Trajectory tracking control of a flapping wing micro aerial vehicle via neural networks

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

Abstract

This conference paper figures out the tracking control issue of a flapping wing micro aerial vehicle (FWMAV) subject to uncertain system parameters based on the model in Lagrangian form. As we know, there are many uncertainties in the complex nonlinear system. To deal with this problem, radial basis function neural networks (RBFNNs) are considered to substitute uncertainties of FWMAV model. Through Lyapunov stability analysis, all the control performances of the FWMAV system are guaranteed via selecting the appropriate control variables. The boundedness of system states is achieved. Finally, a series of simulations are realized with MATLAB and show good tracking results via our control methods.

Original languageEnglish
Title of host publicationICARM 2016 - 2016 International Conference on Advanced Robotics and Mechatronics
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages443-448
Number of pages6
ISBN (Electronic)9781509033645
DOIs
StatePublished - 21 Oct 2016
Externally publishedYes
Event2016 International Conference on Advanced Robotics and Mechatronics, ICARM 2016 - Macau, China
Duration: 18 Aug 201620 Aug 2016

Publication series

NameICARM 2016 - 2016 International Conference on Advanced Robotics and Mechatronics

Conference

Conference2016 International Conference on Advanced Robotics and Mechatronics, ICARM 2016
Country/TerritoryChina
CityMacau
Period18/08/1620/08/16

Keywords

  • Flapping Wing Micro Aerial Vehicle
  • Radial Basis Function Neural Network
  • Robot
  • State Feedback Control

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