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  • 标题:Disturbance observer-based discrete-time neural control for unmanned aerial vehicles with uncertainties and disturbances
  • 本地全文:下载
  • 作者:Shuyi Shao ; Mou Chen ; Rong Mei
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2017
  • 卷号:50
  • 期号:1
  • 页码:15289-15294
  • DOI:10.1016/j.ifacol.2017.08.2439
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractIn this paper, a disturbance observer-based discrete-time neural control problem is studied for unmanned aerial vehicle (UAV) in the presence of external disturbances and system uncertainties. To estimate the external disturbance, a nonlinear discrete-time disturbance observer (DTDO) is designed. Furthermore, the system uncertainties are approximated by employing neural network (NN). Then, a discrete-time neural tracking control scheme is proposed based on the designed DTDO, the discrete-time tracking differentiator and the backstepping technique. Under the discrete-time Lyapunov analysis, the boundness of all the closed-loop system signals are proven. Finally, numerical simulation results are shown to demonstrate the effectiveness of the proposed control scheme.
  • 关键词:KeywordsUAVdisturbance observerneural networkbacksteppingtracking control
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