Aerodynamic parameter estimation of an Unmanned Aerial Vehicle based on extended kalman filter and its higher order approach

Aerodynamic parameter estimation provides an effective way for aerospace system modelling using measured data from flight test, especially for the purpose of developing elaborate simulation environments and control systems design of Unmanned Aerial Vehicle (UAV) with short design cycles and reduced...

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Bibliographic Details
Published in:2010 2nd International Conference on Advanced Computer Control Vol. 5; pp. 526 - 531
Main Authors: Li Meng, Liu Li, Veres, S M
Format: Conference Proceeding
Language:English
Published: IEEE 01.03.2010
Subjects:
Aerodynamic Parameter Estimation
Aerodynamics
Aerospace control
Aerospace simulation
Aerospace testing
Extended Kalman Filter (EKF)
Filtering
Nonlinear dynamical systems
Parameter estimation
System testing
Unmannd Aerial Vehicle (UAV)
Unmanned aerial vehicles
Vehicle dynamics
ISBN:1424458455, 9781424458455
Online Access:Get full text
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Summary:Aerodynamic parameter estimation provides an effective way for aerospace system modelling using measured data from flight test, especially for the purpose of developing elaborate simulation environments and control systems design of Unmanned Aerial Vehicle (UAV) with short design cycles and reduced cost. However, parameter identification of airplane dynamics is complicated because of its nonlinear identification models and the combination of noisy and biased sensor measurements. The combined difficulties mentioned above make the problem of state and parameter estimation a nonlinear filtering problem. Extended Kalman Filter (EKF) is an excellent tool for this matter with the property of recursive parameter identification and excellent filtering. The standard EKF algorithm is based on a first order approximation of system dynamics. More refined linearization techniques such as iterated EKF can be used to reduce the linearization error in the EKF for highly nonlinear systems, which leads to a theoretically better result. In this paper we concentrate on the application and comparison of EKF and iterated EKF for aerodynamic parameter estimation of a fixed wing UAV. The result shows that the two methods have been able to provide accurate estimations.
ISBN:1424458455
9781424458455
DOI:10.1109/ICACC.2010.5487116