Attitude control system of small unmanned aerial vehicle for oil-gas field surveillance

Focusing on the high precision control problem of small unmanned aerial vehicle for oil-gas field surveillance, an adaptive Kalman filter algorithm is proposed to get high precision attitude information, and an optimized fuzzy logic control method is trained to realize heading control algorithm. Based on the heading error, flight control parameters are adjusted on-line to provide accurate oil-gas field information for the remote control center to improve decision efficiency. Finally, effectiveness of the proposed method is proved by a series of simulations and flight tests.