| LDR | | 00000nam u2200205 4500 |
| 001 | | 000000432302 |
| 005 | | 20200224120435 |
| 008 | | 200131s2019 ||||||||||||||||| ||eng d |
| 020 | |
▼a 9781085715836 |
| 035 | |
▼a (MiAaPQ)AAI13900274 |
| 040 | |
▼a MiAaPQ
▼c MiAaPQ
▼d 247004 |
| 082 | 0 |
▼a 620 |
| 100 | 1 |
▼a Szmuk, Michael. |
| 245 | 10 |
▼a Successive Convexification & High Performance Feedback Control for Agile Flight. |
| 260 | |
▼a [S.l.]:
▼b University of Washington.,
▼c 2019. |
| 260 | 1 |
▼a Ann Arbor:
▼b ProQuest Dissertations & Theses,
▼c 2019. |
| 300 | |
▼a 193 p. |
| 500 | |
▼a Source: Dissertations Abstracts International, Volume: 81-03, Section: B. |
| 500 | |
▼a Advisor: Acikmese, Behcet. |
| 502 | 1 |
▼a Thesis (Ph.D.)--University of Washington, 2019. |
| 506 | |
▼a This item must not be sold to any third party vendors. |
| 506 | |
▼a This item must not be added to any third party search indexes. |
| 520 | |
▼a The topic of this dissertation is successive convexification and high performance feedback control for agile flight. This document is divided into three primary branches. The first branch (Chapter 2) is focused on successive convexification-sequential convex programming approach that lends itself well to real-time applications requiring advanced feed-forward guidance. This branch uses a complex rocket landing application to showcase the versatility and computational capabilities of successive convexification.The second branch (Chapters 3-5) applies convexification techniques to quad-rotor motion planning problems. Using flight test results, the work detailed in these chapters shows that convexification techniques like successive convexification can generate trajectories that are trackable by quad-rotors in real-time.The third branch (Chapter 6) is dedicated to developing a high performance feedback control architecture for multi-rotor vehicles. This architecture is designed to complement a variety of feed-forward guidance methodologies by enhancing the system's robustness to model uncertainties and external disturbances. The core of this architecture relies on a fusion between advanced classical control techniques and convex optimization in order to systematically handle actuator saturation and feedback maximization. |
| 590 | |
▼a School code: 0250. |
| 650 | 4 |
▼a Aerospace engineering. |
| 650 | 4 |
▼a Engineering. |
| 690 | |
▼a 0538 |
| 690 | |
▼a 0537 |
| 710 | 20 |
▼a University of Washington.
▼b Aeronautics and Astronautics. |
| 773 | 0 |
▼t Dissertations Abstracts International
▼g 81-03B. |
| 773 | |
▼t Dissertation Abstract International |
| 790 | |
▼a 0250 |
| 791 | |
▼a Ph.D. |
| 792 | |
▼a 2019 |
| 793 | |
▼a English |
| 856 | 40 |
▼u http://www.riss.kr/pdu/ddodLink.do?id=T15492166
▼n KERIS
▼z 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |
| 980 | |
▼a 202002
▼f 2020 |
| 990 | |
▼a ***1008102 |
| 991 | |
▼a E-BOOK |