Adaptive Autopilot System for Small Fixed Wing UAVs

Small low cost UAV autopilot systems (research and fielded platforms) in use today are severely restricted in their operational capability and quite costly with respect to their operational capability. The size of the UAV introduces unique problems in the development of Guidance, Navigation, and Control (GNC) algorithms since aerodynamic models of the vehicle are difficult to define and are specific to each airframe. These low Reynolds number vehicles are subjected to varying environmental flight conditions during flight that must be addressed. Constructing a small footprint flight computing system is difficult due to the limited availability of low cost small footprint computing systems with the computational power, memory, and interfaces to support a variety of applications and research. This paper presents a low cost adaptive GNC system and an adaptive control law. The system is named Reconfigurable Autopilot for Vehicles with Enhanced Navigation (RAVEN), which addresses these issues.