A System Identification Strategy for Nonlinear Model of Small-Scale Unmanned Helicopters

A system identification strategy to identify the parameters of a small-scale unmanned helicopter's nonlinear physics-based model suitable for nonlinear control design applications is described. A time-domain technique, which allows for the identification of a nonlinear model of the helicopter without linearizing the model, is used. A combination of ground and flight-test data is used to parameterize the model. The ground test data are used to identify the physical parameters of the main and tail rotors such as the lift and drag coefficients using an aerodynamic force measurement test bed. The unknown parameters of the rotor dynamics and empennage drag are identified using flight-test data and applying a nonlinear least-squares method. A 10-degree-of-freedom nonlinear physics-based model including rotor and stabilizer bar dynamics is developed and validated using flight-test data. The results indicate that the overall response of the identified nonlinear model of the helicopter matches the real flight data.