Paper Info
Title
Prescribed finite-time adaptive neural trajectory tracking control of quadrotor via output feedback
Abstract
This paper proposes a novel prescribed finite-time output feedback control scheme for quadrotor trajectory tracking control. The proposed control scheme considers the quadrotor modeling containing uncertain nonlinearities and strong coupling. The neural observer is set up to estimate the unknown state variables. The main difficulty caused by the time-vary coefficient matrix to design a state observer is overcame by the convex combination technique. To get a prescribed finite-time tracking performance, Barrier Lyapunov Function (BLF) approach is presented for control design. The constructed controllers guarantee that the tracking errors meet the prescribed accuracy in a pre-specified finite settling time. Finally, a simulation example verifies the effectiveness of the control scheme.
Year
DOI
Venue
2021
10.1016/j.neucom.2021.06.018
Neurocomputing
Keywords
DocType
Volume
Quadrotor control,Neural network,Output feedback,Backstepping
Journal
458
ISSN
Citations 
PageRank 
0925-2312
0
0.34
References 
Authors
0
3
Name
Order
Citations
PageRank
Mingyu Wang113524.90
Bing Chen2158369.28
Chong Lin33323149.22