TY - GEN
T1 - Optimization and Trajectory Tracking of Deep Stall Landing for a Variable Forward-swept Wing UAV
AU - Shao, Shuai
AU - Liu, Junhui
AU - Shan, Jiayuan
AU - Zeng, Weijia
AU - Liu, Sidong
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - This paper presents a trajectory optimization and robust trajectory tracking of deep stall landing for a variable forward-swept wing unmanned aerial vehicle (UAV). Firstly, the longitudinal dynamics model of a variable forward-swept wing UAV is established, and the aerodynamic parameters in a wide-range angle of attack (AOA) are obtained using computational fluid dynamics (CFD). Then, considering multiple running and terminal constraints of UAV deep stall landing, Radau pseudo spectrum method is adopted to generate optimal landing trajectory. Furthermore, to cope with the nonlinear and uncertain aerodynamic parameter at high AOA, a robust trajectory tracking controller is designed via combining feedback linearization and extended state observer (ESO). Finally, nonlinear numerical simulation is conducted to verify the proposed method. The simulation results demonstrate that the control accuracy of the designed controller under various disturbances can meet the landing requirements.
AB - This paper presents a trajectory optimization and robust trajectory tracking of deep stall landing for a variable forward-swept wing unmanned aerial vehicle (UAV). Firstly, the longitudinal dynamics model of a variable forward-swept wing UAV is established, and the aerodynamic parameters in a wide-range angle of attack (AOA) are obtained using computational fluid dynamics (CFD). Then, considering multiple running and terminal constraints of UAV deep stall landing, Radau pseudo spectrum method is adopted to generate optimal landing trajectory. Furthermore, to cope with the nonlinear and uncertain aerodynamic parameter at high AOA, a robust trajectory tracking controller is designed via combining feedback linearization and extended state observer (ESO). Finally, nonlinear numerical simulation is conducted to verify the proposed method. The simulation results demonstrate that the control accuracy of the designed controller under various disturbances can meet the landing requirements.
KW - ESO
KW - deep stall landing
KW - forward-swept wing UAV
KW - trajectory optimization
KW - trajectory tracking
UR - http://www.scopus.com/inward/record.url?scp=85129468527&partnerID=8YFLogxK
U2 - 10.1109/ISAS55863.2022.9757298
DO - 10.1109/ISAS55863.2022.9757298
M3 - Conference contribution
AN - SCOPUS:85129468527
T3 - 2022 5th International Symposium on Autonomous Systems, ISAS 2022
BT - 2022 5th International Symposium on Autonomous Systems, ISAS 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 5th International Symposium on Autonomous Systems, ISAS 2022
Y2 - 8 April 2022 through 10 April 2022
ER -