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dc.contributor.authorBoss, Connor J.
dc.contributor.authorSrivastava, Vaibhav
dc.date.accessioned2025-04-21T09:57:09Z
dc.date.available2025-04-21T09:57:09Z
dc.date.copyright8/29/2024 12:00:00 AM
dc.date.issued2024
dc.identifier.issn0022-0434
dc.identifier.otherds_147_01_011005.pdf
dc.identifier.urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4305183
dc.description.abstractUsing the context of trajectory estimation and tracking for multirotor unmanned aerial vehicles (UAVs), we explore the challenges in applying high-gain observers to highly dynamic systems. The multirotor will operate in the presence of external disturbances and modeling errors. At the same time, the reference trajectory is unknown and generated from a reference system with unknown or partially known dynamics. We assume the only measurements that are available are the position and orientation of the multirotor and the position of the reference system. We adopt an extended high-gain observer (EHGO) estimation framework to estimate the unmeasured multirotor states, modeling errors, external disturbances, and the reference trajectory. We design a robust output feedback controller for trajectory tracking that comprises a feedback linearizing controller and the EHGO. The proposed control method is rigorously analyzed to establish its stability properties. Finally, we illustrate our theoretical results through numerical simulation and experimental validation in which a multirotor tracks a moving ground vehicle with an unknown trajectory and dynamics and successfully lands on the vehicle while in motion.
dc.publisherThe American Society of Mechanical Engineers (ASME)
dc.titleA High-Gain Observer Approach to Robust Trajectory Estimation and Tracking for a Multirotor Unmanned Aerial Vehicle1
dc.typeJournal Paper
dc.journal.volume147
dc.journal.issue1
dc.journal.titleJournal of Dynamic Systems, Measurement, and Control
dc.identifier.doi10.1115/1.4065758
dc.journal.fristpage11005-1
dc.journal.lastpage11005-13
dc.page13
dc.treeJournal of Dynamic Systems, Measurement, and Control:;2024:;volume( 147 ):;issue: 001
dc.contenttypeFulltext


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