A CFD based procedure for airspace integration of small unmanned aircraft within congested areas

Future integration of small unmanned aircraft within an urban airspace requires an a posteriori understanding of the building-induced aerodynamics which could negatively impact on vehicle performance. Moving away from generalised building formations, we model the centre of the city of Glasgow using Star-CCMþ, a commercial CFD package. After establishing a critical turbulent kinetic energy for our vehicle, we analyse the CFD results to determine how best to operate a small unmanned aircraft within this environment. As discovered in a previous study, the spatial distribution of turbulence increases with altitude. It was recommended then that UAVs operate at the minimal allowable altitude within a congested area. As the flow characteristics in an environment are similar, regardless of inlet velocity, we can determine areas within a city which will have consistently low or high values of turbulent kinetic energy. As the distribution of turbulence is dependent on prevailing wind directions, some directions are more favourable than others, even if the wind speed is unchanging. Moving forward we should aim to gather more information about integrated aircraft and how they respond to turbulence in a congested area

EKF-based parameter identification of multi-rotor unmanned aerial vehiclesmodels

This work presents a method for estimating the model parameters of multi-rotor unmanned aerial vehicles by means of an extended Kalman filter. Different from test-bed based identification methods, the proposed approach estimates all the model parameters of a multi-rotor aerial vehicle, using a single online estimation process that integrates measurements that can be obtained directly from onboard sensors commonly available in this kind of UAV. In order to develop the proposed method, the observability property of the system is investigated by means of a nonlinear observability analysis. First, the dynamic models of three classes of multi-rotor aerial vehicles are presented. Then, in order to carry out the observability analysis, the state vector is augmented by considering the parameters to be identified as state variables with zero dynamics. From the analysis, the sets of measurements from which the model parameters can be estimated are derived. Furthermore, the necessary conditions that must be satisfied in order to obtain the observability results are given. An extensive set of computer simulations is carried out in order to validate the proposed method. According to the simulation results, it is feasible to estimate all the model parameters of a multi-rotor aerial vehicle in a single estimation process by means of an extended Kalman filter that is updated with measurements obtained directly from the onboard sensors. Furthermore, in order to better validate the proposed method, the model parameters of a custom-built quadrotor were estimated from actual flight log data. The experimental results show that the proposed method is suitable to be practically appliedPeer ReviewedPostprint (published version