Perching with fixed wings

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2008.

Bibliographic Details
Main Author: Cory, Rick E. (Rick Efren)
Other Authors: Russell L. Tedrake.
Format: Thesis
Language:eng
Published: Massachusetts Institute of Technology 2008
Subjects:
Online Access:http://hdl.handle.net/1721.1/43045
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author Cory, Rick E. (Rick Efren)
author2 Russell L. Tedrake.
author_facet Russell L. Tedrake.
Cory, Rick E. (Rick Efren)
author_sort Cory, Rick E. (Rick Efren)
collection MIT
description Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2008.
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spelling mit-1721.1/430452019-04-12T09:48:33Z Perching with fixed wings Cory, Rick E. (Rick Efren) Russell L. Tedrake. Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. Electrical Engineering and Computer Science. Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2008. Includes bibliographical references (leaves 43-46). Human pilots have the extraordinary ability to remotely maneuver small Unmanned Aerial Vehicles (UAVs) far outside the flight envelope of conventional autopilots. Given the tremendous thrust-to-weight ratio available on these small machines [1, 2], linear control approaches have recently produced impressive demonstrations that come close to matching this agility for a certain class of aerobatic maneuvers where the rotor or propeller forces dominate the dynamics of the aircraft [3, 4, 5]. However, as our flying machines scale down to smaller sizes (e.g. Micro Aerial Vehicles) operating at low Reynold's numbers, viscous forces dominate propeller thrust [6, 7, 8], causing classical control (and design) techniques to fail. These new technologies will require a different approach to control, where the control system will need to reason about the long term and time dependent effects of the unsteady fluid dynamics on the response of the vehicle. Perching is representative of a large class of control problems for aerobatics that requires and agile and robust control system with the capability of planning well into the future. Our experimental paradigm along with the simplicity of the problem structure has allowed us to study the problem at the most fundamental level. This thesis presents methods and results for identifying an aerodynamic model of a small glider at very high angles-of-attack using tools from supervised machine learning and system identification. Our model then serves as a benchmark platform for studying control of perching using an optimal control framework, namely reinforcement learning. Our results indicate that a compact parameterization of the control is sufficient to successfully execute the task in simulation. by Rick E. Cory. S.M. 2008-11-07T18:55:43Z 2008-11-07T18:55:43Z 2008 2008 Thesis http://hdl.handle.net/1721.1/43045 243780142 eng M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 46 leaves application/pdf Massachusetts Institute of Technology
spellingShingle Electrical Engineering and Computer Science.
Cory, Rick E. (Rick Efren)
Perching with fixed wings
title Perching with fixed wings
title_full Perching with fixed wings
title_fullStr Perching with fixed wings
title_full_unstemmed Perching with fixed wings
title_short Perching with fixed wings
title_sort perching with fixed wings
topic Electrical Engineering and Computer Science.
url http://hdl.handle.net/1721.1/43045
work_keys_str_mv AT coryrickerickefren perchingwithfixedwings