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

被引：0
作者：
Hu, Shengbin [1 ,2 ]
Lu, Wenhua [2 ]
Lu, Minxun [1 ]
机构：
[1] Tongji Univ, Coll Mech Engn, Shanghai 200092, Peoples R China
[2] Shanghai Univ Engn Sci, Sch Air Transportat, Shanghai, Peoples R China
来源：
MANUFACTURING SCIENCE AND MATERIALS ENGINEERING, PTS 1 AND 2 | 2012年 / 443-444卷
关键词：
Flapping Wing Micro Aerial Vehicle; sliding mode control; radial basis function neural network; adaptive fuzzy gain control;
D O I：
10.4028/www.scientific.net/AMR.443-444.177
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
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.
引用
收藏
页码：177 / +
页数：2
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