DocumentCode :
675533
Title :
UAV dynamics model parameters estimation techniques: A comparison study
Author :
Al-Shabi, Mohammad A. ; Hatamleh, Khaled S. ; Asad, Asad A.
Author_Institution :
Dept. of Mechatron. Eng., Philadelphia Univ., Jerash, Jordan
fYear :
2013
fDate :
3-5 Dec. 2013
Firstpage :
1
Lastpage :
6
Abstract :
Unmanned Aerial Vehicles (UAVs) dynamics modeling and parameter estimation has recently occupied great interest due to their vast use in military, civilian, industrial and agricultural applications. Accurate Online UAV parameter estimation is essential for robust autonomous control design. This study presents two different online UAV parameter estimation methods; the smooth variable structure filter (SVSF) method and the recursive least squares (RLS) method. This work presents the application of the SVSF method; including chattering signal´s information which previously was applied to linear models, over a nonlinear dynamics model. Moreover, the work presents a simulation study to assess the performance of the methods in terms of accuracy and speed of convergence when applied to estimate the parameters of a general Quadrotor dynamics model. The better method might be considered for deployment in an experimental UAV parameter estimation project under run by the authors.
Keywords :
autonomous aerial vehicles; control system synthesis; least squares approximations; mobile robots; parameter estimation; robot dynamics; robust control; smoothing methods; telerobotics; RLS method; SVSF method; UAV dynamics model parameter estimation techniques; chattering signal information; experimental UAV parameter estimation project; general quadrotor dynamics model; linear models; nonlinear dynamics model; online UAV parameter estimation methods; recursive least squares method; robust autonomous control design; smooth variable structure filter method; unmanned aerial vehicle dynamics modeling; unmanned aerial vehicle dynamics parameter estimation; Dynamics; Equations; Least squares approximations; Mathematical model; Noise; Parameter estimation; Vehicle dynamics; UAV; dynamics modeling; parameter estimation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Applied Electrical Engineering and Computing Technologies (AEECT), 2013 IEEE Jordan Conference on
Conference_Location :
Amman
Print_ISBN :
978-1-4799-2305-2
Type :
conf
DOI :
10.1109/AEECT.2013.6716436
Filename :
6716436
Link To Document :
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