Intelligent Compound Control Based on Spiking Neural Network for Hex-Rotor Unmanned Aerial Vehicle

This paper focuses on the implementation of trajectory tracking control for a hex-rotor unmanned aerial vehicle. In order to design a high performance robust controller without loss of model information, the characteristic model of the hex-rotor is designed firstly. The intelligent compound controller with golden section feedback controller and spiking neural network feedforward controller are proposed to achieve accurate trajectory tracking and rapid dynamic response. The learning algorithm is devised to gradually approximate the inverse model of the hex-rotor via learning the output of the feedback controller. Eventually, the superior tracking performance of the proposed intelligent control strategy is verified through numerical simulation and prototype experiment.