UAV Thrust Model Identification Using Spectrogram Analysis

Abstract

This paper deals with a non-contact method to identify the aerodynamic propeller constants of the Parrot AR.Drone quadrotor. The experimental setup consists of a microphone installed in the flight arena to record audio data. In terms of methodology, a spectrogram analysis is adopted to estimate the propeller velocity based on the filtered sound signal. It is known that, in a hovering maneuver, when the UAV mass increases, the propellers rotate faster to produce the necessary thrust increment. In this work, the rotorcraft takes off with its factory settings, first with no hull, corresponding to a mass of 413 g, and after with a small hull, corresponding to a mass of 444 g, and a bigger hull, corresponding to a mass of 462 g. In the sequence, the velocity of the propellers are estimated for each of these three cases using spectrograms of audio recorded by a microphone, corresponding to the sound generated by the four rotors. Finally, the estimated velocity is used to identify the aerodynamic parameters, thus validating the proposal.

Nonlinear Extended State Observer Based Prescribed Performance Control for Quadrotor UAV with Attitude and Input Saturation Constraints

“…The rotor dynamic can be approximated by a first-order low-pass filter. However, for non-aggressive maneuvers, the fast rotor dynamics can be regarded as a conventional assumption, and the rotor dynamic effects can also be diminished by the high bandwidth of the controller [19,47]. Therefore, the rotor dynamics are ignored and the four virtual control variables τ f , τ p , τ r , τ q are obtained from thrust force as…”