A trajectory-tracking controller design using L<inf>1</inf> adaptive control for multi-rotor UAVs

Abstract

This paper presents a trajectory tracking controller for multi-rotor UAVs to improve their flight performance in the presence of various uncertainties. The proposed tracking system consists of a velocity guidance law based on relative distance and an L1 adaptive augmentation loop for tracking velocity commands. In the proposed structure, the desired velocity generated by the guidance law is the reference value for the adaptive controller for accurate path tracking. In the guidance law, the desired acceleration is generated based on the relative distance and its derivatives, and the velocity command of the inner control loop is then calculated. The L1 augmentation loop compensates the linear controller to guarantee the flight performance parameters such as tracking accuracy in the presence of uncertainties, which include aerodynamic disturbances, modeling error, outdoor environmental factors, and flight dynamics changes. The proposed controller was validated in actual flight tests to successfully demonstrate its capabilities using a quad-rotor UAV.

Dört rotorlu bir insansız hava aracının görüntü tabanlı otomatik kontrolü ve hedef takibi

“…Böylece, hedefin yerel görüntü konumları kullanarak yanal ve boylamsal pozisyonlar olan Plat ve Plon hesaplanabilir [33]. Daha sonra, daha keskin takip yörüngesi için sönümleme terimi uygulanabilir [34].…”

Development of a Vision-enabled Aerial Manipulator using a Parallel Robot

“…Therefore, the relative body velocity profile generator is designed based on the trajectory tracking guidance law to guarantee consistent performance in the presence of unpredicted effects since the outdoor environment is not artificially controlled. 9) The overall block diagram of the control system proposed is shown in Fig. 7 (a), and the enlarged block diagram of the L1 adaptive output feedback-based velocity controller is shown in Fig.…”

“…7 (b), a baseline controller with an adaptive output feedback scheme is applied to overcome internal and external uncertainties such as wind gusts or system modeling error, etc. 9) The structure of the baseline controller is simply constructed using proportional-derivative (PD) feedback control since the L1 adaptive loop can compensate for any uncertainties by generating the additional relative velocity control command. Therefore, the system can perform the desired waypoint tracking or IBVS framework flight mode automatically according to the mission status.…”

A Multi-Feature and Multi-Level Matching Algorithm Using Aerial Image and AIS for Vessel Identification

“…In recent years, there has been a wealth of research and various vision-based methods made available for Maritime UAV applications. The related research includes the design and control of UAV research [16], business application mode and method research [17], task-oriented path planning and collaborative operation research [18,19]. Ross et al [20] introduced a ship detection and identification system based on the fusion of multiple sensors (including vessel AIS equipment, satellite imagery and radar images).…”