This effort seeks to develop a methodology to identify airwake gust disturbances through flight testing, where identified gust data can be used to validate coupled ship airwake and rotor wake disturbance models used in Virtual Dynamic Interface (VDI) simulations. The gust identification algorithm uses an identified linear model of the aircraft to separate effects of airwake disturbances from responses due to control inputs and to estimate gust velocities. The algorithm only requires standard sensors that are likely to be available on production rotorcraft, i.e. an INS/GPS and measurement of control servo motion. The methodology is initially demonstrated in simulations of a utility helicopter flying in a simulated ship airwake using CFD flow solutions. The flow velocities estimated by the gust identification algorithm are compared to the known flow field properties of the CFD solution, and show reasonable agreement. A sensitivity study is conducted in simulations to quantify the effects of noise and model uncertainty on the accuracy of the gust identification algorithm. Finally, indoor flight tests of a small instrumented RC scale rotorcraft are performed to test the algorithms. This involves system identification tests of the RC aircraft, and flights in simulated gusts while taking simultaneous flow measurements. Initial test results show promise but are inconclusive. Past research has shown this general approach to produce excellent agreement with simulated flight data given an adequately accurate model of the vehicle. The deleterious effects of modeling uncertainty are reported herein which are likely a factor for the non-conclusive flight test results. Limitations on current aircraft instrumentation are a probable cause leading of modeling uncertainty which affects the identified gusts. A motion capture system has been implemented, which might resolve these issues.
|Original language||English (US)|
|Number of pages||15|
|Journal||Annual Forum Proceedings - AHS International|
|Publication status||Published - Jan 1 2015|
All Science Journal Classification (ASJC) codes