Title :
Small low-cost unmanned aerial vehicle system identification: A survey and categorization
Author :
Hoffer, Nathan V. ; Coopmans, Calvin ; Jensen, Austin M. ; Yangquan Chen
Author_Institution :
Center for Self-Organizing & Intell. Syst. (CSOIS), Utah State Univ., Logan, UT, USA
Abstract :
Small low-cost unmanned aerial vehicles (UAVs) provide greater possibilities for personal scientific research than other conventional platforms such as satellites or manned aircraft. In order to provide precision aerial imagery or other scientific data, an accurate model of vehicle dynamics is needed for controller development and tuning. The purpose of this paper is to provide a survey of current methods and applications of system identification (system ID) for small low-cost UAVs. This survey divides UAVs into 5 groups: helicopter, fixed-wing, multirotor, flapping-wing, and lighter-than-air. The current state of system ID research with respect to various types of UAVs is reviewed based on research literature. System ID methods and application are tabulated for further research. Concluding remarks are given and applications for system ID methods to small low-cost UAVs are recommended.
Keywords :
autonomous aerial vehicles; helicopters; identification; mobile robots; robot dynamics; telerobotics; vehicle dynamics; dynamic system mathematical modeling; fixed-wing UAV; flapping-wing UAV; helicopter; lighter-than-air UAV; multirotor UAV; small low-cost UAV system identification; system ID research; system identification; unmanned aerial vehicle; vehicle dynamics; Aerodynamics; Data models; Global Positioning System; Helicopters; Mathematical model; Predictive models; Vehicle dynamics; ARMAX; Autoregressive exogenous inputs; Box Jenkins; CIFER; EKF; Fixed-wing; Flapping-wing; Frequency domain; Fuzzy identification; Helicopter; Kalman filter; Least squares; Levenberg Marquardt; Lighter-than-air; Multirotor; Neural network; Observer/Kalman identification; Output-error method; Prediction-error method; State-space; Subspace; System Identification; Time domain; UAV; UKF;
Conference_Titel :
Unmanned Aircraft Systems (ICUAS), 2013 International Conference on
Conference_Location :
Atlanta, GA
Print_ISBN :
978-1-4799-0815-8
DOI :
10.1109/ICUAS.2013.6564775