Intelligent control systems and vision based navigation to enable autonomous aerial refueling of UAVs

Autonomous aerial refueling is an important capability for both civilian and military unmanned air vehicles. This paper develops a candidate autonomous probe-and-paradrogue aerial refueling controller for an existing vision based relative position sensor and navigation system. It examines the feasibility of an autonomous probe-and-paradrogue refueling capability in detail, by first introducing a concept of operations and conducting a trade study which demonstrates a significant improvement in mission effectiveness. An intelligent supervisory system is then presented, which manages the autonomy and mode sequencing of autonomous air refueling operations, including fault and emergency handling. The VisNav relative navigation system and its role in providing accurate measurements is reviewed, and is integrated with a sampled-data Proportional Integral Filter-Command Generator Tracker controller derived in the paper. Feasibility and performance of the combined sensor-navigator-controller system is demonstrated by a simulated unmanned air vehicle docking maneuver to an oscillating paradrogue, in both still air and light turbulence. Results indicate that the system performs well, as no large excursions in the states occur, and control deflections, rates, and effort were well under limits for the still air case. For the turbulence case, docking performance degrades as expected, while still remaining within all limits and specifications.

Intelligent control systems and vision based navigation to enable autonomous aerial refueling of UAVs Conference Paper