NDLI: Identification of the nonlinear dynamic model of sailplanes involving state estimation and image processing for actuator signal computation

Content Provider	IEEE Xplore Digital Library
Author	Lukacs, L. Lantos, B.
Copyright Year	2014
Description	Author affiliation: Dept. of Control Eng. & Inf. Technol., Budapest Univ. of Technol. & Econ., Budapest, Hungary (Lukacs, L.; Lantos, B.)
Abstract	The primary scope of the paper lies on the identification of an aircraft's nonlinear dynamic model. It is assumed that the aircraft has no inbuilt navigational system, nor any sensors mounted on its control surfaces. The flight of the airplane is influenced by the control column and pedals manipulated by the pilot whose positions can only visually be observed. This situation can often occur in the first phase of control system development of airplanes. Hence, for the time of data logging, an external sensory system (GPS, IMU) and a camera system were deployed on the airplane supporting the collection of flight data for state estimation and model identification. An earlier paper discussed the computation of the actuator signals thus the paper deals mainly with the state estimation and model identification. State estimation is based on two-level Extended Kalman Filters with additional correction in an external loop. System identification is based on the dynamical equations of rigid body with additional weighted nonlinear terms for 3D forces and torques. Wind effects are taken into consideration. From the inertial parameters only the mass is known. Dominating nonlinear functions in the force and torque model are selected by using hypotheses tests. The results are presented for a real sailplane using flight data.
Starting Page	227
Ending Page	232
File Size	673661
Page Count	6
File Format	PDF
ISBN	9781479959969
DOI	10.1109/SISY.2014.6923591
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-09-11
Publisher Place	Serbia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	data fusion image processing Atmospheric modeling Computational modeling Aircraft navigation Equations nonlinear modeling state estimation system iden-tification sailplane dynamic modeltjsg Mathematical model Aircraft State estimation control signal computation
Content Type	Text
Resource Type	Article

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