The longitudinal attitude control of UAV based on GPFN neural network

At present, more and more applications of Unmanned Aerial Vehicles (UAV) makes the control of UAV to be a hot pot in doing research. In the controlling of UAV, traditional PID controller´s parameters are not easily chose and anti-interference ability of the control system is poor. Aiming to improve it, the paper designs a GPFN-PID controller based on GPFN neural network. The controller has the functions of online training, self-training and self-adjusting, which makes the control of UAV longitudinal channel more effective. The simulation results show that both the dynamic characteristics and the anti-interference ability of the control system improve a lot.