Title :
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
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;
Conference_Titel :
Mechatronics and Control (ICMC), 2014 International Conference on
Print_ISBN :
978-1-4799-2537-7
DOI :
10.1109/ICMC.2014.7231696
