ElQemmah, AymanFortino, GiancarloTedesco, Francesco2026-05-052025-02-26http://hdl.handle.net/10955/5788UNIVERSITÀ DELLA CALABRIA. Dipartimento di Ingegneria Informatica, Modellistica, Elettronica e Sistemistica Dottorato di Ricerca in Information and Communication Technologies. Ciclo XXXVIIThedeploymentofswarmingsurfacemarinevehicleoffersnumerousad- vantagesinaquaticenvironments,includingoperationalflexibility,taskand environmentaladaptability,resilience,andscalability.Inthiscontext,coor- dinationtogetherwiththesatisfactionofactuator,state,safety constraints becomesessentialtoenhanceautonomy.Meetingthisdemandischallenging: whileadvancedtechniqueshavebeenproposed,manyofthemarecomplex and/ornecessitatefrequentreplanning,whichcannegativelyimpactperfor- manceandcomputationalintensity.Therefore,readilyimplementableandlow computationallydemandingstrategiesarerequired. Thisdissertationpresents: i) aclassofnoveldistributedsupervisionstrate- giesappliedtomarinesurfacemulti-vehiclessystemstoaddresscoordination problems, ii) anovelsupervisionschemethatbypassestheneedforexplicit modelingand iii) experimentalvalidationofdistributedsupervisionstrategies. ByresortingtoCommandGovernor(CG)ideas,predictivesupervision algo- rithmsareemployedtoeffectivelydealwiththeabovementionedsupervision problems. WhiletraditionaldistributedCGstrategieshaveanon-cooperativeap- proach,inthisdissertationtwodistributedschemesthatpromote cooperation amongagentsareintroduced.Initially,consideringthecomputationallyde- mandingnatureofcooperativeapproaches,themainideaconsists ofleverag- inganon-cooperativenon-iterativesolution,andenhancingitto inducecoop- erationbetweenagents,thuspreservingthelowcomputationalburden. Forthis reason,theresultingschemeisreferredtoas“Cooperation-inducing.”Sub- sequently,inspiredbyadistributedoptimizationalgorithmfrom literature, a moregeneraldistributedapproachthatallowsagentstocomputeanear- optimalcentralizedsolution,isfullydescribedandanalyzed. Inthisrespect, wheretheresultingschemeisreferredtoas“Cooperative,”agentsexchange onlyauxiliaryvariables,thusensuringprivacypreservation.Thedevelopment ofbothschemesenablestheselectionofthemostsuitableapproachbased on specificapplicationrequirements. Concurrently,toaddressthechallengeofsolvingtheCGdesignproblem whenanexplicitmodelrepresentationisnotavailable,anapproachreferredto as“Data-Driven,”ispresented.Thisalternativetothemodel-basedapproach avoidstheneedfortime-consumingmodeling,identification,and validation phasesand,unlikeotherexistingapproaches,doesnotrequireanewdata collectionamidstcontrollermodifications. Finally,withtheaimofevaluatingcomputationalperformances andim- plementabilityofCG-baseddistributedstrategiesonmarinesurfacevehicles, severalexperimentalresultsinvariousenvironmentsarepresented.These re- sultsareobtainedusingprototypesofhighlymaneuverablemarinesurface vehicles,followingacomprehensivedesign,identification,validation,control, anddeploymentprocess.enDistributed Cooperative.Command GovernorSupervision of Marine Surface VehiclesData-driven Command GovernorThesis