Abstract
This paper introduces a novel methodology in order to recover an agile maneuvering aircraft from upset conditions as swiftly as possible. The current methodology based on an angular rate grid, which consists of angular velocity nodes. The aircraft is said to start its motion from an initial condition while the initial angular velocity corresponds to a certain node within the aforementioned angular rate grid. A nonlinear dynamic inversion (NDI) based controller is employed to reach transition angular rates, which are the desired rates before the recovery initiates. Once the desired transition node is reached, the controller produces necessary input signals to recover the aircraft. The time elapsed throughout the whole recovery process is recorded. The same sequence of control actions are repeated for each initial and transition nodes of the grid. In this way, a recovery time graph is obtained. The time graph is then used to determine the reference angular rate trajectory, which provides the minimum recovery time for the given rate envelope. Simulations are carried out by employing a nonlinear high fidelity F-16 model. Simulation results show that there exist such angular rate trajectories results with faster recovery. Therefore, the aforementioned results point out nonintuitive solutions. That is, for certain initial states it is not suitable to directly regulate the angular rates when recovery time is considered. Rather, for some cases, it is more convenient to increase the roll rate first, and then regulate the angular rates.
Original language | English |
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Title of host publication | 2018 IEEE Aerospace Conference, AERO 2018 |
Publisher | IEEE Computer Society |
Pages | 1-8 |
Number of pages | 8 |
ISBN (Electronic) | 9781538620144 |
DOIs | |
Publication status | Published - 25 Jun 2018 |
Event | 2018 IEEE Aerospace Conference, AERO 2018 - Big Sky, United States Duration: 3 Mar 2018 → 10 Mar 2018 |
Publication series
Name | IEEE Aerospace Conference Proceedings |
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Volume | 2018-March |
ISSN (Print) | 1095-323X |
Conference
Conference | 2018 IEEE Aerospace Conference, AERO 2018 |
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Country/Territory | United States |
City | Big Sky |
Period | 3/03/18 → 10/03/18 |
Bibliographical note
Publisher Copyright:© 2018 IEEE.