Innovative Methods for Modeling and Simulation of Tiltrotor Aircraft

Aircraft research, development, and testing programs require high-fidelity simulations and aerodynamic models. However, once flight testing begins the process of updating the simulation to match flight-test results is often ad hoc, labor intensive, and costly. Recent research is investigating data-driven methods for automated and semi-automated updating simulation databases and Phase I efforts built upon this research to address the unique challenges associated with updating tiltrotor simulations. In Phase I the authors demonstrated how one can learn a suitably complex tiltrotor model based on the underlying simulation aerodynamics and then search for additional structure (if required) using flight, or other external, data. Additional structure is only suggested if certain information-theoretic criteria are satisfied. Estimation theory is used to calculate optimal parameter estimates of the defined model structure. In Phase II, the authors will extend the tiltrotor approaches to rotorcraft in general, demonstrate the approach for an expanded set of operating conditions, build a suite of simulation-updating tools, and use these tools to develop and update a high-fidelity tiltrotor simulation using measured flight-test data. The suite of simulation-updating tools includes all steps in the update process from data preprocessing to blending the update with the existing database.