• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.41 no.6
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• pp.465-472
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• 2013

In this paper, we suggest how to determine the parachute deploy position for accurate landing of a UAV at a desired position. The 9-DOF dynamic modeling of UAV-parachute system is required to construct the proposed algorithm based on neural network nonlinear function approximation technique. The input and output data sets to train the neural network are obtained from simulation results using UAV-parachute 9-DOF model. The input data consist of the deploy position, UAV's velocity, and wind velocity. The output data consist of the cross range and down range of landing positions. So we predict the relative landing position from the current UAV position. The deploy position is then determined through distance compensations for the relative landing positions from the desired landing position. The deploy position is consistently calculated and updated.

• Journal of Aerospace System Engineering
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• v.16 no.4
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• pp.77-87
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• 2022

The Precision Aerial Delivery System is an instrument designed to improve the poor landing accuracy of aerial delivery system with conventional circular parachutes, and is equipped with an Airborne Guidance Unit to safely transport supplies to the desired destination. Currently, the landing accuracy of the PADS product is reported as CEP₅₀ 100m and also differs significantly, depending on the actual topography and weather environment. In this study, HILS was constructed based on the 6DOF nonlinear modeling of PADS to analyze the maneuver characteristics of Ram Air Parachute under wind environments. By using the new algorithm a precision soft landing algorithm including Energy Management and Final Approach is designed. HILS results show that it is possible to achieve a precise soft landing within CEP₅₀ 40m, and it can be exploited to develop an actual PADS drop test.