Modeling and System Identification using Extended Kalman Filter for a Quadrotor System

Abas, Norafizah and Ari, Legowo and Ibrahim, Zulkifilie and Anuar , Mohamed Kassim and Rahim, Nor Hidayah (2012) Modeling and System Identification using Extended Kalman Filter for a Quadrotor System. In: 2012 2nd International Conference on Electrical Engineering and Applications , 15-16 Dec 2012, Bali.

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Quadrotor has emerged as a popular testbed for Unmanned Aerial Vehicle (UAV) research due to its simplicity in construction and maintenance, and its vertical take-off, landing and hovering capabilities. It is a flying rotorcraft that has four lift-generating propellers; two of the propellers rotate clockwise and the other two rotate counter-clockwise. This paper presents modeling and system identification for autostabilization of a quadrotor system through the implementation of Extended Kalman Filter (EKF). EKF has known to be typical estimation technique used to estimate the state vectors and parameters of nonlinear dynamical systems. In this paper, two main processes are highlighted; dynamic modeling of the quadrotor and the implementation of EKF algorithms. The aim is to obtain a more accurate dynamic model by identify and estimate the needed parameters for the quadrotor. The obtained results demonstrate the performances of EKF based on the flight test applied to the quadrotor system.

Item Type: Conference or Workshop Item (Paper)
Subjects: T Technology > T Technology (General)
Divisions: Faculty of Electrical Engineering > Department of Mechatronics Engineering
Depositing User: Mr Anuar Mohamed Kassim
Date Deposited: 18 Feb 2013 01:49
Last Modified: 28 May 2015 03:44
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