Towards Autonomous Stratospheric Flight: A Generic Global System Identification Framework for Fixed-Wing Platforms

Abstract

System identification of High Altitude Long Endurance fixed-wing aerial vehicles is challenging as its operating flight envelope covers wide ranges of altitudes and Mach numbers. We present a new global system identification framework geared towards such fixed-wing aerial platforms where the aim is to build a global aerodynamic model without many repetitions of local system identification procedures or the use of any aerodynamic database. Instead we apply parameter identification techniques to virtually created system identification data and update the identified parameters with available flight test data. The proposed framework was evaluated using data set outside the flight envelope of the available flight test data, i.e. at different airspeeds considering both interpolation and extrapolation scenarios. The error analysis has shown that the obtained longitudinal aerodynamic model can accurately predict the pitch rate and pitch angle, mostly within a tolerance of $\pm \pmb{1.5}$ degrees/s and $\pm \pmb{2}$ degrees respectively. Such a cost and time efficient model development framework enables high fidelity simulation and precise control which ultimately leads to higher success rates in autonomous missions.