Aerodynamics of MAV rotors in ground and corner effect

Prothin, Sebastien; Fernandez-Escudero, Claudia; Doué, Nicolas; Jardin, Thierry

doi:10.1177/1756829319861596

Cited by 11 publications

(4 citation statements)

References 1 publication

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Similar simulation methods have been utilized before (see e.g. [32], [33]), with the recent advances focusing on predicting propeller air flow near obstacles [34] and air flows associated with realistic UAV flight patterns [35], [36]. For UAV control system design, CFD methods have been utilized for validating the propeller ceiling effect in bridge inspection [37].…”

Section: Related Work and Motivationmentioning

confidence: 99%

An AI-in-Loop Fuzzy-Control Technique for UAV’s Stabilization and Landing

et al. 2022

View full text Add to dashboard Cite

In this paper, an adaptable fuzzy control mechanism for an Unmanned Aerial Vehicle (UAV) to manipulate its mechanical actuators is provided. The mission (landing) for the UAV is defined to track (land on) an object that is detected by a deep learning object detection algorithm. The inputs of the controller are the location and speed of the UAV that has been calculated based on the location of the detected object.Two separate fuzzy controllers are proposed to control the UAV motor throttle and its roll and pitch over the mission and landing time. Fuzzy logic controller (FLC) is an intelligent controller that can be used to compensate for the non-linearity behaviour of the UAV by designing a specific fuzzy rule base . These rules will be utilized to adjust the control parameters during the mission and landing period in runtime.To add the effect of the ground for tuning the FLC membership function over the landing operation, a computational flow dynamic (CFD) modeling has been investigated. The proposed techniques is evaluated on MATLAB/Simulink simulation platform and real environment. Statistical analysis of the UAV location reported during stabilization and landing process, on both simulation and real platform, shows that the proposed technique outperforms the similar state-of-art control techniques for both mission and landing control.

show abstract

Section: Related Work and Motivationmentioning

confidence: 99%

An AI-in-Loop Fuzzy-Control Technique for UAV’s Stabilization and Landing

et al. 2022

View full text Add to dashboard Cite

show abstract

“…They are near the ceiling (Ceiling effect and sidewall effect) and ground (ground effect and sidewall effect). These effects were studied in [18], as In Low Corner Effect (ILoCE) and In Upper Corner Effect (IUpCE). It tries to analyse the effects and concluded that a source and drain vortex depicting the combined forces is formed in the corners.…”

Section: Aerodynamic Ceiling Ground and Wall Effectmentioning

confidence: 99%

Control Barrier Function-based Predictive Control for Close Proximity operation of UAVs inside a Tunnel

Mundheda¹,

K²,

Kandath³

2023

Preprint

View full text Add to dashboard Cite

This paper introduces a method for effectively controlling the movement of an Unmanned Aerial Vehicle (UAV) within a tunnel. The primary challenge of this problem lies in the UAV's exposure to nonlinear distance-dependent torques and forces generated by the tunnel walls, along with the need to operate safely within a defined region while in close proximity to these walls. To address this problem, the paper proposes the implementation of a Model Predictive Control (MPC) framework with constraints based on Control Barrier Function (CBF). The paper approaches the issue in two distinct ways; first, by maintaining a safe distance from the tunnel walls to avoid the effects of both the walls and ceiling, and second, by minimizing the distance from the walls to effectively manage the nonlinear forces associated with close proximity tasks. Finally, the paper demonstrates the effectiveness of its approach through testing on simulation for various close proximity trajectories with the realistic model of aerodynamic disturbances due to the proximity of the ceiling and boundary walls.

show abstract

“…Hence, there is an emerging need for algorithms and design solutions that will ensure efficient and stable flight of MAVs, even in windy conditions. Modeling aerodynamics is still an active area of research, e.g., for flapping wing drones with complex fluid-to-structure interactions [1], [2] or for rotorcraft in confined spaces [3], [4]. Hence, in order to test and evaluate wind resistance simulation studies are insufficient.…”

Section: Introductionmentioning

confidence: 99%

An Experimental Study of Wind Resistance and Power Consumption in MAVs with a Low-Speed Multi-Fan Wind System

Olejnik

Wang

Dupeyroux

et al. 2022

2022 International Conference on Robotics and Automation (ICRA)

View full text Add to dashboard Cite

This paper discusses a low-cost, open-source and open-hardware design and performance evaluation of a lowspeed, multi-fan wind system dedicated to micro air vehicle (MAV) testing. In addition, a set of experiments with a flapping wing MAV and rotorcraft is presented, demonstrating the capabilities of the system and the properties of these different types of drones in response to various types of wind. We performed two sets of experiments where a MAV is flying into the wake of the fan system, gathering data about states, battery voltage and current. Firstly, we focus on steady wind conditions with wind speeds ranging from 0.5 m s −1 to 3.4 m s −1 . During the second set of experiments, we introduce wind gusts, by periodically modulating the wind speed from 1.3 m s −1 to 3.4 m s −1 with wind gust oscillations of 0.5 Hz, 0.25 Hz and 0.125 Hz. The "Flapper" flapping wing MAV requires much larger pitch angles to counter wind than the "CrazyFlie" quadrotor. This is due to the Flapper's larger wing surface. In forward flight, its wings do provide extra lift, considerably reducing the power consumption. In contrast, the CrazyFlie's power consumption stays more constant for different wind speeds. The experiments with the varying wind show a quicker gust response by the CrazyFlie compared with the Flapper drone, but both their responses could be further improved. We expect that the proposed wind gust system will provide a useful tool to the community to achieve such improvements.

show abstract

Aerodynamics of MAV rotors in ground and corner effect

Cited by 11 publications

References 1 publication

An AI-in-Loop Fuzzy-Control Technique for UAV’s Stabilization and Landing

An AI-in-Loop Fuzzy-Control Technique for UAV’s Stabilization and Landing

Control Barrier Function-based Predictive Control for Close Proximity operation of UAVs inside a Tunnel

An Experimental Study of Wind Resistance and Power Consumption in MAVs with a Low-Speed Multi-Fan Wind System

Contact Info

Product

Resources

About