Towards reduced-order models for online motion planning and control of UAVs in the presence of wind
Ashray A. Doshi, Surya P. N. Singh, Adam J. Postula · 2012
This paper describes a model reduction strat-egy for obtaining a computationally efficient prediction of a fixed-wing UAV performing waypoint navigation under steady wind condi-tions. The strategy relies on the off-line gener-ation of time parametrized trajectory libraries for a set of flight conditions and reduced or-der basis functions functions for determining intermediate locations. It is assumed that the UAV has independent bounded control over the airspeed and altitude, and consider a 2D slice of the operating environment. We found that the reduced-order model finds intermediate po-sitions within 10 % and at speeds of 10x faster than clock-time (even in wind conditions in ex-cess of 50 % of the UAV’s forward airspeed) when compared against simulation results us-ing a medium-fidelity flight dynamics model. The potential of this strategy for online plan-ning operations is highlighted. 1