System identification for an autonomous quadrotor using extended and unscented kalman filters
This paper presents aerodynamic parameters estimation techniques for an autonomous quadrotor through the implementation of Extended Kalman Filter (EKF) and Unscented Kalman Filter (UKF). EKF and UKF have known to be typical estimation techniques used to estimate the state vectors and parameters of...
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| Main Authors: | , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2011
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/14162/1/iccas2011.pdf http://irep.iium.edu.my/14162/ |
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| Summary: | This paper presents aerodynamic parameters estimation techniques for an autonomous quadrotor through the
implementation of Extended Kalman Filter (EKF) and Unscented Kalman Filter (UKF). EKF and UKF have known to
be typical estimation techniques used to estimate the state vectors and parameters of nonlinear dynamical systems. In
this paper, three main processes are highlighted; dynamic modeling of the quadrotor, the implementation of EKF and
the implementation of UKF algorithms. The aim is to identify and estimate the needed parameters for an autonomous quadrotor. The obtained results demonstrate the performances of EKF and UKF based on the flight test applied to the quadrotor system. |
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