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DINAME2019
DINAME2019
Parameter Identification for a Flexible Unmanned Aerial Vehicle Using Extended Kalman Filtering
Submission Author:
Alain Souza , SP
Co-Authors:
Alain Souza, David Fernando Castillo Zuñiga, Luiz Carlos Góes
Presenter: Alain Souza
doi://10.26678/ABCM.DINAME2019.DIN2019-0192
Abstract
This paper describes a system identification of a Flexible Unmanned Aircraft Vehicle (FUAV) using a extended Kalman filter. Currently, Technological Institute of Aeronautics (ITA), in partnership with Flight Technologies (FT), are developing an FUAV with a large wingspan, built with composite materials, with the purpose of making the wing structure flexible. Flight data may contain considerable amount of noise; in addition, there may be trends and states not observed in the system model to be estimated, so filtering techniques are generally employed. This 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. Then the goals of this paper is identify the longitudinal aerodynamic and elastic derivatives using a extended Kalman filter
Keywords
aircraft parameter estimation, flexible aircraft dynamics, Extended Kalman Filter, Flexible Unmanned Aircraft Vehicle
