• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.45 no.9
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• pp.711-723
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• 2017

This paper proposes a flight control system for an organic flight array(OFA) which has a new configuration to consist of multi modularized ducted-fan unmanned aerial vehicles (UAVs). The OFA is able to apply to various missions such as indoor reconnaissance, communication relay, and radar jamming by using capability of hover flight. The OFA has a distinguished advantage due to reconfigurable structure to assemble or separate with respect to its missions or operational conditions. A dynamic modelling of the OFA is derived based on equations of motion of the single ducted-fan modules. In order to apply nonlinear control method, an affine system of attitude dynamics is derived. Moreover, the control system is composed of a back-stepping controller for attitude control and a PID controller for position control. Then the performance of the proposed controller is verified via a numerical simulation under wind disturbance.

• Journal of Aerospace System Engineering
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• v.11 no.1
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• pp.14-21
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• 2017

A Linear parameterized Sigma-Pi neural network (SPNN) is applied to a tilt-duct unmanned aerial vehicle (UAV) which has a very large longitudinal stability ($C_{L{\alpha}}$). It is uncontrollable by a proportional, integral, derivative (PID) controller due to heavy stability. It is shown that the combined inner loop and outer loop of SPNN controllers could overcome the sluggish longitudinal dynamics using a method of dynamic inversion and pseudo-control to compensate for reference model error. The simulation results of the way point guidance are presented to evaluate the performance of SPNN in comparison to a PID controller.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.6
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• pp.555-562
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• 2021

Recently, in the field of geospatial information construction, unmanned aerial vehicles have been increasingly used because they enable rapid data acquisition and utilization. In this study, photogrammetry was performed using fixed-wing, rotary-wing, and VTOL (Vertical Take-Off and Landing) unmanned aerial vehicles, and geospatial information was constructed using two types of unmanned aerial vehicle LiDAR (Light Detection And Ranging) sensors. In addition, the accuracy was evaluated to present the utility of spatial information constructed through unmanned aerial photogrammetry and LiDAR. As a result of the accuracy evaluation, the orthographic image constructed through unmanned aerial photogrammetry showed accuracy within 2 cm. Considering that the GSD (Ground Sample Distance) of the constructed orthographic image is about 2 cm, the accuracy of the unmanned aerial photogrammetry results is judged to be within the GSD. The spatial information constructed through the unmanned aerial vehicle LiDAR showed accuracy within 6 cm in the height direction, and data on the ground was obtained in the vegetation area. DEM (Digital Elevation Model) using LiDAR data will be able to be used in various ways, such as construction work, urban planning, disaster prevention, and topographic analysis.