A low-turbulence, aerosol sampling inlet (LTI) has been developed for use on aircraft. The inlet makes use of boundary layer suction in a porous diffuser to slow the sample flow from aircraft air speeds near 150 m/s to velocities near 5 m/s without generating turbulence. The reduction of turbulence reduces losses of supermicron particles by turbulen. t deposition and permits the use of laminar flow calculations and well-understood drag formulations to accurately predict particle motion. Large particles are enhanced in the sample flow due to inertia. These enhancements are predicted with numerical analysis of fluid flow and integration of the equations of motion for the particles. The diffuser discussed in this article has been used in a number of field experiments, and the enhancement factors have been provided to the experimenters measuring aerosol downstream of the inlet. Some particles are doubtless lost in transport from the LTI to the aircraft fuselage. Estimates of those losses have also been made and provided to experimenters. The enhancement factors (EF) and losses are a function of particle Stokes
Instrumented unmanned air vehicles (UAVs) represent a new way of conducting atmospheric science, particularly within the atmospheric boundary layer where the air is turbulent. However, using autonomous UAVs for airborne measurement requires active control methods capable of following altitude commands despite unknown and turbulent disturbances to the air. Filtered dynamic inversion (FDI) is a control method with desirable command-following and disturbance-rejection properties for this application. FDI requires limited model information and is thus robust to parametric uncertainty, which arises in modeling UAV dynamics. In this paper, FDI is implemented in an altitude-flight-control system for an autonomous fixed-wing UAV. The control system is validated in simulation with a nonlinear dynamic model of a small fixed-wing UAV. The control system is also implemented and validated in flight experiments with turbulent wind conditions. Experimental results show that FDI yields improved altitude and pitch command following as compared to a classical (e.g., proportional-integral) flight-control system. In particular, experimental data demonstrate that the average power of the altitude and pitch command-following errors with FDI is smaller than those with proportionalintegral control.
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