Title :
A study of fault detection and system reconfiguration for UAV navigation system bon RBF neural network
Author :
Dongli, Yuan ; Jianguo, Yan ; Qingbiao, Xi
Author_Institution :
Coll. of Autom., Northwestern Polytech. Univ., Xi´´an
Abstract :
In the field of aeronautics and astronautics, the guidance and navigation system play so important role that it will bring huge loss once that system do wrong. Accordingly, besides detecting carefully and completely on the ground, after in the air, it is quite necessary to detect real time and take corresponding measure when the fault is found. Due to the nonlinearity and complexity of UAV integrated navigation system, this paper puts forward a method of fault detection, fault isolation and system reconfiguration based on RBF neural network. This kind of method can realize on line fault detection, fault isolation and system reconfiguration; so that, it can ensure the navigation precision of UAV integrated navigation system satisfy with performance request.
Keywords :
aerospace computing; aircraft navigation; fault diagnosis; radial basis function networks; remotely operated vehicles; RBF neural network; UAV integrated navigation system; fault detection; fault isolation; system reconfiguration; Automation; Convergence; Educational institutions; Extraterrestrial measurements; Fault detection; Intelligent control; Navigation; Neural networks; Sensor phenomena and characterization; Unmanned aerial vehicles; FDI (fault detection and isolation); RBF neural network; UAV (Unmanned Aerial Vehicle); integrated navigation; system reconfiguration;
Conference_Titel :
Intelligent Control and Automation, 2008. WCICA 2008. 7th World Congress on
Conference_Location :
Chongqing
Print_ISBN :
978-1-4244-2113-8
Electronic_ISBN :
978-1-4244-2114-5
DOI :
10.1109/WCICA.2008.4594424
