A small unmanned aerial vehicle for oil-gas field surveillance

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.