Flight Dynamics Modeling of a Lift-plus-Cruise Unmanned Aerial Vehicle with Experimental Validation

The paper discusses the design and high-fidelity flight dynamics modeling of a 13-lb lift-plus-cruise unmanned aerial vehicle (UAV) using Rotorcraft Comprehensive Analysis System (RCAS) in order to (1) better understand its physics of flight during a wide range of maneuvers, and (2) provide insight into the fidelity needed to achieve quantitative accuracy when compared to flight test data. Wind tunnel tests of the full aircraft were performed at a 65% scale to provide lookup tables for the flight dynamics model. Flight test data was collected while providing high control inputs to excite a variety of dynamic states in hovering and cruising modes to systematically validate the physics model. Near quantitative agreement was observed between the model predictions and test data during hover; however, the predictions began to disagree at higher forward cruising speeds. To address the discrepancy between the prediction and experiment, the flight dynamics model was improved by learning a correction from flight test data using a neural network. This hybrid physics plus data-driven approach reduced the error between the physics model and experiment by 74% and only needing 12 minutes of flight data for training. This hybrid methodology presents an alternate approach to high fidelity modeling which only needs a relatively small amount of flight test data.