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

Abstract:

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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)

Edited by:

Li Jian

Pages:

177-182

DOI:

10.4028/www.scientific.net/AMR.443-444.177

Citation:

S. B. Hu et al., "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:

$35.00

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