Abdulghani Mohamed

Development and Flight Testing of a Turbulence Mitigation System for Micro Air Vehicles

There are significant challenges associated with the flight control of fixed-wing micro air vehicles MAVs operating in complex environments. The scale of MAVs makes them particularly sensitive to atmospheric disturbances thus limiting their ability to sustain controlled flight. Bio-inspired, phase-advanced sensors have been identified as promising sensory solutions for complementing current inertial-only attitude sensors. This paper describes the development and flight testing of a bio-inspired, phase-advanced sensor and associated control system that mitigates the impact of turbulence on MAVs. Multihole pressure probes, inspired by the sensory function of bird feathers, are used to measure the flow pitch angle and velocity magnitude ahead of the MAVs wing. The sensors provide information on the disturbing phenomena before it causes an inertial response in the aircraft. The sensor output is input to a simple feed-forward control architecture, which enables the MAV to generate a mitigating response to the turbulence. The results from wind-tunnel and outdoor testing in high levels of turbulence are presented. The disturbance rejection performance of the phase-advanced sensory system is compared against that of a conventional inertial-based control system. The developed sensory system shows significant improvement in terms of disturbance rejection performance compared to that of standard inertial-only control system. It is concluded that a phase-advanced sensory systems can complement conventional inertial-based sensors to improve the attitude-tracking performance of MAVs.

Influence of Turbulence on MAV Roll Perturbations

There are significant challenges in the control of fixed-wing Micro Air Vehicles (MAVs) in high turbulence environments. Birds can sustain stable flight in such environments by obtaining flow information through mechanoreceptors embedded in their wings. Inspired by natures flyers, an investigation into replicating the function of mechanoreceptors with commercially available pressure sensors is presented. Implementation requires an in-depth understanding of the level of correlation that exists between pressure variations over the wing and the roll perturbation of the MAV. This paper investigates the variation in correlation and coherence along a representative wing-chord and wing-span of a MAV. Highest correlation and coherence is found to exist in the vicinity of the leading edge, with significant perturbations which are evident up to ∼35Hz for a 0.49m wingspan MAV.

Towards Autonomous MAV Soaring in Cities: CFD Simulation, EFD Measurement and Flight Trials

MAVs are increasingly being used in complex terrains, such as cities, despite challenges from the highly turbulent flow fields. We investigate the flow around a nominally cuboid building of height 40m both computationally and experimentally in a 1/100th scale wind-tunnel test. A relatively new computational technique, Improved Delayed Detached Eddy Simulation (IDDES), was used for computing the time-varying flow around the building and surrounding domain. The atmospheric boundary layer velocity and turbulent intensity profiles were replicated at the inlet boundary of the computational domain and wind tunnel. The spatial flow field from the CFD was investigated for locating suitable areas of lift, in order to see if soaring flight would be feasible. Good agreement was found with the wind-tunnel results. Flight trials of a small flying wing aircraft were conducted from the roof demonstrating the possibility of keeping aloft with no conventional power system. Soaring was achieved under piloted control and autonomously. The CFD results proved useful in locating the best lift areas and provided insights into path planning.

Gain Scheduled Attitude Control of Fixed-Wing UAV With Automatic Controller Tuning

Fixed-wing unmanned aerial vehicles (UAVs) have become increasingly important in military, civil, and scientific sectors. Because of the existing nonlinearities, effective control this type of UAV remains a challenge. This paper proposes a gain scheduled proportional-integral derivative (PID) control system for fixed-wing UAVs where a family of PID cascade control systems is designed for several operating conditions of airspeed. This is done using an automatic tuning algorithm, where the controllers are automatically selected by deploying an airspeed sensor positioned ahead of the aircraft. Furthermore, the actual gain scheduling is carried out by forming an interpolation between the family members of the linear closed-loop system, which ensures a smooth transition from one operating point to another. Experimental results are conducted in a wind tunnel to show the successful design and implementation of the gain scheduled control system for the fixed-wing UAV and the significant performance improvement over a linear control system without controller adaptation.

Control Strategies for Flight in Extreme Turbulence

The spatial and temporal variations in wind velocity which cause atmospheric turbulence are exacerbated by the topographic and temperature gradients often present at low altitudes. Such gradients exist within the atmospheric boundary layer, which is the region proximate to the ground in which the wind speed varies from near-zero at ground level to the nominal wind speed around 300 m above the ground. With few exceptions for aircraft such as medical evacuation helicopters and crop dusters, low altitude turbulence is a transient problem for manned aircraft in the brief ight phases of take-o and landing. For small unmanned aircraft, however, the entirety of the ight typically exists within an altitude band characterized by high turbulence intensity. Small xed-wing aircraft operating at slow airspeeds are particularly sensitive to turbulence which can generate large disturbances that a ect attitude and ight path stability. UAV control laws are often developed in the absence of signi cant turbulence, since ight tests are often conducted at remote test ranges and on days with benign atmospheric conditions. The environment in which these control laws are developed does not necessarily re ect the expected operating conditions. For new aircraft designs, airworthiness safety review boards may permit ight only in test areas away from structures and population centers. Flight test engineers usually schedule tests for days with calm winds to improve the quality of the aerodynamic and dynamic data measurements. The result of both the expansiveness of typical UAV test sites with the quiescence of the wind conditions is ight at low turbulence intensity which fails to provide sucient excitation to evaluate the disturbance rejection capability of control systems. The objective of the current research is to study how the design of control law parameters a ects the attitude stability and ight path tracking accuracy of xed wing aircraft operating in extreme turbulence. Turbulence is rep

Exploring tandem wing UAS designs for operation in turbulent urban environments

The stability of small unmanned air systems can be challenged by turbulence during low-altitude flight in cluttered urban environments. This paper explores the benefits of a tandem wing aircraft configuration with the implementation of a pressure-based phase-advanced turbulence sensory system on a small unmanned air system for gust mitigation. The objective was to utilise passive and active methods to minimise gust-induced perturbations. Experimentation in repeatable turbulence within a wind tunnel’s test section was conducted. The experiments focus on the roll axis, which is isolated through a specially designed roll-axis rig. The results show improvement over conventional aircraft. This work is part of a larger research project aimed at enabling safe, stable and steady small unmanned air systems flight in urban environments.

Micro air vehicle soaring in urban environments

Micro-air vehicles (MAVs) are envisaged to spend a large portion of their mission within urban environments, which in general are rich in large obstacles (both natural and man-made). These obstacles can be a hindrance to MAV flight, but also have the potential to generate orographic updrafts when wind impinges on them. In theory, MAVs can exploit these updrafts in order to conserve power. However, finding, navigating between, and utilizing these updrafts is a significant challenge. We explore three aspects of this urban soaring challenge: updraft prediction and sensing, path-planning, and control. In an effort to predict urban updrafts, large-scale computational fluid dynamics (CFD) simulations of various environments have been performed. These are then combined with real-time flow field data from several multi-hole pressure probes attached to the MAV to produce better estimates of the current updraft field. The CFD results are used in large-scale path-planning through the use of a randomized planning algorithm to plan energy-efficient paths through known environments. Finally, a demonstration of “wind-hovering” in an orographic updraft using a simplified trajectory determination algorithm and control system is presented. Our vision is an autonomous platform that utilizes a database of flows around canonical shapes, together with a map, and feedback from flow sensors, to effectively navigate between urban soaring locations and maintain prolonged soaring flight.