An intelligent drone testbed for control systems and verification

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dc.contributor.authorYahyaabadi, Amin
dc.contributor.examiningcommitteeKhoshdarregi, Matt (Mechanical Engineering) Ho, Carl (Electrical and Computer Engineering)en_US
dc.contributor.supervisorFerguson, Philip (Mechanical Engineering)en_US
dc.date.accessioned2021-09-10T15:08:48Z
dc.date.available2021-09-10T15:08:48Z
dc.date.copyright2021-08-26
dc.date.issued2021-08en_US
dc.date.submitted2021-08-26T14:05:15Zen_US
dc.date.submitted2021-08-26T18:07:51Zen_US
dc.date.submitted2021-08-26T18:43:00Zen_US
dc.degree.disciplineMechanical Engineeringen_US
dc.degree.levelMaster of Science (M.Sc.)en_US
dc.description.abstractAbstract This research develops a drone testbed that enables the rapid development, validation, and qualification of novel spacecraft and drone control algorithms, control hardware, and remote sensing technologies. The drone testbed facilitates advanced navigation and control research by emulating a multitude of dynamic environments, which provides an easily accessible framework for using new technologies in industrial applications. This research introduces an intelligent system identification method to determine the dynamics and aerodynamic parameters of the drone using Particle Swarm Optimization (PSO), a metaheuristic algorithm. This method provides the knowledge of the system's dynamics that is needed for the environment emulation.en_US
dc.description.noteOctober 2021en_US
dc.identifier.urihttp://hdl.handle.net/1993/35956
dc.language.isoengen_US
dc.rightsopen accessen_US
dc.subjectdroneen_US
dc.subjectcontrolen_US
dc.subjectfeed-forwarden_US
dc.subjectsystem identificationen_US
dc.subjectparticle swarm optimizationen_US
dc.subjectPSOen_US
dc.subjectintelligenten_US
dc.subjecttestbeden_US
dc.subjectverificationen_US
dc.subjectaviationen_US
dc.subjectmetaheuristicen_US
dc.subjectspaceen_US
dc.titleAn intelligent drone testbed for control systems and verificationen_US
dc.typemaster thesisen_US
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