Title :
A small unmanned aerial vehicle for oil-gas field surveillance
Author :
Wang, Tian-miao ; Lei, Xu-sheng ; Linag, Jian-hong ; Pei, Bao-qing
Author_Institution :
Robot Center, Beijing Univ. of Aeronaut. & Astronaut., Beijing
Abstract :
In the last years, there is an increasing demand for cheap and easy to operate platforms for surveillance and reconnaissance purposes in oil-gas filed where are often located in multi-glossary region. This paper describes the flight control and navigation system of a fixed-wing unmanned aerial vehicle. Furthermore, an adaptive Kalman filter algorithm with radial basic function neural network is proposed to improve attitude information performance. Moreover, a vector field path following control algorithm is used to realize precise path control. Based on sensor information, system adjusts parameters in real time to provide detail oil-gas field information for control center to make the corresponding decisions efficiency.
Keywords :
Kalman filters; aircraft control; oil drilling; petroleum industry; radial basis function networks; remotely operated vehicles; surveillance; Kalman filter; flight control; multiglossary region; oil-gas field surveillance; radial basis function neural network; reconnaissance; unmanned aerial vehicle; Accelerometers; Control systems; Global Positioning System; Magnetic sensors; Navigation; Noise measurement; Sensor systems; Surveillance; Trajectory; Unmanned aerial vehicles; Adaptive kalman filter; Oil-gas filed; Path-following control;
Conference_Titel :
Machine Learning and Cybernetics, 2008 International Conference on
Conference_Location :
Kunming
Print_ISBN :
978-1-4244-2095-7
Electronic_ISBN :
978-1-4244-2096-4
DOI :
10.1109/ICMLC.2008.4620705
