NDLI: Minimal Models to Capture the Dynamics of a Rotary Unmanned Aerial Vehicle

Content Provider	Springer Nature Link
Author	Choi, Rejina Ling Wei Hann, Christopher E. Chen, XiaoQi
Copyright Year	2013
Abstract	This paper presents a method for characterising the primary dynamics of a rotary unmanned aerial vehicle. Based on first principles and basic aerodynamics, a mathematical model which explains the rigid body dynamics of a model-scale helicopter is developed. This model is reduced to three simplified decoupled models of attitude dynamics. Empirical test data is collected from a field experiment with significant wind disturbances. The method worked accurately on both uncoupled and fully coupled attitude models. An integral based parameter identification method is presented to identify the unknown intrinsic helicopter parameters as well as model of wind disturbance. An extended Kalman filter system identification method and common nonlinear regression are used for comparison. The EKF was found to be highly dependent on the initial states, so is not suitable for this application which contains significant disturbance and modelling errors. Nonlinear regression proved to be sufficiently accurate but computationally expensive. The proposed integral based parameter identification method was shown to be fast and accurate and is well suited to this application.
Starting Page	569
Ending Page	593
Page Count	25
File Format	PDF
ISSN	09210296
Journal	Journal of Intelligent & Robotic Systems
Volume Number	75
Issue Number	3-4
e-ISSN	15730409
Language	English
Publisher	Springer Netherlands
Publisher Date	2013-10-31
Publisher Place	Dordrecht
Access Restriction	Subscribed
Subject Keyword	Unmanned aerial vehicle Minimal modelling Integral-based parameter identification Extended Kalman Filter Disturbance Control, Robotics, Mechatronics Electrical Engineering Artificial Intelligence (incl. Robotics) Mechanical Engineering
Content Type	Text
Resource Type	Article
Subject	Industrial and Manufacturing Engineering Artificial Intelligence Control and Systems Engineering Mechanical Engineering Electrical and Electronic Engineering Software

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