On-line Inertia Measurement of Unmanned Aerial Vehicles using on board Sensors and Bifilar Pendulum

Matija Krznar (), Denis Kotarski, Petar Piljek and Danijel Pavkoviæ
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Matija Krznar: Sv. Kriz Zacretje, Croatia
Denis Kotarski: Karlovac University of Applied Sciences, Karlovac, Croatia
Petar Piljek: University of Zagreb, Faculty of Mechanical Engineering and Naval Architecture, Zagreb, Croatia
Danijel Pavkoviæ: University of Zagreb, Faculty of Mechanical Engineering and Naval Architecture, Zagreb, Croatia

Interdisciplinary Description of Complex Systems - scientific journal, 2018, vol. 16, issue 1, 149-161

Abstract: Identification of a dynamical model and its parameters is one of the fundamental problems in the field of robotics and system dynamics modelling. For the general situation of an object motion with six degrees of freedom (6-DOF), such as in the case of the Unmanned Aerial Vehicle (UAV), the key physical parameters are vehicle mass and moment of inertia. Even though UAV mass and its geometry/topology are easily obtainable, it is difficult to identify the inertia tensor considering that it is not measurable by static tests. This article presents a simple and effective method for on-line estimation of a rigid-body inertia based on a two-wire pendulum and an on-board integrated sensor system. Herein, the test subject (i.e. UAV) is suspended by two thin parallel wires in such a way to form a bifilar torsional pendulum about the vertical axis. Using on-board sensors from the UAV flight controller (FC) unit, the pendulum oscillations are recorded and processed in order to obtain trend-free and noise-free signals used in the final inertia estimation phase. The proposed identification algorithm is verified experimentally for two typical cases of suspended objects related to the UAV control box and a full UAV configuration.

Keywords: UAV; on-line moment of inertia identification; bifilar pendulum; IMU sensors (search for similar items in EconPapers)
JEL-codes: Z00 (search for similar items in EconPapers)
Date: 2018
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