Abstract

With the growing use of Unmanned Aerial Vehicle (UAV) in civilian airspace, design and development of this type of aircraft requires a thorough study of its dynamics in order to demonstrate airworthiness of such a system. This paper describes the first step in the development of an unmanned version of the SA160 aircraft by presenting a fully-coupled 6 DoF model of the SA160 aircraft. As the aerodynamic parameters are evaluated with inflight data using the SIDPAC (System Identification Program for AirCraft) software, the problem addressed in this paper is the validation of a predictive model for the dynamic response of the SA160 based on identified parameters. In this work, a state-space representation is used for the dynamic modeling of the SA160 single-engine aircraft. The a priori unknown aerodynamic coefficients are first estimated using a Digital Datcom (U.S. Air Force Digital Data Compendium) model. These coefficients are used as initial estimates for the output-error method. The effect of the rotating propeller on the aircraft dynamics is included in order to account for aerodynamic and inertial coupling. The dynamic model is based on the small-disturbance theory, so that aircraft motion is simulated around equilibrium flight conditions. Furthermore, the dynamic model elaborated in this paper is based on dimensionless linearized equations. The main goal is to demonstrate that the statespace model parameters identified through flight test program provide reliable and accurate dynamic model. System identification techniques are then used with in-flight data from an instrumented aircraft. Instrumentation includes an air data boom and an inertial measurement unit fitted to the SA160 in order to get a full set of in-flight aerodynamic and 6 DoF dynamic data. The flight control surfaces deflection is also measured with linear position measurements sensors. The inputs applied to flight control surfaces (elevator, ailerons and rudder) are designed such as to excite the aircraft in order to provide sufficiently rich data quality for modeling. Results from the model with identified SA160 aerodynamic parameters are compared to flight test data. Different sets of longitudinal, lateral/directional and fully-coupled maneuvers are performed for specific flight conditions. In the system identification process, aerodynamic parameters identified from longitudinal and lateral/directional dynamics are used as inputs for the output-error method applied for the fully-coupled case, and the amount of aerodynamic coupling is addressed.

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