On Low Altitude Flight through the Atmospheric Boundary Layer

Abstract

Major challenges to low speed micro flight are the transient and time-averaged velocities arising from the Atmospheric Boundary Layer (ABL), particularly turbulence a few metres above the ground. In this paper, existing data from meteorologists and wind engineers are reviewed and measurements dedicated to understanding the spatial and temporal velocity fields that MAVs experience are briefly described. Data from a wide variety of terrains are analysed, with the majority of data obtained in relatively well mixed turbulent flow (i.e. away from local effects such as buildings) and for conditions of nominally neutral stability. Spectra for data well removed from local effects exhibited the expected 5/3rds Kolmogorov law. Transient flow pitch angles were investigated (obtained from four small laterally displaced probes), in order to understand the possible roll and pitch inputs to MAVs. It was noted that for all data obtained the variation with lateral separation decreased relatively slowly with reducing separation down to the closest inter-probe spacing of 14mm. This effect is thought to explain the increasing piloting difficulties experienced in maintaining good roll control for decreasing scales of craft when any appreciable atmospheric winds are present.

Urban flow and small unmanned aerial system operations in the built environment

“…With a decrease in the mean wind speed as you approach the ground, turbulence intensity will generally increase as altitude decreases. For the same reason, the turbulence intensity that an UA perceives decreases with increasing flight speed (Mohamed, Massey, Watkins, & Clothier, 2014;Watkins, Milbank, Loxton, & Melbourne, 2006;Watkins, Thompson, Loxton, & Abdulrahim, 2010). Therefore, as the mean relative velocity of the UA increases the relative turbulence intensity for the vehicle decreases.…”

Disturbance Observer Based Control with Anti-Windup Applied to a Small Fixed Wing UAV for Disturbance Rejection

“…By modifying the system to include error dynamics, the state regulation gains are chosen internally by the system once the error weighting Q i has been selected. Following the standard method, details of which can be found in [26], the Algebraic Riccati Equations (ARE) can be solved for the control law (6).…”

“…Moreover, a reduction in aircraft size is generally accompanied by a reduction in operating airspeed. This has reached a critical point for small UAVs where their operating airspeeds are of the same magnitude as the gust disturbances they are subjected to [6]. As a consequence, in gust alleviation for small UAVs, structural loads are less critical condition than flight performance.…”

Bird-inspired Velocity Optimization for UAVs in the Urban Environment

“…S Unmanned Air Vehicles, SUAVs, have the potential to fly at low altitudes within the urban environment making them suitable for a range of missions such as infrastructure monitoring, surveillance, emergency response and small payload delivery [1][2][3][4][5]. However, current SUAVs have two main technology limitations, firstly, SUAVs have limited capacity to cope with the high levels of turbulence and complex flows created by wind interactions within the urban landscape [6][7][8]. Secondly, due to the power-weight constraints in battery technology, SUAVs have a limited range and endurance [9,10].…”