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- Publisher Website: 10.1109/LRA.2020.2976323
- Scopus: eid_2-s2.0-85082174997
- WOS: WOS:000520954200029
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Article: Learning Pugachev's Cobra Maneuver for Tail-Sitter UAVs Using Acceleration Model
Title | Learning Pugachev's Cobra Maneuver for Tail-Sitter UAVs Using Acceleration Model |
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Authors | |
Keywords | Acceleration Aircraft Atmospheric modeling Aerodynamics Mathematical model |
Issue Date | 2020 |
Publisher | Institute of Electrical and Electronics Engineers. The Journal's web site is located at https://www.ieee.org/membership-catalog/productdetail/showProductDetailPage.html?product=PER481-ELE |
Citation | IEEE Robotics and Automation Letters, 2020, v. 5 n. 2, p. 3452-3459 How to Cite? |
Abstract | The Pugachev's cobra maneuver is a dramatic and demanding maneuver requiring the aircraft to fly at extremely high Angle of Attacks (AOA) where stalling occurs. This paper considers this maneuver on tail-sitter UAVs. We present a simple yet very effective feedback-iterative learning position control structure to regulate the altitude error and lateral displacement during the maneuver. Both the feedback controller and the iterative learning controller are based on the aircraft acceleration model, which is directly measurable by the onboard accelerometer. Moreover, the acceleration model leads to an extremely simple dynamic model that does not require any model identification in designing the position controller, greatly simplifying the implementation of the iterative learning control. Real-world outdoor flight experiments on the “Hong Hu” UAV, an aerobatic yet efficient quadrotor tail-sitter UAV of small-size, are provided to show the effectiveness of the proposed controller. |
Persistent Identifier | http://hdl.handle.net/10722/288103 |
ISSN | 2023 Impact Factor: 4.6 2023 SCImago Journal Rankings: 2.119 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | XU, W | - |
dc.contributor.author | Zhang, F | - |
dc.date.accessioned | 2020-10-05T12:07:54Z | - |
dc.date.available | 2020-10-05T12:07:54Z | - |
dc.date.issued | 2020 | - |
dc.identifier.citation | IEEE Robotics and Automation Letters, 2020, v. 5 n. 2, p. 3452-3459 | - |
dc.identifier.issn | 2377-3766 | - |
dc.identifier.uri | http://hdl.handle.net/10722/288103 | - |
dc.description.abstract | The Pugachev's cobra maneuver is a dramatic and demanding maneuver requiring the aircraft to fly at extremely high Angle of Attacks (AOA) where stalling occurs. This paper considers this maneuver on tail-sitter UAVs. We present a simple yet very effective feedback-iterative learning position control structure to regulate the altitude error and lateral displacement during the maneuver. Both the feedback controller and the iterative learning controller are based on the aircraft acceleration model, which is directly measurable by the onboard accelerometer. Moreover, the acceleration model leads to an extremely simple dynamic model that does not require any model identification in designing the position controller, greatly simplifying the implementation of the iterative learning control. Real-world outdoor flight experiments on the “Hong Hu” UAV, an aerobatic yet efficient quadrotor tail-sitter UAV of small-size, are provided to show the effectiveness of the proposed controller. | - |
dc.language | eng | - |
dc.publisher | Institute of Electrical and Electronics Engineers. The Journal's web site is located at https://www.ieee.org/membership-catalog/productdetail/showProductDetailPage.html?product=PER481-ELE | - |
dc.relation.ispartof | IEEE Robotics and Automation Letters | - |
dc.rights | IEEE Robotics and Automation Letters. Copyright © Institute of Electrical and Electronics Engineers. | - |
dc.rights | ©20xx IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | - |
dc.subject | Acceleration | - |
dc.subject | Aircraft | - |
dc.subject | Atmospheric modeling | - |
dc.subject | Aerodynamics | - |
dc.subject | Mathematical model | - |
dc.title | Learning Pugachev's Cobra Maneuver for Tail-Sitter UAVs Using Acceleration Model | - |
dc.type | Article | - |
dc.identifier.email | Zhang, F: fuzhang@hku.hk | - |
dc.identifier.authority | Zhang, F=rp02460 | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1109/LRA.2020.2976323 | - |
dc.identifier.scopus | eid_2-s2.0-85082174997 | - |
dc.identifier.hkuros | 314704 | - |
dc.identifier.volume | 5 | - |
dc.identifier.issue | 2 | - |
dc.identifier.spage | 3452 | - |
dc.identifier.epage | 3459 | - |
dc.identifier.isi | WOS:000520954200029 | - |
dc.publisher.place | United States | - |
dc.identifier.issnl | 2377-3766 | - |