Robust Attitude Control Method of Electric UAV Based on Bayesian Improved Neural Network
Aiming at the problem that electric UAV cannot precisely control its motion attitude due to the interference of external factors,a robust attitude control method for the electric UAV based on Bayesian improved neural network is proposed.The mathe-matical model of electric UAV is established by considering the composition,motion and dynamic principle of the electric UAV.The sensor equipment is used to detect the real-time pose of the electric UAV,and the attitude control target is determined by the flight path planning way.Considering the wind threat condition and fault state,the attitude control quantity of the UAV is calculated by u-sing Bayesian improved neural network,and the robust attitude controller is used as the hardware support to realize the robust atti-tude control.Through the performance test,it is concluded that under three different wind conditions,the attitude angle control error of the optimized method is always below 0.2°,and the fluctuation degree of the control error not exceeding 0.5°.Compared with the traditional method,the optimized design method has obvious advantages in the accuracy and robustness of attitude control.
Bayesian networkimproved neural networkelectric UAVattitude controlrobust control
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维普
