Robust adaptive backstepping control of UAV with lumped uncertainties

Author

Cao Lijia ; Hu Xiaoxiang ; Guo Yang

Author_Institution

Xi´an Res. Inst. of Hi-Tech, Xi´an, China

fYear

2014

Firstpage

961

Lastpage

965

Abstract

The design of a robust adaptive backstepping flight control law for a unmanned aerial vehicle (UAV) is discussed. The lumped uncertainties of the nonlinear UAV model are concerned in this paper. RBF neural networks are used inside the backstepping control law to approximate the lumped uncertainties. Command filters are used to implement the virtual control law and avoid “explosion of complexity”. The controller and its performance are evaluated on a nonlinear, six-degrees-of-freedom dynamic model of the UAV in the simulations.

Keywords

adaptive control; autonomous aerial vehicles; control nonlinearities; control system synthesis; mobile robots; neurocontrollers; nonlinear control systems; radial basis function networks; robust control; uncertain systems; RBF neural network; command filter; explosion of complexity; lumped uncertainty approximation; nonlinear UAV model; nonlinear six-degrees-of-freedom dynamic model; performance evaluation; robust adaptive backstepping flight control law design; unmanned aerial vehicle; virtual control law; Adaptation models; Aerodynamics; Aerospace control; Backstepping; Robustness; Uncertainty; Vehicle dynamics; UAV; backstepping; lumpied uncertaines; robust adaptive control;

fLanguage

English

Publisher

ieee

Conference_Titel

Mechatronics and Control (ICMC), 2014 International Conference on

Print_ISBN

978-1-4799-2537-7

Type

conf

DOI

10.1109/ICMC.2014.7231696

Filename

7231696