Encoding aerial pursuit/evasion games with fixed wing aircraft into a nonlinear model predictive tracking controller

Unmanned aerial vehicles (UAVs) have shown themselves to be highly capable in intelligence gathering, as well as a possible future deployment platform for munitions. Currently UAVs are supervised or piloted remotely, meaning that their behavior is not autonomous throughout the flight. For uncontested missions this is a viable method; however, if confronted by an adversary, UAVs may be required to execute maneuvers faster than a remote pilot could perform them in order to evade being targeted. In this paper we give a description of a nonlinear model predictive controller in which evasive maneuvers in three dimensions are encoded for a fixed wing UAV for the purposes of this pursuit/evasion game.