Radial basis function neural network based PID control for quad-rotor flying robot

It is difficult for flying robots with a conventional PID controller to fly stably with external disturbances such as wind. Thus, a flight control method that can change the control parameters of a conventional PID controller according to the external disturbances is described in this paper. The control parameters of the PID controller are automatically adjusted based on a radial basis function neural network (RBFNN). The experimental results show that the control method is capable of effectively dealing with external disturbances.