dc.contributor.author | How, Jonathan | |
dc.contributor.author | Choi, Han-Lim | |
dc.contributor.author | Undurti, Aditya | |
dc.contributor.author | Redding, Joshua | |
dc.date.accessioned | 2009-10-07T22:42:26Z | |
dc.date.available | 2009-10-07T22:42:26Z | |
dc.date.issued | 2009-10-07 | |
dc.identifier.uri | http://hdl.handle.net/1721.1/49418 | |
dc.description.abstract | This 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.iso | en_US | en |
dc.publisher | AIAA | en |
dc.relation.ispartofseries | ACC;2010-Redding | |
dc.subject | multiagent learning | en |
dc.subject | intelligent control | en |
dc.subject | Cooperative Control | en |
dc.title | An Intelligent Cooperative Control Architecture | en |
dc.type | Working Paper | en |
dc.contributor.department | Massachusetts Institute of Technology. Department of Aeronautics and Astronautics | |
dc.contributor.department | Massachusetts Institute of Technology. Aerospace Controls Laboratory | |