Paper Title:
Flapping Wing Micro Aerial Vehicle Attitude Control with Fuzzy Sliding Mode Controller Based on RBF Neural Network
  Abstract

A adaptive fuzzy Sliding Mode Control (SMC) scheme based on Radial Basis Function Neural Network (RBFNN) for attitude tracking control of Flapping Wing Micro Aerial Vehicle (FWMAV) is proposed in this paper. A RBFNN is used to compute the equivalent control of sliding mode control, An adaptive algorithm is used for weight adaptation of the RBFNN and A Lyapunov function is selected for the design of the SMC. The simulation results of FWMAV demonstrate that the control scheme is effective.

  Info
Periodical
Advanced Materials Research (Volumes 443-444)
Chapter
Chapter 1: Advances in Manufacturing Engineering Techniques and Materials Science
Edited by
Li Jian
Pages
177-182
DOI
10.4028/www.scientific.net/AMR.443-444.177
Citation
S. B. Hu, W. H. Lu, M. X. Lu, "Flapping Wing Micro Aerial Vehicle Attitude Control with Fuzzy Sliding Mode Controller Based on RBF Neural Network", Advanced Materials Research, Vols. 443-444, pp. 177-182, 2012
Online since
January 2012
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Price
$32.00
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