The proliferation of Unmanned Aircraft Systems has led to demand for Air- to-Air Refuelling capabilities similar to those available to manned aircraft, and there also exist fuel and cost savings which can be realised. Autonomous Air-to-Air Refuelling presents interesting challenges in the areas of control, sensing, and decision making. This thesis focuses primarily on probe-drogue refuelling.
Work exists on automating Air-to-Air Refuelling using conventional leader- follower architectures. In these schemes, the refuelling drogue is aerodynam- ically stabilised but subject to disturbances such as gusts, tanker wake, and receiver bow wave, and the receiver is controlled in such a way as to capture the drogue.
This method does not effectively utilise all available degrees of freedom – the tanker is usually much larger and less manoeuvrable than the receiver, but there is potential to control and harness the drogue’s motion, for ex-
ample by adding aerodynamic control surfaces. This thesis investigates the feasibility of this approach and compares control architectures by which these degrees of freedom may be harnessed.
A drogue control model is developed, and two candidate architectures are investigated: Common-target-point Control uses a shared target point approach, which is found to improve capture rate under turbulence, and is ex- tended using a novel scheduled-gain method. Intimate Control optimises the whole drogue-receiver system using Multiple-Input Multiple-Output tech- niques. Verification of the control schemes is conducted via the Univer- sity of Bristol’s Relative Motion Robotic hybrid testing facility. A well- characterised F-16 aircraft model is used as a surrogate for future mid-sized Unmanned Aircraft System.
This thesis presents evidence that harnessing the additional degrees of freedom available via drogue control is likely to improve capture performance in Autonomous Air-to-Air Refuelling, and has been tested at a higher Tech- nology Readiness Level than is usual in academic fields.
The work presented here forms part of the Autonomous Systems Technol- ogy Related Airborne Evaluation & Assessment (ASTRAEA) programme in the UK, and was funded by Cobham plc.
|Date of Award||9 May 2017|
- The University of Bristol
|Supervisor||Tom S Richardson (Supervisor)|