Title :
Frame induced vibration estimation and attenuation scheme on a multirotor helicopter
Author :
Fresk, Emil ; Nikolakopoulos, George
Author_Institution :
Dept. of Comput. Sci., Electr. & Space Eng., Lulea Univ. of Technol., Lulea, Sweden
Abstract :
The aim of this article is to establish an induced frame vibration and attenuation scheme, specifically targeting the area of multi-rotor Unmanned Aerial Vehicles (UAVs), such as quadrotors. These types of unmanned small scale helicopters are characterized by small and light frames, which are vulnerable to vibrations induced by the operation of the motors or external environmental factors. The existence of such vibrations effecting the frame can significantly deteriorate the performance of the overall closed system and even drive it to instabilities. In this article spectral estimation schemes based on: a) Autoregressive (AR) modeling and b) Multiple Signal Classification (MUSIC) are being established and evaluated towards their ability to detect the induced vibration frequencies on the UAV, while an extended discussion is being presented on selecting the correct number of the identified induced vibrating frequencies. In a sequential stage, a vibration attenuation approach based on notch filtering is being presented, being able to correctly attenuate the induced vibrating frequencies in the measurements. The efficiency of the overall suggested scheme is being evaluated by experimental results that indicate the significant improvement in the measurements achieved by the direct application of the proposed scheme.
Keywords :
autonomous aerial vehicles; autoregressive processes; helicopters; mobile robots; notch filters; signal classification; telerobotics; vibration control; AR modeling; MUSIC; UAV; autoregressive modeling; frame induced vibration attenuation; frame induced vibration estimation; multiple signal classification; multirotor helicopter; multirotor unmanned aerial vehicles; notch filtering; spectral estimation; unmanned small scale helicopters; vibration frequencies; Correlation; Eigenvalues and eigenfunctions; Frequency estimation; Mathematical model; Multiple signal classification; Noise; Vibrations;
Conference_Titel :
Decision and Control (CDC), 2014 IEEE 53rd Annual Conference on
Conference_Location :
Los Angeles, CA
Print_ISBN :
978-1-4799-7746-8
DOI :
10.1109/CDC.2014.7040281