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Autonomous landing of a quadrotor on a moving platform using vision-based FOFPID control

Published online by Cambridge University Press:  20 September 2021

Ali Ghasemi*
Affiliation:
Department of Mechanical Engineering, Faculty of Engineering, North Tehran Branch, Islamic Azad University, Tehran, Iran
Farhad Parivash
Affiliation:
Mechanical and Mechatronics Engineering Department, Shahrood University of Technology, Shahrood, Iran
Serajeddin Ebrahimian
Affiliation:
Mechatronics Engineering Department, Faculty of Mechanical Engineering, K. N. Toosi University of Technology, Tehran, Iran
*
*Corresponding author. E-mail: [email protected]

Abstract

This research deals with the autonomous landing maneuver of a quadrotor unmanned aerial vehicle (UAV) on an unmanned ground vehicle (UGV). It is assumed that the UGV moves independently, and there is no communication and collaboration between the two vehicles. This paper aims at the design of a closed-loop vision-based control system for quadrotor UAV to perform autonomous landing maneuvers in the possible minimum time despite the wind-induced disturbance force. In this way, a fractional-order fuzzy proportional-integral-derivative controller is introduced for the nonlinear under-actuated system of a quadrotor. Also, a feedback linearization term is included in the control law to compensate model nonlinearities. A supervisory control algorithm is proposed as an autonomous landing path generator to perform fast, smooth, and accurate landings. On the other hand, a compound AprilTag fiducial marker is employed as the target of a vision positioning system, enabling high precision relative positioning in the range between 10 and 350 cm height. A software-in-the-loop simulation testbed is realized on the windows platform. Numerical simulations with the proposed control system are carried out, while the quadrotor system is exposed to different disturbance conditions and actuator dynamics with saturated thrust output are considered.

Type
Research Article
Copyright
© The Author(s), 2021. Published by Cambridge University Press

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