbymanyotherauthorsaswell).
Theimportanceofsynchronizedevolutionormotiondoesnotlieonlyinthosesituationsinwhichsynchronizationcanbefound,butalsowheresynchronousmotioncanbeinducedtoensuretheproperfunctioningofparticularcollectivedevicessuchasmultiplemachineensembles.
Itshouldbenotedsomeofthoseworkshavesuppliedfeasiblecontrolmethodsforreinforcingthesynchronizationinafewfairlywideclassesofdynamicnetworkswithregardtotheirtopology.
xviForeword:FascinatingIdeasonComplexityandComplexSystemsControlTheinvestigationoftheaspectsandissuesrelatedtothecontrolleddynamicalnetworkshasbecomearatherattractiveresearchareafortwomainreasons.
First,dynamicalnetworksappearinvariousworldsofthenatureandhumansocietiesonEarthaswellasmanyeventsandprocessesintherealworldcanbemodeledbydynamicalnetworks.
Second,alargenumberofimportantapplicationsofdynamicalnetworkscanbeidentiedinvariousdisciplines,whichincludeastro-physicsbiology,economics,engineering,lifescience,neuroscience,andsociologytoo[87,168,181].
Inthesequel,buildinganargumentisattemptedinfavorofobservingDarwin'sevolutionaldynamics,asapointofcentralityinthequestforaconsistenttheoryofcontrolledcomplexnetworksandsystemsviathetheoryofSiljak'sdynamicgraphsasanadequatetoolfromappliedmathematicsandthephysicsbehindsystemsscience[55]isattempted.
Thecrucialpointofdeparturetonotice[91,92]istheuniqueintegrityoftheinterplayofenergyandmatterwithinformationintheuniverse;[92]hencealsoonEarth'snature[55,56,82,176,188].
Itshouldbenotedthatreferencetobiology,lifescience,andsociologyinevi-tablyputsaspecialemphasisontheconceptuallyfundamentalcategoryoforga-nizationanditsfeasibleevolutionwhilenotsolelyonthestructureassuch.
Darwin'sevolutionaldynamicsofspecies[49]involvesinteractiveprocessofmutualadjustmentandco-evolutionthatismatchingthestructuralcouplingup[58,126,127,160,176]whiletheorganizationofan"autopoietic,"i.
e.
,aself-reproducingcircularnature,classidentity"livingorganism"comesoutfromthefeatureoftheorganizationpossessingacertainstructuredeterminism[57,156,166,187].
Inturn,referencetothelivingpointsouttoessentiallyanotherbutdeeperunderstandingofcomplexdynamicnetworkandsystemsthatmostoftenpossessgoal-seekingbehavior.
ItisinthisregardthatIdobelievecomplexdynamicnetworksandsystems,whichemploycombinedcontrolandsupervisiontoenforcetheirorganizedinte-gration,oughttobeviewedasakindofapproximationtobiologicalsystems.
Thus,theyshouldbeendowedwithcapacityofbecomingautonomous,closed,circulardynamicalprocessesasthelifeitselfonEarth[5,50,55,63,86,112,130,155,160,166,181,193,215,218,232,235].
Thus,theemployed,combinedcontrolandsupervisionoughttopossesshigherqualitiesthanknownatpresent.
Inparticular,theintuitionsuggeststhesupervisoryleveloughttohavesomepropertiesofcon-trollingcognitionwithinthebroaderviewonevolutionprocessdynamicsthatisassociatedwiththeentirephenomenonoflivingbiologicalsystems.
Itisthereforethatsupervisoryfunctionshouldbesoughttohaveimplementedcertainmentalistactivitieshencecognitionwithinthewidersetofdecisionandcontrolactivities.
Assuchtheymustbecompatiblewithandcoherenttoasetofdecisionandcontrolactivitieswithinthecomplexnetworksandsystemssoastoguaranteethatnotonlythesystemintegrityandstabilitybutalsothegoal-seekingbehavioraresimulta-neouslyreinforced.
Indeedtheseaspectsmaywellopenanewprospectbuttheyalsoposesometremendouscomplicatedanalyticalproblemsbothmathematicallyaswellasfromtheviewpointofsystemsandcontrolsciences.
TheestablishedinsightthatallcomplexnetworksandsystemsareindeedcharacterizedwiththeForeword:FascinatingIdeasonComplexityandComplexSystemsControlxviifeatureofinseparabletwinofstructuredeterminismalongwithstructuralcouplingisduetoextensiveinternalcommunicationsandinformationsharingexchangemechanisms[26,35,52,54,155,186,192,210,232,233,272].
Acomparativeanalysisoftechnologiesandscienceofdynamicnetworks,sys-tems,andtheircontrolatthetimesoftheclassicsofengineeringcybernetics([15,196,229,233,237];Bogdanov1925[29],[79];Wiener1948[246])withtherecentonesreadilyyieldsnotonlytoomanybutalsothemostimportantchangestonotice.
Thesechanges,Ibelieve,canbesummarizedintwoentities:incrediblypowerfulcom-putationaltechnologies,ontheonehand,andunprecedentedpervasivefastcom-putationalandtransportationnetworks,ontheotherhand.
Ofcourse,alongwiththesetechnologies,theunderlyingscienticknowledgeofthehighestqualityandinenormousquantityhasbeenacquiredaswell.
Itisthereforethatthereal-worldsystemsareabundantinallsortsofnonlinearandtime-varyingpro-cesses,whichmaynotbeamenabletomathematicalrepresentationentirely.
Still,asarguedbyRosenbrock[189]in1977,bothmathematicsandphysicsareindispensabletosystemsandcontrolsciences,andthereforeIbelieveaspecialattentionshouldbepaidtoanimportantfeatureinmodernphysics.
Namely,modernquantumtheoryhasabandonedtodealwithstrictcausaldeterminationforelementaryatomicprocessesandhasturnedmoretowardsstatisticalanticipationaboutthoseprocesses.
Shouldwenowtakeacloserinsightintothenetworkcontrol-theoreticdevelopmentsandpracticaldesigns,thennospecialimaginationisneededtoseethatsuchnetworksystemicstructureshaveparallelswiththeworldsofatomsandsubatomicprocessesaswellaswiththemolecularworld.
Ibelievethesubsystemprocessesinnetworkedcontrolsystems,andevenmoreso,incomplexdynamicnetworksaretoacertainextentanalogoustothoseelementaryatomicprocesses,andindeedtovariousmacro-andmicro-worldsonEarth.
Thus,itoccurredtome,indeedweoughttotryhardtotranscendsomeofmodernquantumtheoryintothegeneralframeworkofreasoningaboutthesystemsandcontrolscience[51];hencecomplexdynamicnetworkssystemsaswell.
Forthetimebeing,letleaveoffthisissueandaddresswhatspecicfeaturescanberecognizedaboutcontrolsystemsovercommunicationnetworksasimplementations,whichrepresentpervasiveexistencenowadays.
Butnoticenonetheless,thesearebyandlargecomputercontrolledhencecomputerscienceisindispensable.
Inmyopinion,thefeaturesofprimaryimportancearetheknownkindsofcomplexitiesandofuncertainties,informationconstraintaswellasconnecting/disconnectingsustainabilityandsurvivability.
Thelatterisbeingdirectlyrelatedtoallvariantsofpertinentsystemsstabilityproblems,nowlargelytractablebyLinearMatrixInequalities(LMI)basedtechniquesduetooriginaldiscoveriesofVladimirA.
Yakubovichinfundamentaltheoryofcontrol[250–252]andinapplications[72,253].
Withoutadoubtadaptationandre-organizationalsoplayratherimportantroles.
Andevenmoresodoadaptationandre-organizingadaptationandre-organizationonamassivescale,notnecessarilycollectiveunlessinducedbysomeconsensusstrategy.
Byandlargetheseallarecontrolreinforced.
However,Ibelieveadaptationandre-organizationcomeonlysecondnexttothepreviouslypointedcomplexities.
xviiiForeword:FascinatingIdeasonComplexityandComplexSystemsControlUponnotingseveralkindsofcomplexities,letusrsttakeintoconsiderationtheorganizedones[244],becauseitisthecontrolinfrastructurepreciselythatcanconverttheunorganizedcomplexitiesanduncertaintiesintotheorganizedones.
Itshouldbenoted,solelythemathematicalhencealsothecomputerscience,com-plexitiesaretheonespreciselydened.
ThesearereferredtoasNP-completenessandNP-tractability,usually.
However,ithasbecomeapparentinthepresentdayencounteredcomplexdynamicnetworksthatarchitectural,structural,andtopo-logicalsystemcomplexitiesappearinadditiontothecomputationalone.
YetitistruethatnoneofthemiseithercompletelyorpreciselydenedasitistheNP-completenessincomputerscienceandICT.
Itshouldbenotedfurtherthatthelastcoupleofdecadeshaveyieldedconsiderableadvancesinvariousissuesaboutcomplexdynamicnetworksandsystems,oneofwhichisanimprovedunder-standingoftopologicalcomplexityversusnetworksustainabilityseemstobeinstrumentalforthefurtherdevelopments.
However,itappearedmuchdeeplyinvolvedforthepresentdayexistingknowledgeandunderstanding.
Nonetheless,someoftherecentlyreportedresearch[146–150,223,224,268–271]hasindicatedthatenormouscontroleffortisneededinordertoreinforcecontrolledsynchro-nization,ingeneral,andalsotoensureconnectivesustainability,inparticular.
Thefeatureofinformationconstraintisconsiderablywellunderstood,thankstotheadvancesinlarge-scalesystemstheoryanddecentralizedcontrolsforlarge-scalesystems.
Followingthe2010Springer'smonograph[260],ControlofComplexSystems:StructuralConstraintsandUncertainties,therestillremainopenissuesinthisregardsaswellasaboutthedecentralizedcontrolofcomplexandlarge-scalesystems—inSiljak'swords—beyondthedecentralizedfeedback(Fig.
7),ingen-eral.
Inparticular,despitetheexistingknowledgeonconnectivestability,thisknowledgestillremainstobetranscendedinthewidersettingofconnecting/disconnectingsustainabilityandsurvivability.
Oneratherimportantpathwayforwardtobepointedout,Idobelieve,ispreciselytheoneviadynamicgraphsofSiljak[210].
Inotherwords,complexdynamicnetworksaresystemicstructuresthatdopossessfeaturesofdynamicsrequiringcontrolmechanismsthattranscendbeyondthecurrentknowledgeondecentralizedfeedbackcontrolandsupervisioninfunctionalsynergy.
Theissuesoftheuncertaintyhavebeensubjecttostudyfromtheverybegin-ningsofinformationtheoryaspartofthetheoreticalstudiesincyberneticsanditsapplications.
However,aswithcomplexities,thereappearvariouskindsofuncer-taintiesalbeitinsystemsandcontrolmostoftentheparametricandstructuraluncertaintiesarebeingaccountedfor.
Shouldwerecognizetheunavoidableneedforsomeintegrativeorganizationalstrategyimposedeveninlargelydecentralizedcomplexdynamicnetworks,thentheuncertaintytoobecomesasmultifacetedoneasthecomplexityis.
Atthispoint,itshouldpointoutthelargelyneglectedneedfordevelopingsophisticatedtheoryonsupervisorycontrolstrategiesthatcanguaranteesurvivabilityofthecomplexdynamicnetworkundervariousadhoctopologicalcircumstancesviasomecontrolledreinforcementofsystemintegration(seeFig.
7).
Inmyopinion,fortheissuesofsupervisorycontrolslongertimeisleftformoreempiricalinvestigationsthantheoreticalstudies.
ItisinthisregardthatIbelieveForeword:FascinatingIdeasonComplexityandComplexSystemsControlxixSiljak'sconceptofdynamicgraphsdoesprovideaninnovativeandsoundpathforward.
Atthispoint,Iwouldliketoinferfromtheissueofexploitingsomehintsfrommodernquantumtheory[91,96],whichseemstohavebeenforeseenbyEinsteinhisfellow-friends[63].
Namely,Ithinkthatsoonerorlaterwehavetoplaceourmainfocusonhowtomitigateconsequencesofstrictuseofthecausalityprincipleinsystemandcontrolscience.
Iinclinetobelievenomajorbreakthroughisfeasiblewithoutendowingtheintegrativesupervisorycontrolwithsomecapacityforanticipation;onlythencombinedcontrolandsupervisioncoulddeliverfarbeyondthepresentdayknowledgeonvariouspredictivecontrols.
ThereforeIbelievethattheincreasingprecisionwithdecreasingintelligence(IPDI)principleduetoGeorgeN.
Saridis,i.
e.
,theanalyticalformulationoftheprincipleofIPDI[194],albeitprimarilyitwasdrivenfortheneedsinrobotics,hasbeenunderestimatedandleftasideunjustiedforthatmatter.
Inhereandforthepurposeofcomplexdynamicnetworksandsystems,Iwoulddaretore-interpretitintermsofincreasingintelligencewithdecreasingprecisionhenceand,onthegroundsofentropytheory,comeupwithsupervisorycontrolprocessingalbeitwithsomeincompleteantici-patoryproperties.
However,suchsupervisorycontrolscannotbeachievedwithoutemployingcomputationalintelligencetechniques.
Henceexploitingthecognitiveapproachincontrolimitatinghumanintelligencecapacities,whichwemaydaretoFig.
7Thewell-known,hierarchical,computercontrolbased,implementationofintegratedcontrolandsupervisionforcomplexdynamicnetworksandsystemsintermsofdynamicsub-networksofnonlineardynamicnodes,whichincompliancewithSiljak'sconceptofdynamicgraphs[210,212]xxForeword:FascinatingIdeasonComplexityandComplexSystemsControlenvisageintermsofevolvingcomputationalintelligence,becomesasnecessaryasmathematicsandphysicsare.
Itiswithinthiscontextthatthetechnologicalimplementationofintegratedcontrolandsupervision,whichisillustratedinFig.
7,seemstogainitsfullsystemsengineeringvalueasemanatedfromcontrolsystemtheoreticalendeavorsofthelarge-scalesystemstheory[26,35,55,77,107,158,192,207,209,210,227].
TheIPDIprincipleofSaridis[194],inmyopinion,hasmadearatherstimulatingimpacttowardsexploitingcomputationalintelligencemethods[89,113,127,259]forsolvingcomplicatedtasksofcontrolandsupervisionfornonlinearandcomplexsystemsaswellasforcomplexdynamicnetworks.
Thesemethods,alongwiththerespectivetechniquesforrepresentationmodelingofprocessestobecontrolled,includetheoriesmethodologicaltechniquesoffuzzysystems,neuralnetworks,fuzzy-neuralorneuro-fuzzysystems,andfuzzy-Petrinetsaswellaslearningmachinesandsystemsinabroadersense[2,7,52–54,60,61,90,103,104,113,127,129,133,135,152,172,174,183,191,221,255,257–259,262].
Further-more,someofthemostrecentstudieshaveclearlydemonstratedhowmanymin-glingandmutuallyinuencingarenonlineartheoriesofsystemsandcontrolwithinteractingfuzzysystemandneuralnetworktheories,fromtheviewpointofsta-bilityinparticular.
Inthisregard,theinterestedreaderissuggested,forinstance,toconsultrecentarticles[52,89,103,104,142,221,228,254].
Itisinterestingtonotethatcomputationalintelligencetechniquesappeartobyandlargeanothermethodologytotacklemathematicallycomplexnonlinearproblemswhereanalyt-icaltechniquesfailtodelivertechnologicallytangibleresults.
Itshouldbenotedfurther,inaddition,duringthelastcoupleofdecadessig-nicantscienticadvanceshavebeenachievedinthetheoriesofbothcomplexdynamicnetworksaswellasofswitchedsystemsandswitching-basedcontrols.
Suchdynamicnetworksandsystemslargelyoccurduetocombinedevent-driven,state-driven,andtime-drivencontrolandsupervisioninman-madetechnologies[13,16,39,40,74,80,94,107,142,145–151,223,224,265–273].
ItseemsmorethanjustcoherentthatthesetheoreticaldevelopmentsarealsowellcoherentwithtechnologicalimplementationschemethatispresentedinFig.
7.
Nonetheless,thecomplexdynamicnetworksinvolvingswitchedtopologiesandswitchingbasecontrols,Idobelieve,appealforessentiallymodiedconceptualizationsonhowweperceiveprocessesthatevolveduetothecombinedtime-,event-,andstate-drivendynamics.
Infact,thesetwoareashaveopenedawholenewprospectstowardsnetworkedsystemsengineeringcreationsofthefuture.
Itshouldbenoted,althoughatinfancynow,someencouragingresultsonthesynergyofcomplexdynamicnetworksandswitchingcontrolbasedmodeshaveappeared.
Forthesakeofacertainscienticevidenceoftheseissuesmentionedabove,letmeputanoverviewofthefollowingreasonablygeneralandwidelyapplicablemodelofcomplexdynamicalnetworks,whichinvolvesrealisticcaseofnon-identicalnodeswithrelative-degree-onenonlineardynamicsystems[150].
Itisdescribedbythefollowingsetofstateandoutputequations:Foreword:FascinatingIdeasonComplexityandComplexSystemsControlxxixi=fix+gixui,yi=hix,i=1,N,.
2Herethesymbolsdenotexi∈Rn,ui∈Rm,yi∈Rmarethestates,thecontrolinputs,andthecontrolledoutputsofthei-thnode,respectively;thevectorfunctionsfi:Rn→Rn,gi:Rn→Rn*m,hi:Rn→Rmare(assumed)tobetwicedifferentiableorsmoothmappingsthatpossessthereal-worldpropertiesfi0=0andhi0=0.
Forillustrationpurpose,atthisinstance,notethatonesuchdynamicnetworkhavingvenonlineardynamicnodesisdescribedasfollows:xi1=xi1+li1xi2sinxi1+xi2ui,xi2=sinxi1+xi2ui,yi=xi2.
3Inhere,i=1,…,5,andinaddition,valuesofliaredenedas:l1=1.
2,l2=1.
3,l3=1.
05,l4=0.
8,l5=0.
9.
Obviously,allnodesarenotpassive,buttheyallarenodesofrelative-degree-onenonlineardynamicsystems,quitecommoninpracticalapplications.
Communicationcouplingtopologyforthenetworkisdenedbyvi=∑j=Nj=1aijΓyj.
4Ithasbeenshown[150]thatthiscanberewrittenasu=AΓy,whereA=aijNNisamatrix,calledtheoutercouplingmatrix,Γisanm*mdiagonalmatrix,calledtheinnercouplingmatrix.
ThequantityAΓistheKroneckerproductbetweenthesetwomatrices,whichispresentedbelow.
AΓ=a11Γa12Γ.
.
.
a1NΓa21Γa22Γ.
.
.
a2NΓaN1ΓaN2Γ.
.
.
aNNΓ0BB@1CCA∈RNm*Nm,5whereA=21100031111021011032010022666643777756istheoutercouplingmatrixthatdoesnotpossesstheusuallyassumedpropertyintherelevantliterature;also,itisshownthatΓcanbetakenastheidentitymatrix[150].
xxiiForeword:FascinatingIdeasonComplexityandComplexSystemsControlItmaywellbeinferredfromtheabovemathematicalrepresentationmodelthatitimpliescomplexityinseveralrespects.
Still,thecontrolledoutputsynchronizationcanbewellenforcedasthesimulationresultsinFig.
8demonstrate.
Indeed,synchronizationisacollectivebehaviorofdynamicalnetworks,ofcourse,butitisoneofthecrucialissuesinstudyingpotentialbehaviorofcomplexdynamicalnetworks.
Ithasadirectrelevancetoandcertainrelationswiththelogicoflifeitself(Rosen1991;[50,126,166,186]).
Andthelifeitselfindeedisthebestteacherforbothorganizationandself-organizationintheuniverse[50,127,156].
Themainissueofconcernseemstoappearintermsofhowtoaccommodatewithincomplexnetworkssettingtheneedtoemploysometechniquesofgametheoriesandsomeanticipationfeatures[186],becausetheyarealsocrucialincomprehendingthereal-worldliving,ecology,andsocietalsystemsintheirmutualinteractivecouplings[85,155,181,190,218,233].
Theideasaboutengineeringimplementationofintegratingcontrolandsuper-visionofman-madecomplexindustrialplantsalsodeservetobeappropriate,butbrieyaddressedinthisessaytractate.
Itshouldbenotedherethat,intherstplace,theheritagefromcontroldevelopmentsaimedatinterconnectedandlarge-scalesystemcomplexesintermsofhierarchicallyorganizedcomputercontrolsystemarchitectureandtherespectiveapplicationssoftwaretechnology.
Thesewerepre-ciselythetechnologiesthatenabledthemodern-dayautomatedfactories,powerplants,aswellascommunication,power,andtransportationsystems,andevenstimulatetheexplorationoftheparadigm"factoriesofthefuture"further.
Forthispurpose,fromRomeroetal.
andtherelatedworks[119,200,231],respectively,theborrowedFig.
9isgivenaspresentedabove[188].
Itmaywellbeconsiderablystimulating,andpossiblyinstructivetoo,ifinthiscontextafewmorepointsaremade.
Thenthisdiscussioninevitablyinvolvestheissuesofoperatingsymbiosisofhuman(s)andautomationsystem[119].
Itisthereforethatalsoman–machineinteractions[70,111,154,156,200]aswellasFig.
8Thesynchronizedoutputresponsesofthenet-workwithcommunicationcouplingtopologyandnodesofnonlineardynamicsystemshavingrelative-degree-one[150]Foreword:FascinatingIdeasonComplexityandComplexSystemsControlxxiiifeaturesofhumansintheroleofcontroloperator[182,187,232]oughttobeplacedwithinthesceneandscenariosofcontrolandsupervisionofcomplexdynamicnetworksandsystems.
Itisinthisregardthatthesupervisoryleveloughttohavesomepropertiesofcontrollingcognitionasabroaderevaluationofcontrolledprocesseswithintheautomatedcomplexplant.
Thereforethatsupervisorycontrollevelistobedesignedtohaveimplementedcertainmentalistactivitiesandhencecognitionwithinthewidersetofdecisionandcontrolactivities.
Assuchtheymustbecoherenttotheentirefeasiblesetofdecisionandcontrolactivitieswithinthecomplexnetworksandsystemsinordertoguaranteenotonlythesystemintegrityandstabilitybutalsotheoveralladaptabilityandgoal-seekingevolution.
Further-more,followingarecentstudy[231]byTzafestasthisconceptualizationseemstotranscendbeyondthetechnologicalcomplexsystem,sinceitdoesreectuponthesocietyandhencethenature[85,180,203,218,245].
Finally,withinthisdiscussionaboutcomplexdynamicnetworksandsystemsintegratedviatheircontrolandsupervisioninfrastructure,issuesofstabilityoughttobeaddressedbecausethesearesine-qua-noninsystemsandcontrolsciencesfromthetimeofPoincare'[175]andclassicanalyticalmechanics.
IthasbeensosincethedaysofdevelopmentsintheoryandengineeringoflineardynamicsystemsFig.
9Anoverviewofthecurrentstate-of-the-artdevelopmentsinhuman–automationsymbiosis[188]withindesignvariantsofhuman-centeredautomationsystems[70]intermsofthePurdueEnterpriseReferenceArchitecture;thesegmentontherightpointsouttheongoingresearchtasksxxivForeword:FascinatingIdeasonComplexityandComplexSystemsControlandtheircontrol;forinstance,Anderson[8,9],Barnett[21],Bernusou,andTitli[26],Dimirovskietal.
[55],Kalman[121,122],KrasovskiiandPospelov[133],MesarovicandTakahara[158],Rosenbrock[189],Siljak[202,207],Tsien[229].
True,theseaspectsareconsiderablymoredifcultandmoreinvolvedwithinthiscontextofcomplexdynamicnetworksandsystems.
Moreover,thereweremuchmoreinvolvedthanstudiesofnonlineardynamicsystemsatthetimeofLiapunov[173]andPoincare'[175]withintherealmofclassicanalyticalmechanics.
Itistheextensiontowardsthecontrolofnonlineardynamicsystemsanditsoptimizationthatmadeessentialdifference;forinstance,seeAnderson[8],Emelyanov[65],FilippovandArscott[71],Isidori[110],Moylan[98],Kalman[120],Krasovskii[132],Lurye[153],Pontryaginetal.
[177],Siljak[203,207,210].
Thesedevel-opmentshavegivenconsiderableunderstandingofthenatureofLyapunovfunc-tionsandLyapunov–Krasovskiifunctionalstotheextenttobecomefundamentaltoolsforexplorationsintherealmofcomplexdynamicnetworksandsystems.
Itshouldbenotedrstofall,therstconsiderableextensionsofLyapunovstabilitytheoryhavebeenmaderatherearlybyLurye[153]andbyKrasovskii[132].
Theseextensionshavepavedwaytowardsadeepandfar-reachingstudyoftheoriginalconceptualizationofLyapunovfunctionthatyieldedinnovativemodicationsuptonowtovariousLyapunov-likefunctionsinthesearchofcon-structingLyapunovthataresuitableforspecicbutnonlinearand/ortime-delayphenomena;forinstance,seeAntsaklis[13],BasarandBernhard[22],Fominetal.
[72],FridmanandShaked[75],IkedaandSiljak[106],Kalman[124],Kozyakin[138],LeeandJiang[140],Liberzonetal.
[142],LiuandFridman[145],LongandZhao[151],Teeetal.
[225,226],Zhangetal.
[261],J.
ZhaoandDimirovski[266],J.
ZhaoandHill[267],Zhaoetal.
[148].
However,asrecentlypointedoutbyAhamdietal.
(2013),akindofcomplexityofLyapunovfunctionsforswitchedlinearsystemsexistsifthesearesoughtinthetraditionofquadraticstability,duetotheunderlyinglinearalgebra[117,118,139]thatseemsevenset-theoreticmethodsincontrol[28]couldnotbeovercome.
Indeed,duringthelastcoupleofdecadesmanynewand/orinnovatedexitingstabilityresultsforcomplexdynamicnetworksandsystemsandfornetworkcontrolsystems,allbasedontheideasaboutLyapunovfunctionsandLaypunov–-Krasovskiifunctionals,haveemerged;forinstance,see[13,25,27,43,51,78,86,103,104,140,145–151,178,179,212,224,269–273].
Furthermore,evencom-putationalintelligence[46,60,90,129,191],basedoneitherfuzzysystemsorneuralnetworks,recentlyhavebeenhandledascomplexnonlinearsystemsbymeansofnoveldevelopmentsofeitherLyapunovfunctionsorLyapunov–-Krasovskiifunctionals[13,52,78,103,104,152,178,183,221,254,261].
IntheviewoftheseitmaywellbeinferredthatthederivationofsophisticatedLyapunovfunctionsand/orLyapunov–Krasovskiifunctionalsincombinationwiththedynamicgraphsandtheprincipleofincreasingprecisionwithdecreasingintelli-gencearethebuildingblocksforfutureexplorationofcomplexdynamicnetworksandsystemsunderintegratedsupervisionandcontrol.
However,asshownbyFilippovandArscott[71]andbySiljak[207,210],thestabilityproblemrequiresconstructiveuseoftechniquesbasedonthetheoryofdifferentialinclusions,Foreword:FascinatingIdeasonComplexityandComplexSystemsControlxxve.
g.
,seeAubinandCellina[18],andbasedonthetheoryoffunctionaldifferentialequations,e.
g.
,seeHaleandLumel[87].
Thestabilityprobleminsuchsystemsisbyfarmoreinvolvedandsubtletohandleinaclear-cutway.
ConcludingRemarksInthisforeword,anattemptwasmadetobringmanyup-to-datefacetsofcom-plexityandcomplexsystems.
Itisonlyuptotheinterestedreadershiptoevaluatewhetherandtowhatextentithasbeenaccomplished.
Tothisauthor'sbelief,theconceptoforganizationisthemostfundamentaloneintothefurtherquestfordeepercomprehensionofcomplexdynamicnetworksandsystemsifatheoreticallysound,systematic,andyetreasonablypragmaticengineeringdesigncreativityhastobeachieved.
Thisseemstobeanappropriateaheadperceptionforthefuture,whichislargelyarguedforintheprecedingsectionsaswellasindicatedinFigs.
7and9.
Itisbyintention,andbythepermissionofProf.
Ji-FengZhang,theEditor-in-ChiefofAASCjournal,thatIselectedandincludedhereFig.
10asmadeofthetwooriginalguresfromarticle[240].
Indeed,itmaywellbearguedthatChinesecolleaguespromotetheparadigm,control–computing–communication(C3)asadynamicallyevolvingentitythat,beingintegratedbymeansofcontrolfunctions,decisionandsupervisionessentiallyremainasimultaneoussystemicinformationprocessingandcommunicationmechanism[17,39,94,179,263,266,271].
Authors,L.
Y.
WangandP.
Zhao,haverightlyentitledtheirarticle"Evolutionofthefeedbackmechanismininformationera";inAASC2(1),70–76(2014).
Butitseemsmorethanjustinterestingtonotice:WasitjustacoincidencewiththedecisionbySpringerEditorialtopublishthisbookalbeitdocumentationarguedthesameparadigmonthegroundsofobservingtheevolutionoflifewithinthecontextofcontrolofcomplexdynamicnetworksandsystemscontrolWell,onlytimemayprovidesomeanswerafterall.
Thismonographhasmaterializedoutoftheeffortsofalargeinternationalgroupofauthorsandmaturedoveraperiodofacoupleofyearsfollowingathemeconferencededicatedtothebook'stitle,forwhichIamprofoundlygratefultothemall.
ItisthereforeonlyinthisforewordIdaredtopresentmyownperceptions,reasoning,andbeliefsaboutcomplexnetworksandsystemsfromacontrolper-spective.
Furthermore,Idaredtoplacetheseonaprospectwithregardtowiderscienticknowledgeandadvancedengineeringtechnologiesavailableatpresent.
Therefore,theresponsibilityissolelyminefortheviewsexpressedhere.
Theseviewsareexpressedviasymbolicparadigmsasalookbackandalookforwardprimarilyonthebackgroundofphysicsalthough—tociteagainwordsoflateProf.
H.
H.
Rosenbrock—"…mathematicsisindispensable…"[189],henceasine-qua-nontoolinsystemsandcontrolsciences.
InthiscontrolintellectualeffortIdidobserveverballythebackgroundmathematicsofsets,setrelations,andsetsofxxviForeword:FascinatingIdeasonComplexityandComplexSystemsControlsetsaswellasgraphsandgraphsfollowingthepigeonholeprincipleofChurch–-Turinghypothesis[129]solelyandintherstplace.
Tillnowonlythecomputa-tionalcomplexityandtheundecided-abilityissueareformallyandrigorouslyexplainedtothefullviatheNP-completenessornon-completeness[126].
Withinthesamecontext,alsothepotentialemergenceofparadoxes[62,63,191,247]hasbeenmadealegitimatemathematicaloutcomeevent.
Intheviewofthesefacts,onemayarguethatsomeparadoxesinthesystem-theoreticsensecouldalsomakelegitimateoutcomeeventsifthesearekeptasquestionableconjectures.
Finally,atthispointIwouldliketoemphasizeagainthefamousremarkputforwardbyProf.
RudolphE.
Kalmaninoneofhismanyplenarylectures:"Firstgetthephysicsofconsideredproblemright.
Therestismathematics.
"IndeedIdoappreciateKalman'sadvicedeeply,despitemyargumentsfavoringthenecessitytoinvolvecognitiveandcomputationalintelligencesciencesaswellintoourFig.
10Thethreecelebritiesofinformation-basedsciencesNorbertWeiner,JohnvonNeuman,andClaudeShannon(a),andtheC3paradigminthejournal,AllAboutSystems&Control,AASC,foundedin2014bytheAcademyofMathematics&SystemsScienceoftheChineseAcademyofSciences(b)Foreword:FascinatingIdeasonComplexityandComplexSystemsControlxxviiperceptionandexplorationofcomplexnetworksandsystems.
Itshouldbewidelynotedforthatmatter,withoutaproperunderstandingofthephysicsbehindanyinvestigatedphenomenonintheoriesandapplicationsofsystemsscience,decisionscience,andcontrolsciencesolelytheuseofsophisticatedmathematicalmethodsandmodelsisboundtoremainonlyanacademicexercise.
Inanycase,myownconclusionisthatthebuildupofanall-encompassingscienceofcomplexnetworksandsystemsisboundtoremainanever-open,lastingquestthatappearstobecorrect,preciselybecauseofmanyfacetsofcomplexity.
"Whodarestosay—thisfarmancangobutnotastepfurther.
"—JeanJacquesRusseaux[51,56].
GeorgiM.
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7(3),225–230(2009b)Foreword:FascinatingIdeasonComplexityandComplexSystemsControlxxxixPreface:AnOverviewoftheContributionsThisbookisamulti-authoredmonographonadvancedresearchintheeldofcomplexdynamicnetworkanddynamicsystemsinvolvingbothevent-drivenandtime-drivenevolutiondynamics,andalsosomestatisticalmechanics,henceemployingsomekindofcombinedcontrolandsupervision.
Itdoespresentanumberofcasestudiesandcertainreectionsinabroaderprospectivetowardsimplementablesystemengineeringcreationsalongthelinesofcomplexdynamicnetworksandsystems.
Thebookcomprisesveparts:1.
Controlandsupervisionforcomplexnetworksandsystems;2.
Machineintelligenceandlearningincom-plexcontrolsystems;3.
Controlandsupervisionofcomplexmechanicalandroboticstructures;4.
Controlandsupervisioninmulti-agentandindustrialsystems;and5.
Novelideasandvariable-structureandswitchedsystemscontrol.
Thisoverviewispresentedconsequentlyfollowingthepartsalongwithenumerationofchaptersalbeitindividualchaptersinthebookaresolelyorderedaccordingly,i.
e.
,donotbearenumeration.
However,thenamesoftheauthorsofeachchapterareincludedbeneaththetitleoftheirrespectivecontribution.
Initially,thiscollectivemonographhasemergedfromtheselectedasetofselectedcontributions,butinexpandedandrevisedversions,ofaspecialinterna-tionalconferencechairedbyProf.
MogensBlanke,oneoftheleadersofscienticresearchprogramCOSY1995–1999ofEuropeanScienceFoundation(ESF),andalsooneoftheeditorsofthe2001book,ControlofComplexSystems,bySpringer.
Severalofthepresentcontributingauthors,includingthiseditor,alsoparticipatedintheESFresearchprogramincomplexsystemscontrolandwrotethatmonograph.
Thusthisbookisanimportantstepforwardintoboththeoreticalandtechnologicalissuesofcomplexnetworkandsystems.
Themainfeatureincommonofthecontributionsauthoredinthisbookisakindofhighlightingcertainexistingsynergiesofcontrol,computing,andcommunica-tioninordertoachieveaguaranteedstableandsustainableplantsystemoperationwithrobustquality.
Intheindividualchapters,thereappearcontributionsthatrangefromagenerallyapplicablemodel-baseddiagnosisandsystemsengineeringtomedical,tocommunication,topower-gridandairportnetworks,tocreatingbio-logicalbrainsforcontrolapplicationsandsafety-criticalhuman–machinesystems,xlitoprocessindustriesandindustrialcomplexes,tobipedrobots,tolargespacestructuresandUAVs,toprecisionservomechanisms,aswellastootheradvancedmechatronicstechnologies.
Nonetheless,mostofthecontributionsintroducecertainnoveltheoreticaltechniquesforhard-to-controlnetworksandsystems,whichgobeyondstandarddecentralizedfeedbackandwherecompoundsystemarchitecturesofcontrolandsupervisionareemployed.
Itisthissensepresentbookmaybeviewedasakindoffollow-upmonographtothosecollectiveresearcheffortssummarizedinthe2001monographbySpringer.
PartIControlandSupervisionforComplexNetworksandSystemsDiagnosisforControlandDecisionSupportforAutonomousVehiclesMogensBlanke,SrenHansen,andMortenRufusBlasInthischaptertherearepresentedthetheoreticalfoundationsfordesignmethod-ologiesthatnowappearasenablingtechnologyforanewareaofsystemdesignsthatarereliableinpractice.
Yettheyarealsoaffordableduetotheuseoffault-tolerantphilosophiesandtoolsthatmakeengineeringeffortsminimalfortheirimplementation.
Italsoincludestheexamplesforanautonomousaircraftandabalingsystemforagriculturetoillustratethegenericdesignproceduresandreal-liferesults.
Itshouldbenoted,diagnosisand,whenpossible,prognosisoffaultsareessentialforsafeandreliableoperation.
Developmentsofmethodologiesthatcopewithcomplexandnonlinearsystemshaveconsiderablymaturedandmethodologyandassociatedtoolshavebecomeavailableintheformoftheoryandsoftwarefordesign.
Genuineindustrialcaseshavealsobecomeavailable.
Analysisofsystemtopology,referredtoasstructuralanalysis,hasproventobeuniqueandsimpleinuseandarecentextensiontoactivestructuretechniqueshavemadefaultisolationpossibleinawiderangeofsystems.
Followingresidualgenerationusingthesetopology-basedmethods,deterministicandstatisticalchangedetectionhasprovenveryusefulforonlineprognosisanddiagnosis.
Forcomplexsystems,resultsfromnon-Gaussiandetectiontheoryhavebeenemployedwithconvincingresults.
IntegrationofSupervisoryControlSynthesisinModel-BasedSystemsEngineeringJosC.
M.
Baeten,JoannaM.
vandeMortel-Fronczak,andJakobusE.
RoodaThischapterdiscussestheintegrationofrecentlydevelopedsupervisorsynthesistechniquesandtoolsinengineeringplantprocessesbasedonsuitablemodels.
Formalmodelsplayanimportantroleherebecausetheyenabletheuseofvariousmodel-basedanalysesforearlyintegrationtechniques,andtools.
Engineeringprocessesbasedonformalmodelsareshowntobeabletocopewithcomplexity.
Theyalsosupporttime-to-marketanddevelopmentcostsreduction.
Moreover,applicationofsupervisorycontrolsynthesisinthedevelopmentofcontrolsystemsxliiPreface:AnOverviewoftheContributionscanspeeduptheprocessconsiderably.
Theproposedapproachisillustratedbyexamplesofindustrialcases,wheresupervisorssynthesizedhavesuccessfullybeenimplementedandintegratedinexistingresource-controlplatforms.
OutputSynchronizationofDynamicalNetworksHavingNodeswithRelative-Degree-OneNonlinearSystemsYanyanLiu,GeorgiM.
Dimirovski,andJunZhaoThischapterstudiestheoutputsynchronizationproblemincomplexdynamicnetworksthathavenonlineardynamicsystemswithrelative-degree-oneattheirnodes.
Systempropertyofpassivityhasbeenfoundtobeausefultoolforsolvingtheoutputsynchronizationprobleminsuchdynamicnetworks.
Althoughnotalldynamicsystemsmaybepassive,however,itisnonethelessshownstillpassivitycanbesuccessfullyusedtooutputsynchronizedynamicnetworks.
Ifanodenon-linearsystemisweaklyminimumphaseandhasrelative-degree-one,thenitisshowntobefeedbackequivalenttoapassivesystem.
Thefeedbackpassivationresultisexploitedinordertoinvestigatetheoutputsynchronizationofdynamicnetworks.
Theconditionsarefoundunderwhichtheoutputsynchronizationofdynamicnetworks,havingnodenonlinearsystemswithrelative-degree-one,isachievedwithouttheneedthenegativedenitenesspropertyoftheoutercouplingmatrix.
MechanismDesignforIncentiveCompatibleControlofNetworksAnilKumarChorppathandTansuAlpcanThischapterprovidesanoverviewoftherecentresultsintheareaofmechanismsandgamesfordistributedcontrolofnetworksandauthorsrecentcontributions.
Themethodologyandalgorithmsdevelopedareappliedtodiversenetworkcontrolproblemssuchasinterferenceandspectrummanagement.
Theheterogeneousbehaviorofusers,whichrangesfromaltruistictoselshandtomalicious,isbeingmodeledwithintheanalyticalframeworkofgametheory.
Networkmechanismdesignaimstoachievesystem-levelgoalssuchasmaximizationofaggregatenetworkperformanceusingspecicmethodsinnetworks,whereusersarestrategicandselshdecision-makerswithindividualpreferences.
Amechanismdesignapproachisadoptedtoquantifytheeffectofadversarialbehavior,whichrangesfromextremeselshnesstodestructivemaliciousness.
Differentiatedpricingisproposedasamethodtocounterandmitigateadversarialbehavior.
Anadditionalapplicationtothelocationprivacyinmobilecommerceisalsobrieydiscussed.
BuildingSmartGrid:OptimalCoordinationofConsumptionwithDecen-tralizedEnergyGenerationandStorageArazAshouri,SebastianGaulocher,andPetrKorbaThisworkdescribesatimelyimplementationofanofceand/orpersonalsmartgridforenvironmentallyfriendlybuildings.
Thesecanbeequippedwithalocalenergysource(e.
g.
,photovoltaicpanelsorcombinedheat-powerunits),energystoragedevices(batteries,electrichotwaterboilers,heatingandventilationsystemsincludingairconditioning),abuildingenergymanagementsystemwithsensorsPreface:AnOverviewoftheContributionsxliii(e.
g.
,providingtheroomtemperatures),andhouseholdappliancesactingasactu-ators(ingeneral,splitintogroupsofschedulableandnon-schedulableones).
Theideabehindthisworkistodevelopanautomaticcontrolsystemwhichwouldoptimallydecidefortheend-customerwhentobuy,sell,orstoreelectricenergywiththeobjectivetominimizehistotalcosts.
Atthesametime,itfulllsallconstraintsintermsofthelimitsonpowerallowedtobetakenfromthegrid.
Inthisproject,amodelpredictivecontrolapproachtotheenergyoptimizationprobleminabuildinghasbeenproposedbasedonutilizationofareal-timepricingsignalwhichreectsdailypeaksinconsumptiontotheenergymanagementsystem.
Differentscenarioshavebeenrunandtheresultsarediscussedhere.
Passivity-BasedSwitchingRuleandControlLawCo-designofNetworked-SwitchedSystemswithFeedbackDelaysDanMa,andGeorgiM.
DimirovskiInthistheoreticalstudy,aclassofswitchedlinearsystemsunderahybridstatefeedbackcontrollerwithtime-varyingdelaysisstudied.
Themaincontributionisgivenontheissueofhowtoco-designswitchingruleandfeedbackcontrollawsoastomaketheclosed-loopsystemstrictlyinputfeed-forwardoutput-feedbackpassiveforalladmissibletimedelaysinthefeedbackchannels.
Sufcientcondi-tionsforstrictinputfeed-forward,output-feedback'passivitication'ofswitchedsystemswithtime-varyingdelaysundersomestate-dependentswitchingrulebyusingthemethodofmultiplestoragefunctionsisderived.
Theproposedswitchingrulecanachievestrictinputfeed-forward,output-feedbackpassivityoftheswitcheddelaysystemswhoseallsubsystemscanbeinputfeed-forwardoutput-feedbacknon-passive.
ThenitegainL2stabilityinclosed-loopisguaranteed.
Furthermore,undertheproposedswitchingrule,theasymptoticstabilitycanbeguaranteediftheswitchedsystemiszero-statedetectablewhenexogenousdisturbanceinputiszero.
PartIIMachineIntelligenceandLearninginComplexControlSystemsCreatingandControllingComplexBiologicalBrainsKevinWarwickThischapterpresentsacloserlookintohowanimaland/orhumanbraincellscanbecultivated(grown)andgivenarobotphysicalbody(asacontrollingbrain)inwhichtheycanmovearoundandinteractwiththeworld.
Theseobservationsareutilizedtoproposeadesignthatisaimedatcreatingaspecickindofcyborg.
Thisisrealizedasanewformofarticialintelligenceinwhichthecomplexityofahighlynonlinearbiologicalneuralnetworkisemployedtouniquelycontrolareal-worldrobot.
Anadequatepresentationisgiveninwhichthecommunication/controlxlivPreface:AnOverviewoftheContributionsfeedbackloopisdescribedandconsideredintermsoflearning,performance,long-termoperation,andspecializationwithintheneuralstructure.
Experimentalresultsarepresentedandalsoanoutlineofcertainopenphilosophicalargumentsisgiven.
IterativeLearningControlasanEnablerforRobotic-AssistedUpperLimbStrokeRehabilitationEricRogers,ChrisT.
Freeman,Ann-MarieHughes,JaneH.
Burridge,KatieL.
Meadmore,andTimExcellInthischapter,arecentresearchissurveyedwhereiterativelearningcontrol,developedinitiallyforrobotsexecutingcommonlyencounteredindustrialtaskssuchassequentiallycollectingobjectsfromonelocationandtransferringthemtoanother,isusedtocontroltheassistivestimulationinrobotic-assistedupperlimbstrokerehabilitation.
Thepresentationisaccompaniedwithanumberofbothanalyticalandempiricalresultsobtainedinthecourseofthisresearchendeavor.
Theresultsgivenincludetheoutcomesofsmall-scaleclinicaltrialswithstrokepatients,andareasforfutureresearcharealsobrieydiscussed.
Thisresearchisaimedatcopingwithanincreasedburdenonhealthcareandrehabilitationresourcesduetothenumberofpeoplesufferingastrokeandthereforenovelapproachestorehabilitationarerequired,ifthecapacityofhealthservicesistomeetfuturedemands.
AdaptiveFuzzyModelingBasedQuantitativeAssessmentofOperatorFunc-tionalStateinComplexandSafety-CriticalHuman–MachineSystemsJian-HuaZhangandRu-BinWangInthischapterthehumanoperatorfunctionalstate,OFS,isquantitativelyestimatedbyusingmultiplesourcesofmeasuredpsycho-physiologicaldata.
Inthedataacquisitionexperiments,anautomation-enhancedCabinAirManagementSystem(aCAMS)wasemployedtosimulatewithhighdelityahighlycomplexmultitaskplatformofhuman–machinecooperativeprocesscontrol.
Twotypesofadaptivefuzzymodels,viz.
,adaptive-network-basedfuzzyinferencesystemandgeneticalgorithmbasedMamdanifuzzymodel,areconstructedtoestimatethetemporaluctuationsoftheOFS.
Thefuzzymodelsareusedtorevealthecomplexunknowncorrelationbetweenthepsycho-physiological(i.
e.
,electroencephalographicandcardiovascular)variablesandtheoperatorperformance(i.
e.
,primary-task-relatedperformance).
Theadaptivefuzzymodelingparadigmwasvalidatedbyusingthedatameasuredfromagroupofyounghealthyandwell-trainedmalesubjects(twotrialsforeach),whowereengagedinthemanualcontroltasksunderaCAMSexperimentalenvironment.
SpaceIndependentCommunityDetectioninAirportNetworksEmilGegov,MariaNadiaPostorino,AlexanderGegov,andBorianaVacthovaInthisresearchcontribution,theproblemofcommunitydetectionhasbeeninvestigatedwithinlargenetworkswithhighlychangeablebutmostoftenunpre-dictableows.
ThegivenobjectsofexplorationarethetopologyandpassengerPreface:AnOverviewoftheContributionsxlvowsoftheUnitedStatesAirportNetwork(USAN)overtwodecades.
Thenetworkmodelconsistsofatime-seriesofsixnetworksnapshotsfortheyears1990,2000,and2010,whichcapturebimonthlypassengerowsamongUSairports.
Thevol-umeoftheseowsisnaturallyaffectedbyspatialproximity,andtherefore,amodel(recentlyproposedintheliterature)accountingforthisphenomenonisusedtoidentifythecommunitiesofairportsthathaveparticularlyhighowsamongthem,giventheirspatialseparation.
Thisresearchresultshighlightthefactthatsomegeneraltechniquesfromnetworktheory,suchasnetworkmodelingandanalysis,canbesuccessfullyappliedforthestudyofawiderangeofcomplexsystems;whileothers,suchascommunitydetection,needtobetailoredforaspecicsystem.
Thusasuccessfulempiricalstudyonthecomplexsystemsinairtransportationalsoinvolvingnetworkmodelingandaimedatcommunitydetectionproblemhasbeenaccomplished.
DecentralizedControlofComplexDynamicSystemsEmployingFunctionEmulationbyNeuralNetworksYuanweiJing,YanxinZhang,VesnaM.
Ojleska,TatjanaD.
Kolemisevska,andGerogiM.
DimirovskiInthiscontribution,anovelrobustadaptivecontroldesignsynthesisisproposedforaclassofmechatronicnonlinearsystemspossessingsimilaritypropertyhasbeenderived.
Thedesignemploysbothhigh-orderneuralnetworksandmath-analyticalresultsinacompatibleway.
Thisapproachexploitsadequateusageofthestructuralfeatureofcompositesimilaritysystemsandofneuralnetworkstosolvetherep-resentationissueofuncertaintyinterconnectionsandsubsystemgainsbyonlineupdatingtheweightsoftheneuralnetworks.
Lyapunovstabilitytheoryandattractiondomainanalysisareused.
Theproposeddesignsynthesisguaranteesthepracticalrealstabilityinclosed-loop,butalsorequiresskillstoobtainlargerattractiondomainsaroundtheoperatingequilibrium.
Thebenchmarkexampleofelasticallyinterconnectedtwoinvertedpendulumsoncarts,thuscreatingacomplexnonlineardynamicsystempossessinginherentuncertainties,isinvestigatedanditsdecentralizedcontrolsolved.
NeuralNetworkswithStrongAnticipationandSomeProblemsofComplexityTheoryOleksandrS.
MakarenkoThischapterpresentsthestudyofonenewtypeofmodelsofneuralnetworks,whichtakesintoaccountcertainanticipationproperty.
Asthebasemodelinit,Hopeld-typeofmodelswithanticipationhasbeenexplored.
Thebasicnewqualitiesdiscoveredinthisresearchisthepossibilityofmulti-valuedsolutionsofgivenneuralnetworks.
Differenttypesofbehaviorofsuchsystemshavebeenexploreddependingonparametersofnetworks.
Theproblemsofcomplexsolutionsandstoredinformationhavebeenconsidered,includingthemeasuresofcomplexityindeterministicandnon-deterministiccases.
Presumableapplicationsofsuchmodelsforlivingandsocialsystemsarediscussedwithinthecontextofthesenewtypemodelsofneuralnetworks,whichtakeintoaccountpropertyofanticipation.
xlviPreface:AnOverviewoftheContributionsAsthebasebackgroundmodel,theHopeld-typemodelswithanticipationarefoundtobecrucial.
Differenttypesofbehaviorofsuchsystemshavebeenexploreddependingonparametersofnetworks.
PartIIIControlandSupervisionofComplexMechanicalStructuresandRobotsHowtoCopewithDisturbancesinBipedLocomotionMiomirVukobratovi,BranislavBorovac,MirkoRakovi,andMilutinNikoliNowadayswalkinghumanoid-likerobotshavebecomeanexpandingreality.
Fur-thermore,itisexpectedthatthehumanoidrobotsofthenearfuturewill"live"andworkinacommonenvironmentwithhumans.
Thisimposestherequirementthattheiroperationalefciencyoughttobeclosetothatofhumans.
Themainprereq-uisitetoachievethisistoensuretherobot'sefcientmotionquality,thatis,itsabilitytocompensatefortheever-presentdisturbances.
Thisworkconsiderspre-ciselythestrategiesofhowtocompensateforthedisturbancesofdifferentinten-sities:smallwhicharepermanentlypresentandlargethatjeopardizetherobot'sdynamicbalanceinstantly.
Itisillustratedthatthosetwoclassesofdisturbancesrequirequitedifferentcompensationapproaches.
NewAdaptiveAlgorithmforFlexibleSpacecraftControlVladislavY.
Rutkovsky,VictorM.
Glumov,andVictorM.
SukhanovDuringthelastcoupleofdecades,thedesign,implementation,anddeploymentoforbitinspaceoflargespacestructureshavebeenexpandedtounprecedentedextent.
Alltheselargespacestructuresareessentiallyexiblestructures,whichexhibitdelicatedynamicsevenwhenmotiononorbitiswellsettled.
Forthecaseoflargespacestructurecontrol,anewadaptationalgorithmforsystemwithreferencemodelisproposed.
Itsoperationdoesnotdependontheintensityandspectralcompositionoftheinputactionsanditsrealizationdoesnotrequireestimationofexternaldisturbances.
Theproposedalgorithmfunctioningisillustratedontheexampleoflargespacestructurecontrol.
Itisanewtypeoflarge-sizespacecraft(spaceenergystations,largeorbitingreectors).
Suchanobjectcannotbeinsertedintoorbitinassembledconditionbecauseofitsbigsize.
ThereforeLSSisassembledinorbitanditisadiscretelyevolvingstructure.
Asthecontrolobjectitismulti-frequencyoscillatingsystemwithdiscretelytime-varyingparametersandnumberoffreedomdegrees.
Forthecaseoflargespacestructurecontrol,proposedalgorithmissimplied;yetthedesignedcontrolsystemperformshigh-precisionoperation.
Preface:AnOverviewoftheContributionsxlviiState-DependentRiccatiEquation-BasedTrackingControlofaHydraulicSeismicIsolatorTestRigStefanoPagano,RicardoRusso,SalvatoreStrano,andMarioTerzzoAnoveldesignandimplementationofhydraulicseismicisolatortestrigwhichemploysanonlinearoptimaltrackingcontrolbasedonthestate-dependentRiccatiequation(SDRE)techniquehasbeendeveloped.
Itisaimedattestingthedeviseandsystemswhichareusedmitigateeffectsduetoeitherearthquakeorseverstormwinds.
Earthquakeandwindstormeffectscanbemitigatedbymeansofbaseisolationstrategies.
Thebaseisolationistypicallyeffectedusingpassive,semi-active,oractivesystems.
Thesedevicesmustbetestedinordertoobtainthehorizontalforce-displacementcyclethatallowsfordeducinganalyticaldescriptionoftheirdynamiccharacteristicsiftheyaretobepracticallyused.
TheSDREalgorithmfullypreservessystemnonlinearities,bringingthenonlinearsystemtoalinearstructurewithstate-dependentcoefcient(SDC)matrices.
Thelinearquad-ratic(LQ)synthesismethodhasbeenbeappliedtothisstate-dependentstate-spaceequationcharacterizedbytheSDCmatricesandimprovedcontroldesignachieved.
AdSPACEDS1103hardwarehasbeenemployedforthecontrolimplementationandalsoforthereal-timeresolutionoftheSDRE,whichsupportedbytheobtainedresultsfromreal-timeexperiments.
Multi-RobotNavigationUsingMarket-BasedOptimizationRainerPalm,AbdelbakiBouguerra,andMuhammadAbdullahThiscontributionisdedicatedtoathoroughinvestigationofthearticialforcepotentialeldsforobstacleavoidanceandtheiroptimizationbyamarket-basedapproachinscenarioswhereseveralrobotsareactinginasharedarea.
Thepotentialeldmethodhasbeenenhancedbyfuzzylogic,trafcrules,andthetechniqueofmarket-basedoptimization(MBa).
Fuzzyrulesareusedtodeformrepulsivepotentialeldsinthevicinityofobstaclestoproducesmoothermotionsaroundthem.
Trafcrulesareusedtodealwithsituationswhererobotsarecrossingeachother.
TheMBa,ontheotherhand,isusedtostrengthenorweakenrepulsivepotentialeldsgeneratedduetothepresenceofotherrobots.
Fortestingandverication,thenavigationstrategyisimplementedandtestedinsimulationofmorerealisticvehicles.
ExtensivesimulationexperimentsareperformedtoexaminetheimprovementofthetraditionalpotentialeldmethodbytheMBastrategyandverifytheperformanceachieved.
Fault-TolerantEstimationofUAVDynamicsviaRobustKalmanFilterChingizHajiyevandHalilErsinSokenThiscontributedchapterpresentsanovelrobustadaptivealgorithmforestimatingsensorandactuatorfaultsinunmannedaerialvehicles(UAV).
AcovariancescalingbasedrobustadaptiveKalmanlter(RAKF)algorithmhasbeendevelopedforthecaseofsensor/actuatorfaults.
TheproposedRAKFusesvariablescalefactorsforscalingtheprocessandmeasurementnoisecovariancesandeliminatingtheeffectofthefaultsontheestimationprocedure.
FirsttheexistingcovarianceestimationxlviiiPreface:AnOverviewoftheContributionsbasedadaptationtechniquesarereviewed.
Afterchoosingtheefcientadaptationmethod,anoverallconceptfortheRAKFisproposed.
Inthisconcept,thelterinitiallyisolatesthefault,eitherinthesensorsoractuators,andthenitappliestherequiredadaptationprocesssuchthattheestimationcharacteristicisnotdeterio-rated.
TheperformanceoftheproposedltersisinvestigatedviasimulationsfortheUAVstateestimationproblem.
GuidanceLawsandNavigationSystemsforQuadrotorUAV:TheoreticalandPracticalFindingsStojceDeskovski,VaskoSazdovski,andZoranGacovskiThischapterpresentsanovelcontributiontowardsthedesignofsmall-size,inex-pensive,quadrotor-basedunmannedaerialvehicle(UAV).
NowadaysUAVsarebecomingessentialformanyapplicationswherehumanpresenceisconsideredunnecessary,dangerous,orimpossible.
Theseapplicationsincludevarietyofsci-entic,civilian,andmilitaryapplications.
Thispaperreectstheeffortsthatwearetakingovertheyearstowardadeeperunderstandingofthesetechnologies.
Apre-sentationofalow-cost,small-sizequadrotorUAVthatwehavemodiedforourexperimentsisgiven.
BothpracticalandtheoreticalresearchactivitiesintheguidancenavigationandcontrolalgorithmsforquadrotorUAVsarediscussedhere.
Theseanalytical,simulation,andexperimentalstudieshaveyieldedcertainnovelndings,whicharereportedinthiscontribution.
PartIVControlandSupervisioninMulti-AgentandIndustrialSystemsDistributedSupervisoryStrategiesforMulti-AgentNetworkedSystemsAllesandroCasavola,EmanuelGarone,andFrancescoTedescoInthischapter,certainnoveldistributedsupervisorystrategiesformulti-agentlinearsystemsthatareconnectedviadatanetworksandsubjecttocoordinationconstraintsarepresentedSuchacoordination-by-constraintparadigmisbasedontheonlinemanagementoftheprescribedsetpointsanditischaracterizedbyasetofspatiallydistributeddynamicsystems,connectedviacommunicationchannels,withpossiblydynamicalcouplingamongthemwhichneedtobesupervisedandcoordinatedinordertoaccomplishtheiroverallobjective.
Twodistributedstrategieswillbefullydescribedandanalyzed.
First,a"sequential"distributedstrategyispresentedwhereonlyoneagentperdecisiontimeisallowedtomanipulateitsownreferencesignal.
Suchastrategyistheninstrumentaltointroduceamoreeffective"parallel"dis-tributedstrategy,inwhichallagentsareallowedtomodifytheirownreferencesignalssimultaneouslyundercertainconditions.
Preface:AnOverviewoftheContributionsxlixPetriNet-BasedSynthesisofAgentCooperationbyMeansofModularityandSupervisionPrinciplesFrantiekapkoviThischapterpresentsanexplorationstudyonthepossibilityandthemeanshowtheprinciplesofmodularityandofsupervisioncanbeutilizedinthesynthesisofthecooperationamongacollectiveofagents.
Subsystemsmodelingagentsofdifferentkindsareunderstoodtobemodulesofdiscrete-eventsystems(DES).
Theyaremodeledbymeansofplace/transitionPetrinets(P/TPN).
AdesiredstrategyofthemutualbehaviorofagentsduringtheircooperationisexpressedbyconditionsfortheDES-basedsupervisorsynthesis.
Then,thesynthesizedsupervisordoesobtrudethecooperationstrategyontheagentsattherealizationofacommonjob.
ThesupervisorsynthesisisrealizedeitherbymeansoftheP/TPNplaceinvariants(P-invariants)orbythevirtuallyextendedmethod,whereP-invariantsarecom-plementedbyconditionsimposedonP/TPNtransitionsand/orontheParikh'svector,especiallyinordertoexpresspriorities.
AdaptiveInternalModel-BasedDistributedOutputAgreementinaClassofMulti-AgentDynamicSystemsEsmaGülandVeyselGaziThiscontributionpresentsanovelstudyoftheagreementprobleminaclassofmulti-agentdynamicsystemsthathaveuncertainties.
Inparticular,thecaseofthedistributedoutputagreementproblemhasbeenstudiedandnovelsolutionisderived.
Theinvestigatedproblemisformulatedasanonlinearservomechanismproblem,andthenanadaptiveinternalmodelbasedcontrollerhasbeenemployedtoachieveagreementoftheagentoutputsusinglocalinformation.
Variousagentneighborhoodtopologieshavebeenconsideredandtheoverallperformancehasbeenveriedusingfairlysimplenumericalsimulations.
Thusanovelsolutiontotheoutputagreementprobleminmulti-agentdynamicsystemshasbeenfoundthattoleratespresenceofuncertainties.
AnExampleofFaultDetectionandReconguration-BasedToleranceWithinDistributedEmbeddedControlSystemsMatjaColnari,DomenVerberandMatejprogarThiscontributedchapterintroducescertainnovel,recentlydevisedsolutionsforthefaultdetectionwithinembeddedcontrolsystems.
Theserepresentakindoffollow-onelaborationonthesuccessfulISTFW5projectIFATIS,whichhasbeencarriedoutattheauthors'LaboratoryforReal-TimeSystemsoftheFacultyofElectricalEngineeringandComputerScienceinMaribor.
Thetopicisrstre-elaboratedandtheoverallresultsoftheoriginalprojectpresentedtosomeextent.
Then,incontinuation,certainlaterenhancementsandimprovementsareshownalltogetherwithoriginalimplementationsofspecicparts.
Inparticular,thediscreteFPGA-andPSoC-basedfaultmonitoringcellsaregivenproperattention.
Allthenovelimprovementsarediscussedviaproperlyemphasizedpresentation.
lPreface:AnOverviewoftheContributionsPredictiveControlofThermalProcessesinComplexIndustrialFurnacesGoranS.
Stojanovski,andMileJ.
StankovskiThischapterpresentsathoroughinvestigationofadvancedpredictivecontrolmethodsforindustrialthermalprocessesthathavebeendevelopedandpracticallyimplementedintheASEInstituteLaboratoryoftheFacultyofElectrical-ElectronicsEngineeringandInformationTechnologiesinSkopje.
Thisresearchislargelycarriedoutonthegroundsofidentiedrepresentationmodelsoftwohigh-power,industrialfurnacesthatareoperatedinourcountry.
Suchindustrialthermalprocessestypicallyrequirehighfuelconsumption,andthereforetheopti-mizationofthefuelcostsisalwaysneeded.
Itiswidelyknownthatreducingthosecostsyieldsdramaticallyreducedcostsofthenalproductdeliveredbytheindustrialplant.
Forthispurpose,theadvancedpredictivecontrolmethodsappearespeciallytailoredforfurnacethermalprocesses,sinceemployingpredictivecon-troltechniquesenforces,atthesametime,theplanttoachievebothfasterresponseandincreasedrobustness.
Thisisclearlysupportedbybothexperimentalandsimulationresultsareobtained.
Closed-LoopControlwithEvolvingGaussianProcessModelsJuKocijanandDejanPetelinThiscontributionpresentsanoveldevelopmentinthedesignofcontrolsystemsthatisbasedonemployingevolvingGaussianprocess(GP)models.
TheGPmodelsareknowntoprovideaprobabilistic,nonparametricmodelingapproachforblack-boxidenticationofnonlineardynamicsystems.
Theycanhighlightareasoftheinputspacewherepredictionqualityispoor,byindicatingthehighervariancearoundthepredictedmean,whichmayoccurduetoeitherthelackofdataortheunderlyingcomplexity.
WhiletheGPmodelsareBayesianmodels,theoutputhasnormaldistribution,expressedintermsofmeanandvariance.
TheevolvingGPmodelistheconceptualapproachwithinwhichvariouswaysofmodeladaptationscanbeused.
Ifthepriorknowledgeaboutthesystemtobecontrolledisscarceortheplantsystemvarieswitheitherthetimeortheoperatingregion,thenthiscontrolproblemcanbesolvedwithaniterativemethodthatadaptsthemodelbymeansofinfor-mationobtainedwithstreamingdataandthusconcurrentlyoptimizeshyper-parametervalues.
PartV:NovelControlIdeasandVariable-StructureSystemsControlAttenuationofUncertainDisturbancesThroughFastControlInputsAlexanderB.
KurzhanskiandAlexanderN.
DaryinInthischapter,thereispresentedanewclassofcontrolsthatensureaneffectsimilartotheoneproducedbyconventionalmatchingconditionsbetweencontrolanddisturbanceinputsinalinearsystem.
However,inthisstudyabroaderclassofPreface:AnOverviewoftheContributionslisuchinputshasbeenobtained.
Thisisduetoanapplicationofpiecewise-constantcontrolfunctionswithvaryingamplitudes,generatedbyapproximationsof"idealcontrols"whicharelinearcombinationsofdelta-functionsandtheirhigherorderderivatives.
Suchaclassallowsforcalculationoffeedbackcontrolsolutionsbysolvingproblemsofopen-loopcontrol,thusreducingtheoverallcomputationburden.
Itisbelievedthatthiscontrolapproachdoesopenanewprospectforfuturedevelopmentsofcontroltechniques.
SlidingManifoldDesignforLinearSystemswithScalarUnmatchedDisturbancesBobanVeseli,BranislavaDraenoviandedomirMilosavljeviThischapterpresentsanefcientslidingmanifolddesignmethodthatminimizestheimpactofunmatcheddisturbancesonslidingmode(SM)dynamicsinvariable-structurecontrolsystems.
Althoughvariable-structurecontrolsystemsareknowntobeinsensitivetoso-calledmatcheddisturbancesinidealslidingmode,nonethelesstheyarevulnerabletotheunmatchedones.
Thesystemsensitivityuponanunmatchedconstantexternaldisturbanceisevaluatedthroughthesteadystatevectornorm.
Aninnitesetoftheslidinghyper-planesthatminimizethechosenoptimizationcriterionisdetermined.
AwayofselectingamanifoldoutofthatsetthatprovidesadoptedSMdynamicsisalsosuggested.
Theproposedapproachhasbeendemonstratedonseveralnumericalexamplesandinvestigatedbymeansofcomputersimulations.
SlidingModeBasedAnti-LockBrakingSystemControlDraganS.
Anti,DarkoB.
Miti,ZoranD.
Jovanovi,StaniaLj.
Peri,MarkoT.
MilojkoviandSaaS.
NikoliThischapterpresentstheresultsofathoroughinvestigationoftheanti-lockbrakingsystemcontrolbymeansofslidingmodecontrol.
Thereareconsidereddifferentcontinuous-anddiscrete-timeslidingmodecontrol(SMC)techniquesinthecontrolofanti-lockbrakingsystem(ABS).
TheSMCisfoundarightchoiceforitscontrolbecauseofitsrobustcharacteristicsintheviewthatinherentlytheABSischar-acterizedbynonlinearanduncertaindynamics.
Thesurveyofcontinuous-timeSMCalgorithmsbasedonnonlinearmodelsofABSisgivenrst.
Then,thediscrete-timenonlinearmodelofABSisderived,andtheoverviewofexistingdiscrete-timeSMCtechniquesispresented.
TheexperimentalresultsaregiventoverifytheeffectivenessoftheinvestigatedSMCmethods.
SwitchingFrequencyOptimizationofDC/ACInvertersUsingSlidingModeKhalifaAl-HoseniandVadimI.
UtkinThischapterinvestigatestheapplicationofsidingmodeinordertoachievetheswitchingfrequencyoptimizationofDC/Acinvertors.
ItiscommonthataDC/ACconverterforthree-phaseloadisdesignedforcontrollingtwovariablessuchasspeedanduxofanACmotor.
Anadditionaldegreeoffreedomcanbeutilizedtominimizetheswitchingfrequency,whichdependsonthevoltageoftheloadneutralpoint.
AmethodologyofswitchingfrequencyminimizationisproposedintheliiPreface:AnOverviewoftheContributionsframeworkofthemodiedhysteresiscontrol.
Theloadneutralpointvoltageisselectedasthethirdvariabletobecontrolled.
First,thetrackingsystemalgorithmisdevelopedandthenoptimizationwiththeswitchingfrequencyasacriterionisperformedbyaproperchoiceofthereferenceinputfortheneutralpointvoltage.
Thesystemaccuracyisdeterminedbythewidthofhysteresisloopandisthesameforanyswitchingfrequency.
Discrete-TimeSliding-ModeServoSystemsDesignwithDisturbanceCom-pensationApproachedomirMilosavljevi,BranislavaDraenoviandBobanVeseliInthischapter,thereispresentedanoveldiscrete-timeslidingmodecontroldesignemployinganewdisturbancecompensator.
Thisnovelcontributionisanessentiallychattering-free,discrete-time,slidingmode,controlalgorithmwithanewcombineddisturbancecompensator.
Itisbasedonswitchingfunctionmeasurementonly.
Theoverallsystembehavesasahighaccuracytrackingsystemwithanexcellentcompensationofmatcheddisturbances.
Thustheproposedservosystemdesignrepresentsanewdesignsynthesissolutiontothisfundamentalcontrolengineeringproblem.
Propertiesoftheproposeddesignmethodaredemonstratedonavelocityandapositionalservosystem.
Analyticallyderivedresultsaswellastheexperi-mentaloneshavedemonstratedasuperiorperformanceincomparisonwiththeexistingdesigns.
PragmaticDesignMethodsUsingAdaptiveControllerStructuresforMecha-tronicApplicationswithVariableParametersandWorkingConditionsStefanPreitl,Radu-EmilPrecup,ZsuzsaPreitl,Alexandra-IuliaStnean,Claudia-AdinaDragoandMircea-BogdanRdacThischapterpresentsanexplorationstudyoftwopragmaticdesignmethodsforcontrollersdedicatedtomechatronicapplicationsworkingundervariablecondi-tions.
Adaptivestructureofthecontrolalgorithmsareknowntoberatherimportantforsuchapplications.
Basically,thedesignisfoundedontwoextensionsofthemodulusoptimummethodandofthesymmetricaloptimummethod(SO-m):theextendedSO-mandthedoubleparameterizationoftheSO-m(2p-SO-m).
Bothmethods,whichareattributedtotheauthors,makeuseofspecicPI(D)controllersthatarecapableofensuringhighcontrolperformanceintermsof:increasedvalueofthephasemargins,improvedtrackingperformance,andefcientdisturbancerejection.
Ashortandsystematicpresentationofthemethodsanddigitalimple-mentationaspectsusinganadaptivestructureofthealgorithmsforindustrialapplicationsaregiven.
Applicationdealswithacascadespeedcontrolstructurefordrivingsystemswithcontinuouslyvariablereferenceinput,momentofinertia,anddisturbance.
Preface:AnOverviewoftheContributionsliiiAcknowledgmentsFirstofall,Iwouldliketoexpressmygratitudetoallthecontributingauthors.
Itwastheirdedicationthatmadethismulti-authoredmonographtomaterializeandcomeintobeing.
Mythanksaredueforthepatiencewithwhichtheyrespondedtovariousrequestofmineduringthelaststageofthiscommonendeavor.
Inpartic-ular,IdoremainindebtedtoProfs.
MogensBlanke,AlexanderB.
Kurzhanskiy,JakobusE.
Rooda,VladislavY.
Rutkovskiy,BranislavaDrazenovic,andKevinWarwickfortheirencouragingsupportthroughoutalltheactivitiesinvolvedinproducingthisbook.
However,myspecialgratitudegoestolateProf.
MiomirK.
Vukobratovic,mypersonalteacherofrobotics,whopassedawayattheveryearlystageofthisworkingendeavor,andthusImissedhisinspiringcounselsomuch.
Atthismoment,IamgladtoextendmysincerethankstobothMs.
KarindeBie,Springer'sproductionmanager,andMr.
OliverJackson,Springer'sengineeringeditor,fortheirunderstandingaboutmydifcultiesandcooperatingwithmeduringtheseyears.
Indeedtheircooperationandhelpwereinstrumentalinbringingthisworktoitsfruitfulend.
Inaddition,byallmeansIowemyprofoundgratitudetomyentirefamilyforbeingverypatientastotolerateoftenmissingmefromhomeandhencetocarryonwithoutahusband,afather,andagrandfather.
Thankyousomuchmydearestones.
lvContentsPartIControlandSupervisionforComplexNetworksandSystems1DiagnosisforControlandDecisionSupportforAutonomousVehicles.
3MogensBlanke,SrenHansenandMortenRufusBlas1.
1Introduction41.
2Graph-BasedAnalysis51.
2.
1ReconfigurabilityandSafety.
61.
2.
2SubsystemServices61.
2.
3ServiceatSystemLevel.
71.
2.
4AvailabilityandSafety81.
2.
5StructureGraph91.
2.
6Constraints91.
2.
7Variables91.
2.
8MatchingandResults101.
2.
9ActiveIsolation111.
2.
10AnalysisofScenarioswithMultipleFaults.
111.
3DesignProcedureBasedonAnalysisofBehaviouralRelations121.
3.
1ToolsforAnalysisofSystemStructureProperties.
.
.
.
121.
3.
2TransformationtoSignalSpaceandAnalysis131.
3.
3RobustResiduals151.
3.
4EvaluationofResiduals151.
4AeroplaneDiagnosisandFaultHandling161.
4.
1AirspeedSensorProblem161.
4.
2ModelforDiagnosis171.
4.
3SignalAnalysis.
191.
4.
4ChangeDetection201.
4.
5Results.
23lvii1.
5Fault-TolerantGuidanceUsingVision231.
5.
1ModellingtheNaturalEnvironment.
251.
5.
2StereoCamera261.
5.
3RobustStereoEnhancementbyTexture261.
5.
4TextonLabelling.
271.
5.
5StructuralModel291.
5.
6ResidualsforFaultDiagnosis291.
5.
7FieldTests301.
5.
8Control321.
6Conclusions33References.
332IntegrationofSupervisoryControlSynthesisinModel-BasedSystemsEngineering39JosC.
M.
Baeten,JoannaM.
vandeMortel-FronczakandJacobusE.
Rooda2.
1Introduction392.
2Overview412.
3Synthesis-BasedSupervisoryControlEngineering442.
4ModelTransformations472.
5IndustrialCases502.
5.
1MRIScanner502.
5.
2Océprinter.
522.
5.
3ThemeParkVehicle532.
6Conclusions56References.
573OutputSynchronizationofDynamicalNetworksHavingNodeswithRelative-Degree-OneNonlinearSystems59YanyanLiu,GeorgiDimirovskiandJunZhao3.
1Introduction603.
2ProblemStatementandPreliminaries623.
3TheOutputSynchronization633.
4AnIllustrativeExample683.
5Conclusion.
70References.
704MechanismDesignforIncentiveCompatibleControlofNetworks73AnilKumarChorppathandTansuAlpcan4.
1Introduction734.
1.
1RevenueMaximizationinWirelessNetworks744.
1.
2NetworkMechanismDesignwithMaliciousUsers.
.
.
744.
1.
3PrivacyinMobileCommerce764.
2GeneralSystemModel774.
3PricingMechanismforDesignerRevenueMaximization79lviiiContents4.
4MechanismDesignandGameModelwithMaliciousUsers.
.
.
824.
5PriceofMaliceinMechanisms.
834.
5.
1PriceofMaliceinVCGMechanism:834.
5.
2PriceofMaliceinIndirectAuctionMechanisms854.
5.
3PriceofMaliceinPricingMechanisms894.
5.
4DifferentiatedPricing.
904.
6PrivacyMechanismModel934.
6.
1PrivacyMechanism974.
7DiscussionandOpenProblems.
97References.
995BuildingSmartGrid:OptimalCoordinationofConsumptionwithDecentralizedEnergyGenerationandStorage101ArazAshouri,SebastianGaulocherandPetrKorba5.
1Abbreviations1025.
2Introduction1025.
2.
1SmartGridPhilosophy.
1025.
2.
2BuildingEnergyManagementSystemsinSmartGrids1045.
3Methodology1055.
3.
1ModelingFrameworkandParadigms.
1055.
3.
2ModelPredictiveControl1065.
4Modeling1085.
5Results1125.
5.
1LoadShifting1125.
5.
2PowerLimiting.
1145.
5.
3EffectofTariffs1155.
5.
4SomePracticalConsiderations1165.
6Conclusions117References.
1186Passivity-BasedSwitchingRuleandControlLawCo-designofNetworkedSwitchedSystemswithFeedbackDelays119DanMaandGeorgiM.
Dimirovski6.
1Introduction1206.
2Preliminaries1226.
3Passivity-BasedSwitchingRuleDesign1266.
4SwitchingRuleandFeedbackControlLawCo-design.
1316.
5AnIllustrativeExample1346.
6Conclusions135References.
135ContentslixPartIIMachineIntelligenceandLearningControlinComplexSystems7CreatingandControllingComplexBiologicalBrains141KevinWarwick7.
1Introduction1417.
2CulturePreparation1437.
3ExperimentalPlatform1447.
4ExperimentalResults1477.
5Learning1507.
6Conclusions1527.
7FutureResearch153References.
1548IterativeLearningControlasanEnablerforRobotic-AssistedUpperLimbStrokeRehabilitation.
157EricRogers,ChrisT.
Freeman,Ann-MarieHughes,JaneH.
Burridge,KatieL.
MeadmoreandTimExell8.
1Introduction1578.
2ILCAppliedtoStrokeRehabilitation.
1598.
2.
1MeasurementinNeurorehabilitation.
1628.
3ILCforRehabilitationofPlanarTasks.
1648.
3.
1HumanArmModel:PassiveSystem1658.
3.
2RoboticControlScheme1668.
3.
3TrajectorySelection.
1698.
3.
4ILCStructureandDesign.
1708.
3.
5ClinicalAssessment.
1748.
4IterativeLearningControloftheUnconstrainedUpperLimb1778.
4.
1StimulatedArmModel1778.
4.
23DControlSchemes1808.
5ConclusionsandFurtherResearch.
184References.
1859AdaptiveFuzzyModelingBasedAssessmentofOperatorFunctionalStateinComplexHuman–MachineSystems189JianhuaZhangandRubinWang9.
1Introduction1909.
2DataAcquisitionExperiments.
1919.
2.
1Subjects.
1919.
2.
2ExperimentalEquipmentsandEnvironment1919.
2.
3ExperimentalTasks1929.
2.
4ExperimentalProcedure1939.
3AdaptiveFuzzyModelingMethods.
1949.
3.
1OFS-RelatedPsycho-physiologicalMarkers1959.
3.
2BasicsofFuzzyModelingParadigm1969.
3.
3Mamdani-TypeFuzzyModel197lxContents9.
4OFSEstimationResultsandDiscussion.
1989.
4.
1OFSEstimationResults1989.
4.
2Discussions2049.
5ConclusionandFutureWork207References.
20810Space-IndependentCommunityDetectioninAirportNetworks.
.
.
211EmilGegov,MariaNadiaPostorino,AlexanderGegovandBorianaVatchova10.
1Introduction21110.
2ResearchMethodology21410.
2.
1NetworkModelling21610.
2.
2NetworkAnalysis21610.
3SimulationResults21910.
3.
1NetworkParameters22010.
3.
2CommunityStructure.
22410.
4Discussion22610.
4.
1NetworkParameters22610.
4.
2CommunityStructure.
22810.
5Conclusion.
236AppendixA.
237AppendixB.
242References.
24711DecentralizedControlofComplexDynamicSystemsEmployingFunctionEmulationbyNeuralNetworks249YuanweiJing,YanxinZhang,VesnaM.
Ojleska,TatjanaD.
Kolemisevska-GugulovskaandGeorgiM.
Dimirovski11.
1Introduction25011.
2ProblemStatementandAssumptions25211.
3ANNEmulation-BaseDecentralizedControloftheSimilarityClassofComplexDynamicSystems25311.
4ApplicationtoComplexInvertedPendulumsMechatronicPlantSystem26111.
5Conclusions264References.
26512NeuralNetworkswithStrongAnticipationandSomeRelatedProblemsofComplexityTheory267OleksandrS.
Makarenko12.
1Introduction26712.
2StrongAnticipationProperty26812.
3NeuralNetworkExamplewithAnticipation27112.
3.
1ClassicalHopfieldModel27112.
3.
2NeuralNetworkwithAnticipation.
272Contentslxi12.
4NumericalRealizationofSimpleModelwithAnticipation.
.
.
.
27312.
4.
1CalculationResults27312.
5MathematicalandAppliedProblemsforFutureInvestigations27712.
6ConclusionsandFurtherLinesofInvestigations279References.
280PartIIIControlandSupervisionofComplexMechanicalStructuresandRobots13HowtoCopewithDisturbancesinBipedLocomotion285MiomirVukobratovi,BranislavBorovac,MirkoRakoviandMilutinNikoli13.
1Introduction28513.
2BasicIssues28613.
3BipedMechanicalStructure28813.
4CompensationofSmallDisturbances.
29213.
5CompensationofLargeDisturbances.
29713.
5.
1CharacteristicCompensatingMovements29813.
5.
2AnalysisofCompensatingMovements.
29913.
5.
3CompensationInvolvingOnlytheAnkleJoint30013.
5.
4CompensationSimultaneousMotionoftheAnkleandtheHipJoints30313.
5.
5CompensationSimulation—OnlybyAnkleandUsingSimultaneouslyAnkleandtheHipJoints30513.
6Conclusions311References.
31214NewAdaptiveAlgorithmofFlexibleSpacecraftControl313VladislavYu.
Rutkovsky,VictorM.
GlumovandVictorM.
Sukhanov14.
1Introduction31314.
2AdaptationAlgorithmSynthesis31514.
3MathematicalModeloftheLargeSpaceStructure.
32014.
4DesignoftheLSSControl.
32314.
5Conclusion.
325References.
32615State-DependentRiccatiEquation-BasedTrackingControlofaHydraulicSeismicIsolatorTestRig327StefanoPagano,RiccardoRusso,SalvatoreStranoandMarioTerzo15.
1Introduction32715.
2TestRigDescription32815.
3MathematicalModel32915.
4ControllerDesign331lxiiContents15.
5Real-TimeExperiments33315.
6Conclusions334References.
33516Multi-RobotNavigationUsingMarket-BasedOptimization.
337RainerPalm,AbdelbakiBouguerraandMuhammadAbdullah16.
1Introduction33716.
2Navigation,Modeling,andObstacleAvoidance33916.
2.
1NavigationPrinciples.
33916.
2.
2ModelingoftheSystem.
34016.
2.
3ObstacleAvoidanceUsingArtificialForceFields.
.
.
.
34216.
2.
4"Deformation"ofPotentialFieldsUsingFuzzyRules34416.
3MBApproach.
34516.
4MBoptimizationofobstacleavoidance34816.
4.
1MBOBetweenActiveMobilePlatforms34816.
5SimulationResults34916.
5.
1SoftwareFrameworkandPackages34916.
5.
2ExperimentalSetup35016.
5.
3Results.
35216.
5.
4ResultsSummary36016.
6Conclusion.
365References.
36617FaultTolerantEstimationofUAVDynamicsviaRobustAdaptiveKalmanFilter369ChingizHajiyevandHalilErsinSoken17.
1Introduction36917.
2MathematicalModeloftheUAVFlightDynamics37217.
3OptimalKalmanFilterforUAVStateEstimation37417.
4AdaptiveKalmanFiltering37517.
4.
1APrioriUncertainty37517.
4.
2Adaptation37617.
5AdaptiveKalmanFilteringwithNoiseCovarianceEstimation37717.
5.
1Innovation-BasedAdaptiveEstimation(IAE)37717.
5.
2ResidualBasedAdaptiveEstimation(RAE)37817.
5.
3DrawbacksofAdaptiveEstimationMethods.
37917.
6AdaptiveKalmanFilteringwithNoiseCovarianceScaling.
.
.
.
37917.
6.
1Innovation-BasedAdaptiveScaling37917.
6.
2Residual-BasedAdaptiveScaling38217.
7AdaptiveKalmanFilteringfortheUAVStateEstimation.
38317.
7.
1ComparisonoftheNoiseCovarianceEstimationandScalingTechniquesfortheUAVStateEstimation.
.
.
.
38317.
7.
2SimultaneousQ-andR-Adaptation385Contentslxiii17.
8TheRAKFAlgorithmfortheUAVStateEstimation.
38617.
8.
1TheOverallRAKFAlgorithm38617.
8.
2NumericalExample38917.
9Conclusions392References.
39318GuidanceLawsandNavigationSystemsforQuadrotorUAV:TheoreticalandPracticalFindings.
395StojcheDeskovski,VaskoSazdovskiandZoranGacovski18.
1Introduction39518.
2ConceptofLow-CostUnmannedAerialVehicle—Quadrotor39618.
3QuadrotorNavigationSystem39818.
4QuadrotorGuidanceandControlSystem39918.
5SimulationandResults40318.
6ConclusionandFutureWork406References.
406PartIVControlandSupervisioninMulti-AgentandIndustrialSystems19DistributedSupervisoryStrategiesforMulti-agentNetworkedSystems411AlessandroCasavola,EmanueleGaroneandFrancescoTedesco19.
1Introduction41119.
2SystemDescriptionandProblemFormulation.
41419.
3DistributedCG41619.
3.
1SequentialProcedure(S-FFCG)41619.
3.
2ParallelFFCG(P-FFCG)41819.
4IllustrativeExample:CoordinationofAutonomousVehicles.
.
.
42019.
5Conclusions426References.
42620PetriNet-BasedSynthesisofAgentCooperationbyMeansofModularityandSupervisionPrinciples.
429Frantiekapkovi20.
1Introduction42920.
2ModularityatBuildingdesModels43120.
2.
1InterconnectionsbyPNTransitions43220.
2.
2InterconnectionsbyPNPlaces43220.
2.
3InterconnectionsbybothPNPlacesandPNTransitions43320.
2.
4ConnectingPNModulesofAgentsbyPNTransitions433lxivContents20.
3SupervisionandtheAgentCooperation43620.
3.
1UsingP/TPNP-InvariantsatAgentCooperationSynthesis43620.
3.
2AGeneralApproachtoAgentCooperationSynthesis44020.
4Self-ContainedSynthesisoftheSupervisor.
44720.
5Conclusion.
448References.
44921AdaptiveInternalModel-BasedDistributedOutputAgreementinaClassofMulti-AgentDynamicSystems451EsmaGülandVeyselGazi21.
1Introduction45121.
2AgentModelandProblemDefinition45221.
3NeighborhoodTopologies45421.
4ControllerDesign45621.
5SimulationResults46321.
6ConcludingRemarks470References.
47022AnExampleofFaultDetectionandReconfiguration-BasedToleranceWithinDistributedEmbeddedControlSystems473MatjaColnari,DomenVerberandMatejprogar22.
1Introduction47322.
2BriefIFATISProjectOverview.
47422.
2.
1ModificationstotheModel47822.
3FaultDetectionbyMonitoringCells47822.
4ImplementationsoftheMC48222.
4.
1ImplementationwithDiscreteComponents48322.
4.
2ImplementationUsingProgrammableSoC48422.
4.
3DiscussionAboutDifferentImplementationsofMC48522.
5FutureWork.
486References.
48723PredictiveControlofComplexIndustrialThermalProcesses.
.
.
.
489GoranStojanovskiandMileStankovski23.
1Introduction48923.
2SystemIdentificationoftheIndustrialFurnaceinFZC11-Oktomvri49023.
2.
1Steady-StateGainMatrix49023.
2.
2Time-DelayMatrix49123.
3PredictiveControlofIndustrialThermalProcesses49223.
3.
1PredictiveControl49223.
3.
2SwitchedPredictiveControl492Contentslxv23.
3.
3PredictiveControlwithGeneticAlgorithmsOptimization.
49323.
3.
4HybridModelPredictiveControl49423.
3.
5DiscreteTimeHybridModel49423.
4SimulationResults49523.
4.
1ModelPredictiveControl49523.
4.
2SwitchedMPC49723.
4.
3PredictiveControlwithGeneticAlgorithmOptimization.
49723.
4.
4HybridModelPredictiveControl50023.
5FurtherControlofIndustrialThermalProcesses50223.
6Conclusions502References.
50224Closed-LoopControlwithEvolvingGaussianProcessModels.
.
.
.
505JuKocijanandDejanPetelin24.
1Introduction50624.
2SystemsModellingwithGaussianProcesses.
50624.
3AdaptiveControlAlgorithmsBasedonGaussianProcessModels.
51024.
4EvolvingGP-Model-BasedControl51324.
5IllustrativeExample.
51524.
6Conclusions518References.
519PartVNovelControlIdeasandVariable-StructureSystemsControl25AttenuationofUncertainDisturbancesThroughFastControlInputs525AlexanderB.
KurzhanskiandAlexanderN.
Daryin25.
1Introduction52525.
2TheProblem52625.
3GeneralizedControls52725.
4ChoosingAppropriateConstraints52825.
4.
1GeneralCase52825.
4.
2SpecialCase.
52925.
4.
3Example52925.
4.
4ConstraintsforDisturbance53025.
5ControlInputsfortheOriginalSystem53125.
5.
1FirstScheme53225.
5.
2SecondScheme.
53425.
5.
3Example535References.
536lxviContents26SlidingManifoldDesignforLinearSystemswithScalarUnmatchedDisturbances.
539BobanVeseli,BranislavaDraenoviandedomirMilosavljevi26.
1Introduction53926.
2SMinSystemswithUnmatchedDisturbances54126.
3LinearSlidingManifoldDesign54326.
4SlidingModeDynamics.
54626.
4.
1Case14.
2Casem=n154826.
4.
3Casem=154826.
5IllustrativeExamples54926.
6SimulationResults55326.
7Conclusion.
555References.
55527SlidingModeBasedAnti-LockBrakingSystemControl557DraganS.
Anti,DarkoB.
Miti,ZoranD.
Jovanovi,StaniaLj.
Peri,MarkoT.
MilojkoviandSaaS.
Nikoli27.
1Introduction55727.
2ABSDescriptionandGraphicalModel56027.
3Continuous-TimeSMCofABS56227.
3.
1Continuous-TimeABSModel.
56227.
3.
2Continuous-TimeSMCAlgorithms56427.
4Discrete-TimeSMCofABS.
57027.
4.
1Discrete-TimeABSModel57027.
4.
2Discrete-TimeSMCAlgorithms57127.
5ExperimentalResults57227.
6Conclusions577References.
57828SwitchingFrequencyOptimizationofDC/ACInvertersUsingSlidingMode.
581KhalifaAlHosaniandVadimI.
Utkin28.
1ProblemStatementandModelingofDC/ACInverter58128.
2Sliding-ModeControlAlgorithm.
58528.
3SimulationResult59028.
4Conclusion.
593References.
59429Discrete-TimeSliding-ModeServoSystemsDesignwithDisturbanceCompensationApproach.
597edomirMilosavljevi,BranislavaDraenoviandBobanVeseli29.
1Introduction59729.
2Preliminaries59929.
3DisturbanceCompensatorsSynthesis602Contentslxvii29.
4DTSMControloftheFirst-OrderPlants60629.
4.
1VelocityServoSystemDesign60929.
5DTSMControlofaPositionalServoSystem61129.
6SomePracticalRecommendations61529.
7Conclusions616References.
61730PragmaticDesignMethodsUsingAdaptiveControllerStructuresforMechatronicApplicationswithVariableParametersandWorkingConditions619StefanPreitl,Radu-EmilPrecup,ZsuzsaPreitl,Alexandra-IuliaStnean,Claudia-AdinaDragoandMircea-BogdanRdac30.
1Introduction:TheDesignMethods62030.
2PragmaticFormsoftheModulusOptimumMethodandoftheSymmetricalOptimumMethod62230.
3ExtensionsoftheSymmetricalOptimumMethod62430.
3.
1TheExtendedSymmetricalOptimumMethod(ESO-m)62530.
3.
2TheDoubleParameterizationoftheSO-m(2p-SO-m)62630.
3.
3PerformanceEnhancementUsingReferenceFilters.
.
.
63230.
3.
4VariableStructurefortheControllerwithBumplessSwitchoftheControlAlgorithms.
.
.
.
63330.
3.
5TheAutomaticTuning/RetuningSteps.
63430.
4Application:ControlStructureforMechatronicSystemwithVariableParameters63630.
4.
1Steady-StateConditionsandAnti-WindupResetMeasure.
63730.
4.
2Application:TheStripWindingSystemwithVariableMomentofInertia.
Bench-MarkTypeModelforControllerDesign.
63830.
4.
3Application:TheCaseStudyandSimulationResults.
64130.
5Conclusions644References.
645Index649lxviiiContentsEditorandContributorsAbouttheEditorDr.
GeorgiM.
DimirovskiwasbornonDecember20,1941inGreece,invillageNestorion—NestraminAegeanMacedonia.
Currently,heisaResearchProfessor(retiredlife-timeprofessor)ofAutomationandSystemsEngineeringatSt.
CyrilandSt.
MethodiusUniversityofSkopje,RepublicofMacedonia,andofComputerScienceandInforma-tionTechnologiesatDogusUniversityofIstanbul,RepublicofTurkey.
In2015,hewaselectedanActiveMemberoftheEuropeanAcademyofSci-encesinSalzburg,Austria,whilein2004hewaselectedaForeignMemberoftheAcademyofEngi-neeringSciencesinBelgrade,Serbia.
Dr.
DimirovskiisaninvitedguestprofessoronthegraduatestudiesatIstanbulTechnicalUniversity(AeronauticalEngineering)andbeforehewasatDokuzEylulUniversityofIzmir(MechatronicsEngineering)too;part-timeteaching.
In2011,hewasawardedthehonor'ProUniversitas'ProfessorofObudaUniversityinBudapest,Hungary,andincludedintheacademicstaffoftheDoctoralSchoolthere.
Since2011,hehasbeenteachinginsummergraduateschoolsateitherofuniversitiesinDalian,Nanjing,Shanghai,andShe-nyang.
HereceivedhisPh.
D.
inACCin1977fromtheUniversityofBradford,UK.
Hehasobtainedhisdegrees:Dipl.
-Ing.
inEEfromSt.
CyrilandSt.
MethodiusUniversityofSkopje,Macedonia,andM.
Sc.
inEEEfromUniversityofBelgrade,Serbia—thenbothwithintheformerS.
F.
R.
ofYugoslavia—inyears1966and1974,respectively.
Asayoungengineer,Dimirovskispent3yearsintheindustrybeforejoiningtheacademiain1969.
AtUniversityofBradford,hehasheldapostdoctoralpositionin1979,andwasaVisitingProfessorin1984,1986,and1988,respectively.
HehasbeenaVisitingScientisttoWolverhamptonUniversityin1990and1992.
Dr.
DimirovskiwasaSeniorResearchFellowandVisitinglxixProfessoroftheFreeUniversityofBrussels,Belgium,in1994,andalsoofJohannesKeplerUniversityofLinz,Austria,in2000.
Duringthelastthreedecades,hehaspaidlong-orshort-termacademicvisitswithseminarsattheuniversitiesinAalborg,Ankara,Belgrade,Bradford,Bochum,Brussels,Coimbra,Covilha,Duisburg,Grenoble,Hannover,Istanbul,Izmir,Linz,Lisbon,Ljubljana,London,Maribor,Nis,Portsmouth,Sarajevo,Sevastopol,Soa,Split,Valencia,Wien,Wolverhampton,Zagreb,andKaohsiung(TW);Beijing,Dalian,Nanjing,Shang-hai,andShenyang(CN).
HeparticipatedinandservedontheSteeringCommitteeofEuropeanScienceFoundation'sScienticProgrammeonControlofComplexSystems(COSY)1995–1999undertheleadershipofProfs.
KarlAstroemandManfredThoma,alongwithhispostdoctoralresearchfellowandfourgraduatestudents.
Hehassuccessfullysupervisedthreepostdoctoral,16Ph.
D.
,and27M.
Sc.
aswellasmorethan300graduationstudentsprojects,andadvisedmorethan30graduatestudentsattheNEUofShenyangwithintheframeworkofhisacademiccooperationwithProfs.
YuanweiJingandJunZhao.
HehasservedonPh.
D.
evaluationjuriesand/orpanelsforseveraluniversitiesincludingBradfordandWolverhamptonintheUK,IzmirinTurkey,LjubljanainSlovenia,ChennaiinIndia,ZagrebinCroatia,Soa,VarnainBulgaria,andCraiovainRomania.
HewaseditorofsixproceedingsvolumesoftheIFACseriesandofonevolumeoftheIEEESeries.
Internationally,hehascontributedoneeditedresearchmonographbySpringer,nineinvitedthemepapers(chapters)inmonographs,andmorethan100journalarticlesaswellasmorethan350conferencepapersintheIFACandtheIEEEproceedingsseriesalone.
ProfessorDimirovski,asanAssociateEditor(AE),nowservesonEditorialBoardsoftheJournaloftheFranklinInstitute(TheFI,USA),AsianJ.
ofControl(Wiley,TW),AI&Society(Springer,UK),Intl.
J.
ofAutomation&Computing(CAS,CN)aswellasregularlyreviewsforanumberofarchivaljournalsrefereedintheSCIandSCI-Expanded.
BeforeheservedasanAEoftheIEEETransactionsonSystems,Man&Cybernetics(TheIEEE,USA),ProceedingsoftheInstitutionofMechanicalEngineersPt.
ISystems&ControlEng.
J.
(InstitutionMechanicalEngineers.
,UK),FactaUniversitatisJ.
Electronics&Energetics(UniversityofNis,RS),J.
Electrical&ElectronicsEngineering(UniversityofIstanbul,TR),InformationTechnologies&ControlJ.
(BulgarianUnionofAutomationandInformatics,Soa),J.
ofControlEngineering&AppliedInformatics(SRAIT,RO),Automatika(formerS.
F.
R.
Yugoslavia),andwasEditor-in-ChiefofEngineeringJ.
(MK).
Induetimes,hewasawardedgrantsforvenationalprojectsinautomationandcontrolofindustrialprocesses,andtwoincomplexdecisionandcontrolsystemsbytheMinistryofEducationandScienceofMacedonia.
HefoundedtheInstituteofAutomationandSystemsEngineeringattheFacultyofElectricalEngineeringofSt.
CyrilandSt.
MethodiusUniversityin1985.
Hehasinitiatedandsubsequentlyin1981foundedtheETAISociety—MacedonianIFACNMO,waselectedasitsrstpresident,andservedseveraltermsaspresident.
In1996,hejoinedDr.
GoceArsovinfoundingtheIEEERepublicofMacedoniaSection,andin2002joinedDr.
OkyayKaynakinfoundingtheIEEEComputa-tionalIntelligenceChapterofTurkey.
Hehasdevelopedanumberofundergraduateand/orgraduatecoursesincontrolandautomationaswellasothersinrobotics,inlxxEditorandContributorsappliednumerical,fuzzysystemandneural-networkcomputing,andinoperationsresearchathishomeuniversityandatuniversitiesinBradford,Istanbul,Izmir,Linz,andZagreb,respectively.
During1985–1991,heservedthreetermsasPresidentoftheYugoslavAssociationforETAN,thenYugoslavIFACNMO.
During1988–1993,heservedtheEuropeanScienceFoundationonitsExecutiveCouncilandinothercapacitiesaswell.
HeservedtheInternationalFederationofAutomaticControl(IFAC)inthecapacitiesof:Vice-ChairofTC9.
3onDevel-opingCountries,during1996–2002,andofChairduring2002–2005;ChairofCoordinationCommitteeCC9andTechnicalBoardMemberoftheIFAC(TB)during2005–2011.
HehasservedontheIPC'sformanyIFAC,IEEE,ECC,andWACconferences,andforothers.
HewasCo-ChairmanoftheIFACSWIIS2000andoftheIFACDECOM-TT2001,2003,2004,and2007,andoftheIFACCEFIS2007aswellastheProgramChairoftheIEEESMC-2010andIEEECCA-2003,andofthe1993and2003InternationalAASETAIsymposia.
Dr.
DimirovskireceivedtwoYugoslavETANBestPaperAwards:the1974inAuto-maticControlandthe1991inRobotics&Automation.
In2009,theETAISocietyawardedhimtheETAIMeritsAward.
In2011,G.
M.
DimirovskireceivedtheIFACOutstandingServiceAwardfromtheIFACOrganization.
In2009,alongwithDr.
King-QuiLiandProf.
JunZhao,Prof.
G.
M.
Dimirovskireceivedthe2009IETPremiumAwardfromtheUKInstitutionofEngineeringandTechnologyforthebestarticleoftheIET-CTAjournalin2008.
Hispublicationshavereceivedmorethan1280citationsinScopus(Elsevier,NL),morethan790inWeb-of-Science(ThomsonReuters,USA),andmorethan1790citationsinGoogleScholar,untilnow.
BiSvP!
Currentaddress/contactmeans:DogusUniversityofIstanbul,Acibadem,ZeametSk.
21,Kadikoy,Istanbul34722,Turkeye-mail:gdimirovski@dogus.
edu.
tr;Phone:+90-216-544-5555,Extension:1202;Fax:+90-216-5445535ContributorsMuhammadAbdullahrebroUniversity,rebro,SwedenKhalifaAlHosaniElectricalEngineeringDepartment,ThePetroleumInstitute,AbuDhabi,UnitedArabEmiratesTansuAlpcanDepartmentofElectricalandElectronicEngineering,TheUniversityofMelbourne,Melbourne,AustraliaDraganS.
AntiDepartmentofControlSystems,FacultyofElectronicEngi-neering,UniversityofNi,Ni,RepublicofSerbiaArazAshouriDepartmentofMechanicalandProcessEngineering,ETHZurich,Zurich,SwitzerlandEditorandContributorslxxiJosC.
M.
BaetenCentrumWiskundeandInformatica,Amsterdam,TheNether-lands;EindhovenUniversityofTechnology,Eindhoven,TheNetherlandsMogensBlankeAutomationandControlGroup,DepartmentofElectricalEngi-neering,TechnicalUniversityofDenmark,KongensLyngby,Denmark;AMOSCoE,InstituteforTechnicalCybernetics,NorwegianUniversityofScienceandTechnology,Trondheim,NorwayMortenRufusBlasCLAASAgrosystems,Niv,DenmarkBranislavBorovacFacultyofTechnicalSciences,UniversityofNoviSad,NoviSad,SerbiaAbdelbakiBouguerrarebroUniversity,rebro,SwedenJaneH.
BurridgeFacultyofHealthSciences,UniversityofSouthampton,Southampton,UKFrantiekapkoviInstituteofInformatics,SlovakAcademyofSciences,Bratislava,SlovakiaAlessandroCasavolaUniversitàdellaCalabria,Rende,ItalyAnilKumarChorppathTechnicalUniversityofMunichLehrstuhlFürTheo-retischeInformationstechnik,Munich,GermanyMatjaColnariFacultyofElectricalEngineeringandComputerScience,UniversityofMaribor,Maribor,SloveniaAlexanderN.
DaryinDepartmentofComputationalMathematicsandCybernet-ics,MoscowState(Lomonosov)University,Moscow,RussiaStojcheDeskovskiFacultyofTechnicalSciences,UniversitySt.
KlimentOhrid-ski,Bitola,RepublicofMacedoniaGeorgiM.
DimirovskiSchoolFEEIT,St.
CyrilandSt.
MethodiusUniversity,Skopje,RepublicofMacedonia;ComputerandControlDepartment,DogusUniversity,Acibadem,Istanbul,RepublicofTurkeyClaudia-AdinaDragoDepartmentofAutomationandAppliedInformatics,"Politehnica"UniversityofTimisoara,Timisoara,RomaniaBranislavaDraenoviFacultyofElectricalEngineering,UniversityofSarajevo,Sarajevo,BosniaandHerzegovinaTimExellDepartmentofElectronicsandComputerScience,UniversityofSouthampton,Southampton,UKChrisT.
FreemanDepartmentofElectronicsandComputerScience,UniversityofSouthampton,Southampton,UKZoranGacovskiFacultyforInformationandCommunicationTechnologies,FONUniversity,Skopje,RepublicofMacedonialxxiiEditorandContributorsEmanueleGaroneUniversitéLibredeBruxelles,Brussel,BelgiumSebastianGaulocherInstituteofAutomation,UniversityofAppliedSciencesandArtsNorthwesternSwitzerland,Basel,SwitzerlandVeyselGaziDepartmentofElectricalandElectronicsEngineering,IstanbulKemerburgazUniversity,Baclar,Istanbul,TurkeyAlexanderGegovUniversityofPortsmouth,Portsmouth,UKEmilGegovBrunelUniversity,Uxbridge,UKVictorM.
GlumovInstituteofControlSciences,RussianAcademyofScience,Moscow,RussiaEsmaGülTurkishAerospaceIndustries(TAI),FethiyeMahallesi,Kazan,Ankara,TurkeyChingizHajiyevAeronauticsandAstronauticsFaculty,IstanbulTechnicalUniversity,Maslak,Istanbul,TurkeySrenHansenAutomationandControlGroup,DepartmentofElectricalEngi-neering,TechnicalUniversityofDenmark,KongensLyngby,DenmarkAnn-MarieHughesFacultyofHealthSciences,UniversityofSouthampton,Southampton,UKYuanweiJingCollegeofInformationScienceandEngineering,NortheasternUniversity,Shenyang,Liaoning,People'sRepublicofChinaZoranD.
JovanoviDepartmentofControlSystems,FacultyofElectronicEngineering,UniversityofNi,Ni,RepublicofSerbiaJuKocijanJoefStefanInstitute,Ljubljana,Slovenia;UniversityofNovaGorica,NovaGorica,SloveniaTatjanaD.
Kolemisevska-GugulovskaSchoolFEEIT,St.
CyrilandSt.
MethodiusUniversity,Skopje,RepublicofMacedoniaPetrKorbaInstituteofEnergySystemsandFluidEngineering,ZurichUniversityofAppliedSciences,Zürich,SwitzerlandAlexanderB.
KurzhanskiDepartmentofComputationalMathematicsandCybernetics,MoscowState(Lomonosov)University,Moscow,RussiaYanyanLiuStateKeyLaboratoryofSyntheticAutomationforProcessIndustries,NortheasternUniversity,Shenyang,Liaoning,People'sRepublicofChinaDanMaStateKeyLaboratoryofSyntheticalAutomationforProcessIndustries,CollegeofInformationScienceandEngineering,NortheasternUniversity-Shenyang,People'sRepublicofChinaEditorandContributorslxxiiiOleksandrS.
MakarenkoInstituteforAppliedSystemAnalysis,NationalTechnicalUniversityofUkraine(KPI),Kyiv,UkraineKatieL.
MeadmoreDepartmentofElectronicsandComputerScience,UniversityofSouthampton,Southampton,UKMarkoT.
MilojkoviDepartmentofControlSystems,FacultyofElectronicEngineering,UniversityofNi,Ni,RepublicofSerbiaedomirMilosavljeviFacultyofElectricalEngineering,UniversityofIstonoSarajevo,IstonoSarajevo,BosniaandHerzegovinaDarkoB.
MitiDepartmentofControlSystems,FacultyofElectronicEngi-neering,UniversityofNi,Ni,RepublicofSerbiaJoannaM.
vandeMortel-FronczakEindhovenUniversityofTechnology,Eindhoven,TheNetherlandsMilutinNikoliFacultyofTechnicalSciences,UniversityofNoviSad,NoviSad,SerbiaSaaS.
NikoliDepartmentofControlSystems,FacultyofElectronicEngineering,UniversityofNi,Ni,RepublicofSerbiaVesnaM.
OjleskaSchoolFEEIT,St.
CyrilandSt.
MethodiusUniversity,Skopje,RepublicofMacedoniaStefanoPaganoDepartmentofIndustrialEngineering,UniversityofNaplesFedericoII,Naples,ItalyRainerPalmrebroUniversity,rebro,SwedenStaniaLj.
PeriDepartmentofControlSystems,FacultyofElectronicEngi-neering,UniversityofNi,Ni,RepublicofSerbiaDejanPetelinJoefStefanInstitute,Ljubljana,SloveniaMariaNadiaPostorinoMediterraneaUniversityofReggioCalabria,ReggioCalabria,ItalyRadu-EmilPrecupDepartmentofAutomationandAppliedInformatics,"Poli-tehnica"UniversityofTimisoara,Timisoara,RomaniaStefanPreitlDepartmentofAutomationandAppliedInformatics,"Politehnica"UniversityofTimisoara,Timisoara,RomaniaZsuzsaPreitlSiemensA.
G.
,Erlangen,GermanyMircea-BogdanRdacDepartmentofAutomationandAppliedInformatics,"Politehnica"UniversityofTimisoara,Timisoara,RomaniaMirkoRakoviFacultyofTechnicalSciences,UniversityofNoviSad,NoviSad,SerbialxxivEditorandContributorsEricRogersDepartmentofElectronicsandComputerScience,UniversityofSouthampton,Southampton,UKJacobusE.
RoodaEindhovenUniversityofTechnology,Eindhoven,TheNetherlandsRiccardoRussoDepartmentofIndustrialEngineering,UniversityofNaplesFedericoII,Naples,ItalyVladislavYu.
RutkovskyInstituteofControlSciences,RussianAcademyofScience,Moscow,RussiaVaskoSazdovskiFacultyofElectricalEngineering,UniversityGoceDelchev,Shtip,RepublicofMacedoniaHalilErsinSokenInstituteofSpaceandAstronauticalScience(ISAS),JapanAerospaceExplorationAgency(JAXA),Sagamihara,Kanagawa,JapanMatejprogarFacultyofElectricalEngineeringandComputerScience,UniversityofMaribor,Maribor,SloveniaMileStankovskiDepartmentofAutomaticsandSystemEngineering,FacultyofElectricalEngineeringandInformationTechnology,SSCyrilandMethodiusUniversitySkopje,Skopje,MacedoniaGoranStojanovskiDepartmentofAutomaticsandSystemEngineering,FacultyofElectricalEngineeringandInformationTechnology,SSCyrilandMethodiusUniversitySkopje,Skopje,MacedoniaSalvatoreStranoDepartmentofIndustrialEngineering,UniversityofNaplesFedericoII,Naples,ItalyAlexandra-IuliaStneanDepartmentofAutomationandAppliedInformatics,"Politehnica"UniversityofTimisoara,Timisoara,RomaniaVictorM.
SukhanovInstituteofControlSciences,RussianAcademyofScience,Moscow,RussiaFrancescoTedescoUniversitàdellaCalabria,Rende,ItalyMarioTerzoDepartmentofIndustrialEngineering,UniversityofNaplesFedericoII,Naples,ItalyVadimI.
UtkinDepartmentofElectricalandComputerEngineering,TheOhioStateUniversity,Columbus,OH,USABorianaVatchovaBulgarianAcademyofSciences,Soa,BulgariaDomenVerberFacultyofElectricalEngineeringandComputerScience,UniversityofMaribor,Maribor,SloveniaBobanVeseliFacultyofElectronicEngineering,UniversityofNi,Ni,SerbiaEditorandContributorslxxvMiomirVukobratoviMihajloPupinInstitute,Belgrade,SerbiaRubinWangInstituteofCognitiveNeurodynamics,EastChinaUniversityofScienceandTechnology,Shanghai,People'sRepublicofChinaKevinWarwickSchoolofSystemsEngineering,UniversityofReading,White-knights,Reading,UKJianhuaZhangDepartmentofAutomation,EastChinaUniversityofScienceandTechnology,Shanghai,People'sRepublicofChinaYanxinZhangSchoolofElectronicandinformationEngineeringHaidian,BeijingJiaotongUniversity,Beijing,People'sRepublicofChinaJunZhaoStateKeyLaboratoryofSyntheticAutomationforProcessIndustries,NortheasternUniversity,Shenyang,Liaoning,People'sRepublicofChinalxxviEditorandContributors