Neural network based feedback linearization control of an unmanned aerial vehicle

被引：13
|
作者：
Necsulescu D. [1 ]
Jiang Y.-W. [2 ]
Kim B. [3 ]
机构：
[1] Department of Mechanical Engineering, University of Ottawa, Ottawa, Ont. K1N 6N5
[2] Solectron Design and Engineering, Kanata, Ont. K2K 2C1
[3] Defence Research and Development Canada, Ottawa, Ottawa, Ont. K1A 0Z4
来源：
International Journal of Automation and Computing | 2007年 / 4卷 / 1期
关键词：
Neural network based feedback linearization; Non-minimum phase; Nonlinear unmanned aerial vehicle (UAV) flight control; Output redefinition;
D O I：
10.1007/s11633-007-0071-y
中图分类号：
学科分类号：
摘要：
This paper presents a flight control design for an unmanned aerial vehicle (UAV) using a nonlinear autoregressive moving average (NARMA-L2) neural network based feedback linearization and output redefinition technique. The UAV investigated is non-minimum phase. The output redefinition technique is used in such a way that the resulting system to be inverted is a minimum phase system. The NARMA-L2 neural network is trained off-line for forward dynamics of the UAV model with redefined output and is then inverted to force the real output to approximately track a command input. Simulation results show that the proposed approaches have good performance. © Institute of Automation, Chinese Academy of Sciences 2007.
引用
收藏
页码：71 / 79
页数：8
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