Abstract

This paper investigates the applicability of a remote-controlled (RC) helicopter as a sensing platform for measuring local wind conditions. A simplified nonlinear multibody helicopter dynamics model has been proposed in this paper, which models local wind conditions in addition to capturing essential helicopter states such as fuselage dynamics, rotor inflow, blade flapping, and lead lagging. The critical aerodynamic parameters for the model were extracted using indoor calibration flights. This paper also presents the performance of particle swarm optimization in optimizing and validating the helicopter's dynamic model parameters. An in-house developed multisensor instrumentation system was used to track the helicopter dynamics and extract wind model parameters through anomalies in the helicopter dynamics estimates. A three-dimensional (3-D) map of local wind conditions was generated for a controlled turbulent wind environment created in an indoor test facility. To validate the system's performance, wind parameters estimated from the proposed system were quantitatively compared against the experimentally generated 3-D wind map.

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