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Adaptive Robust Servo LQR control of an iced aircraft

Authors
Beheshti, Amin RabieiKim, YoonsooMyong, R.S.
Issue Date
Jan-2023
Publisher
American Institute of Aeronautics and Astronautics Inc, AIAA
Citation
AIAA SciTech Forum and Exposition, 2023
Indexed
SCOPUS
Journal Title
AIAA SciTech Forum and Exposition, 2023
URI
https://scholarworks.gnu.ac.kr/handle/sw.gnu/73466
DOI
10.2514/6.2023-1636
ISSN
0000-0000
Abstract
Aircraft icing can affect the aircraft's stability and dynamic derivatives of aerodynamic coefficients, resulting in a loss of performance, handling qualities, and control that could threaten flight safety. As a result, an autopilot system must be designed to recover the aircraft in any upset conditions, particularly icing conditions. In this paper, an Adaptive Robust Servo Linear Quadratic Regulator (ARS_LQR) is designed to control the altitude and velocity of aircraft in icing circumstances. All aerodynamic derivatives are assumed to vary linearly over time. The nonlinear equations of motion are then linearized using the Jacobean technique around the nominal trajectory of the aircraft in every fixed-time step to construct a time-varying state-space model. Then, to ensure the stability of the system, the standard cost function for LQR is modified with an exponential weight for which ARS-LQR is designed. Simulation results show that the proposed autopilot architecture works well for controlling aircraft in icing conditions. © 2023, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.
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