Real-time Neural Network Based Identification of a Rotary-wing UAV Dynamics for Autonomous Flight

被引：0
|
作者：
Samal, Mahendra Kumar [1 ]
Anavatti, Sreenatha [1 ]
Garratt, Matthew [1 ]
机构：
[1] UNSW ADFA, Sch Aerosp Civil & Mech Engn, Canberra, ACT 2600, Australia
来源：
2009 IEEE INTERNATIONAL CONFERENCE ON INDUSTRIAL TECHNOLOGY, VOLS 1-3 | 2009年
关键词：
D O I：
暂无
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
Real time flight implementation of a Neural Network based black-box Identification (NNID) scheme to a Rotary Wing Unmanned Aerial Vehicle (RUAV) is presented in this paper. The applicability of NNID scheme for real time identification of longitudinal and lateral dynamics of the RUAV is evaluated in flight. To show the efficacy of the method for real time applications, the identification results and error statistics are provided. The challenges involved in terms of hardware implementation, computational time requirements, and real time coding are investigated and reported. Results indicate that NNID is suitable for modeling the dynamics of the RUAV in real time.
引用
收藏
页码：1019 / 1024
页数：6
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