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dc.contributor.authorZhang, Fumin
dc.contributor.authorFratantoni, David M.
dc.contributor.authorPaley, Derek A.
dc.contributor.authorLund, John M.
dc.contributor.authorLeonard, Naomi Ehrich
dc.date.accessioned2011-05-16T15:53:20Z
dc.date.available2011-05-16T15:53:20Z
dc.date.issued2007
dc.identifier.citationFumin Zhang, D. M. Fratantoni, D. Paley, J. Lund, N. E. Leonard, “Control of Coordinated Patterns for Ocean Sampling,” International Journal of Control, 80(7):1186-1199, special issue on the Navigation, Guidance and Control of Uninhabited Underwater Vehicles, 2007en_US
dc.identifier.issn0020-7179
dc.identifier.urihttp://hdl.handle.net/1853/38880
dc.descriptionThis is a preprint of an article submitted for consideration in the International Journal of Control, 2007, copyright Taylor & Francis; International Journal of Control is available online at: http://www.informaworld.com/smpp/. DOI: 10.1080/00207170701222947en_US
dc.description.abstractA class of underwater vehicles are modelled as Newtonian particles for navigation and control. We show a general method that controls cooperative Newtonian particles to generate patterns on closed smooth curves. These patterns are chosen for good sampling performance using mobile sensor networks. We measure the spacing between neighbouring particles by the relative curve phase along the curve. The distance between a particle and the desired curve is measured using an orbit function. The orbit value and the relative curve phase are then used as feedback to control motion of each particle. From an arbitrary initial configuration, the particles converge asymptotically to form an invariant pattern on the desired curves. We describe application of this method to control underwater gliders in a field experiment in Buzzards Bay, MA in March 2006.en_US
dc.language.isoen_USen_US
dc.publisherGeorgia Institute of Technologyen_US
dc.subjectUnderwater vehiclesen_US
dc.subjectNewtonian particlesen_US
dc.subjectMotion controlen_US
dc.titleControl of coordinated patterns for ocean samplingen_US
dc.typePre-printen_US
dc.contributor.corporatenameGeorgia Institute of Technology. School of Electrical and Computer Engineering
dc.contributor.corporatenameGeorgia Institute of Technology. Center for Robotics and Intelligent Machines
dc.contributor.corporatenamePrinceton University. Dept. of Mechanical and Aerospace Engineering
dc.contributor.corporatenameWoods Hole Oceanographic Institution. Dept. of Physical Oceanography
dc.publisher.originalTaylor & Francis


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