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dc.contributor.authorHow, Jonathan
dc.contributor.authorChoi, Han-Lim
dc.contributor.authorUndurti, Aditya
dc.contributor.authorRedding, Joshua
dc.date.accessioned2009-10-07T22:42:26Z
dc.date.available2009-10-07T22:42:26Z
dc.date.issued2009-10-07
dc.identifier.urihttp://hdl.handle.net/1721.1/49418
dc.description.abstractThis paper presents an extension of existing cooperative control algorithms that have been developed for multi-UAV applications to utilize real-time observations and/or performance metric(s) in conjunction with learning methods to generate a more intelligent planner response. We approach this issue from a decentralized cooperative control perspective and embed elements of feedback control and active learning, resulting in an new intelligent Cooperative Control Architecture (iCCA). We describe this architecture, discuss some of the issues that must be addressed, and present illustrative examples of cooperative control problems where iCCA can be applied effectively.en
dc.language.isoen_USen
dc.publisherAIAAen
dc.relation.ispartofseriesACC;2010-Redding
dc.subjectmultiagent learningen
dc.subjectintelligent controlen
dc.subjectCooperative Controlen
dc.titleAn Intelligent Cooperative Control Architectureen
dc.typeWorking Paperen
dc.contributor.departmentMassachusetts Institute of Technology. Department of Aeronautics and Astronautics
dc.contributor.departmentMassachusetts Institute of Technology. Aerospace Controls Laboratory


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